Why is synthetic data important? Approximately 328.77 million terabytes of data are created each day. There are limits to what and how you can use this vast amount of data without breaking compliance laws or compromising privacy.

By using synthetic data, organizations can overcome the challenges of data access, data sharing, and data privacy and can still perform critical tasks that depend on real-world data. Moreover, synthetic data helps organizations overcome data scarcity issues, especially when there is a limited amount of actual data available for analysis or AI model training.

Read on to learn more about the best synthetic data software, including their pricing, features, pros and cons, integration and more.

Jump to:

• Top synthetic data software: Comparison chart
• Best synthetic data software
• Key features of synthetic data software
• How to choose the best synthetic data software for your business
• How we evaluated the best synthetic data software
• Bottom line: Top synthetic data software

Top Synthetic Data Software: Comparison Chart

Top 9 Synthetic Data Software

MOSTLY AI Synthetic Data Platform: Best for ease of use

Overall rating: 4.55

• Cost: 5
• Feature Set: 5
• Ease of Use: 5
• Tools: 5
• Support: 2

We included MOSTLY AI for its versatility and comprehensive features. This versatility allowed us to generate realistic and diverse datasets for a variety of use cases.

The MOSTLY AI synthetic data platform allows enterprises across industries to generate high-quality, privacy-preserving synthetic data. Those in the banking, telecommunication, healthcare and insurance can use MOSTLY AI to generate synthetic data for various use cases such as data anonymization, artificial intelligence and machine learning development, testing and product development, and cross-border and enterprise data sharing.

To learn about the tool, I created a free account, which took me less than two minutes to sign up. After signing up, I didn’t have data to upload so I selected one of the three sample data available (Bank Marketing) and proceeded to generate synthetic data based on that sample.

Pricing

• Free forever plan: Allows you to generate up to 100K rows per day.
• Team: $3 per credit.
• Enterprise: $5 per credit.

The actual price you will pay per month depends on the number of data subjects (rows), data points per subject (columns) and creators (users). For instance, a “team plan” user with 1 creator, 100 data points per subject, and 100,000 data subjects will pay $1,860 per month or $22,320 per year, while an “enterprise plan” user with the 1same feature will pay $3,100 per month or $37,200 per year.

Key features

• Time-series support.
• Support for different data types – MOSTLY AI works with various structured data: numerical, categorical, and date-time variables.
• Data rebalancing for data exploration.
• Deployment via Kubernetes or OpenShift.

Pros

• Users say the free plan is feature-rich.
• The platform is easy to learn and use.

Cons

• Dedicated support is limited to enterprise plan users.
• Users says the UI elements can be improved.

MOSTLY AI integrations

You can connect MOSTLY AI with various third-party tools, including:

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform
• Oracle Cloud Infrastructure
• PostgreSQL
• SQL Server
• Snowflake
• Databricks
• Maria DB

Also see: Best Artificial Intelligence Software

Syntho: Best for small and medium businesses

Overall rating: 3.28

• Cost: 0
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 5
• Support: 1

Our research found that Syntho’s synthetic data can be used for data analysis as though it is real data, and the outcomes will be nearly identical to analysis results on the original data.

Syntho is an Amsterdam based startup founded in 2020 that AI-Generated Synthetic data for public organizations, healthcare and finance industries. This synthetic data can be used by organizations for training machine learning models, testing applications, and conducting data analysis without compromising privacy or security.

You can deploy Syntho on-premise, any (private) cloud and Syntho cloud. You can also run the Syntho Engine as a Docker container or python package in your secure IT environment. To do this there are some minimum hardware and software requirements that you must meet.

Minimum hardware requirements

• 32 GB of RAM
• 8 virtual CPUs
• ‘Sufficient’ storage for the data

Minimum software requirements

• Docker Compose Deployment
  • Docker: 1.13.0+
  • Docker-compose: V3 and higher
• Kubernetes Deployment (alternative)
  • Kubernetes: 1.20 and higher
  • helm: v3 and higher

Pricing

Syntho offers three pricing plans: Basic, standard and ultimate. However, the vendor requires interested buyers to contact them for quotes. Pricing depends on the size of your database and your preferred plan.

Key features

• Support time series data and longitudinal data.
• On-premise and private cloud integration.
• PII discovery and generation.
• Auto-scaling via Ray & Kubernetes.

Pros

• Advanced subsetting capability.
• Its self-service capability and easy-to-use interface make it accessible to users of all skill levels.
• Role-based access control (RBAC).

Cons

• Lacks free plan and pricing transparency.
• Some users reported that it does not infer the relationship between databases.

Syntho integrations

Syntho integrates with various databases and filesystems.

• Postgre SQL
• MySQL
• Microsoft SQL Server
• Oracle
• Databricks
• Amazon S3
• Sybase
• MariaDB
• Hive
• IBM DB2

GenRocket: Best for test data management (testers)

Overall rating: 2.43

• Cost: 0.65
• Feature Set: 3.75
• Ease of Use: 1.5
• Tools: 2
• Support: 2

We selected GenRocket because it allows developers and testers to generate data sets with specific characteristics, formats, and structures required for testing different scenarios. This accelerates the testing process and improves the overall quality of software applications.

GenRocket is a software company that specializes in test data generation. It provides a platform that allows users to create and manage realistic and customizable test data for software testing and development purposes. The generated data can be used for various types of testing, including functional, performance, and security testing. GenRocket also offers additional features, such as data masking and subsetting, to ensure data privacy and compliance.

GenRocket has a four-step methodology that enables testers to work independently to provision their own data on demand.

• Model – the data to be generated during testing.
• Design – the variety and volume of data for testing.
• Deploy – test data cases into a test environment.
• Manage – test data projects in a shared repository.

Pricing

GenRocket offer three pricing plans.

• Growth: $55,000 per year. Includes 20 test data projects.
• Business: Quotes available on request. Includes 40 test data projects.
• Advanced: Quotes available on request. Includes 80 test data projects.

Key features

• Offers a library of 730+ data generators.
• Has a library of 101+ data formats.
• Data subsetting and masking.
• Support various test use cases, including realistic data, negative data, data for complex workflows, machine learning data and X12 EDI transaction data.

Pros

• Self-service test data portal.
• Can be integrated into your CI/CD release pipeline.
• User applauds GenRocket technical support.

Cons

• Add-on cost extra fee.
• Steep learning curve.

GenRocket integrations

Some of the top tools GenRocket integrates with include:

• Jenkins
• Azure DevOps
• Selenium
• UiPath
• Katalon
• Tosca

Also see: 100+ Top AI Companies

Tonic.ai: Best for developers

Overall rating: 3.93

• Cost: 1
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 5
• Support: 4

We selected Tonic.ai for its advanced capabilities in generating privacy-conscious synthetic data. Although it requires you to invest time to learn and implement the platform, we found Tonic.ai’s ability to preserve relationships, consistency and complex structures in the data is particularly valuable.

Tonic.ai’s synthetic data platform equips developers with the tools they need to generate “fake data” that closely resemble real data. The platform allows developers to create realistic test data based on your organization’s data, preserving critical relationships and maintaining input-to-output consistency across tables and databases. Tonic.ai is suited for developers and data scientists in finance, ed-tech, insurance, retail and healthcare.

Pricing

Tonic is available in two editions: Tonic cloud and enterprise. To get quotes for these plans, you must contact an in-house expert for custom quote. Tonic offers a 2-week free trial which allows you to try the tool before making a purchase decision.

Key features

• It supports several flat files including .txt, JSON, CSV and XML.
• Schema change alerts capability helps to prevent sensitive data leakage.
• Connects with several CI/CD applications.
• De-identification and AI synthesis capabilities.

Pros

• Ranks high for ease of use and feature set.
• Offers quality customer support.
• Offers subsetting functionality.

Cons

• Some users reported that the tool is somewhat expensive.
• Steep learning curve.

Tonic.ai integrations

This platform integrates with several third-party services including

• PostgreSQL
• MySQL/MariaDB
• SQL Server
• MongoDB
• Vertica
• DocumentDB
• Oracle
• Snowflake
• Redshift
• BigQuery
• Databricks
• Amazon EMR w/ Glue
• Spark

Hazy: Best for financial services

Overall rating: 3.18

• Cost: 0
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 2.5
• Support: 2

Hazy enables businesses to create realistic but entirely fictional datasets that mimic the statistical properties of accurate data without exposing actual customer information. Hazy is used in the financial services industry for fraud modeling, asset management and customer engagement, financial crime, credit risk,  AML, and operational risk.

Hazy’s synthetic data engine is built to handle complex data from large enterprise. Hazy can connect with complex network and security setups, working alongside your original data to provide the highest level of protection, whether it’s stored on your premises or in your private cloud. With Hazy, complex data can be generated for financial service applications and securely stored within the company’s silos.

Pricing

The company doesn’t advertise its rate on its website but encourages interested buyers to get in touch with an in-house expert by completing a short form on their website.

Key features

• Advanced memory optimization and subsetting techniques lower energy usage.
• Deploy on-premises or in the cloud.
• It can create diverse datasets that encompass various scenarios, enabling thorough testing and analysis.

Pros

• Support complex data needs.
• Users applaud Hazy’s built-in privacy tools.

Cons

• May not be suitable for small companies.
• Lacks transparent pricing.

Hazy integrations

Top Hazy integrations:

• Snowflake
• AWS
• Azure

On a related topic: What is Generative AI?

K2View: Best for ML training

Overall rating: 3.60

• Cost: 3.25
• Feature Set: 5
• Ease of Use: 2
• Tools: 5
• Support: 1

K2View offers four synthetic data generation methods, making it easy for teams to generate and integrate synthetic data into CI/CD (Continuous Integration/Continuous Deployment) and ML (Machine Learning) pipelines.

K2View synthetic data generation tool combines four data generation methods: Generative AI, rules engine, entity cloning, and data masking.

• Generative AI: The Generative AI model involves subsetting the required source data to train generative AI models. This data is then masked to ensure privacy and protection. The masked training data is used to train the GPT (Generative Pre-trained Transformer) model, which enables synthetic data generation.
• Rule engine: Rule-based data generation allows you to generate data creation functions based on data classification, and then you can proceed to customize, test, and debug the functions code-free. The rules engine data generation allows users to assign business parameters for the functions and generate data on demand or via API.
• Entity cloning and data masking: Entity cloning allows you to extract, mask, and clone a single business entity and all its data and then create unique identifiers for each cloned entity. The data masking data generation method auto-discovers sensitive and personally identifiable information (PII) and then applies prebuilt, customizable data masking functions. K2View allows you to mask data inflight, as it’s extracted from the sources.

Pricing

K2View pricing is available on demand.

Key features

• Connectors to structured and unstructured data sources.
• Low code/no-code platform.
• Version and roll back datasets on demand.

Pros

• Preserves data relationships.
• Data masking capabilities.
• Enhance data privacy and compliance.

Cons

• Steep learning curve for beginners.
• Users say it’s expensive.

K2View integration

You can connect K2View with the following tools:

• IBM DB2
• Salesforce
• Oracle
• Couchbase

Datomize: Best for data analysts and machine learning engineers

Overall rating: 3.96

• Cost: 4.4
• Feature Set: 3.4
• Ease of Use: 4.5
• Tools: 5
• Support: 3

Our research found that Datomize excels in analytical data sets with its AI-powered data generation capabilities. By leveraging behavior extracted from current data, Datomize allows data analysts and machine learning experts to generate precise and relevant analytical data sets.

The Datomize AI-powered data generation platform allows data analysts and machine learning experts to get the most out of their analytical data sets. It enables you to generate the exact analytical data sets required using the behavior extracted from current data, and creates synthetic data that is similar in properties to the original data but without containing any sensitive or personal information.

Pricing

• Community: Free forever plan with 40 credits per month and up to 20MB input size.
• Starter: $720 per month, billed annually or $800 per month billed monthly. It includes 160 credits per month plus up to 500MB input size.
• Enterprise: Quote available upon request. Unlimited usage and input size.

Key features

• Advanced augmentation capabilities.
• Datomize’s rules-based engine enables users to generate the exact analytical data set needed for any desired scenario.
• Support time-series data.

Pros

• Offers a free forever plan.
• Predict outcomes for any scenario.

Cons

• Limited resources about the product.
• Lacks live chat support.

Datomize integrations

• Python SDKs
• PostgreSQL
• MySQL
• Oracle

Sogeti Artificial Data Amplifier (ADA): Best for testing and development use cases

Overall rating: 2.55

• Cost: 0
• Feature Set: 5
• Ease of Use: 1
• Tools: 5
• Support: 2

Sogeti received high marks for its feature set, which includes the maturity of the product, its ability to serve large enterprises and output fine tune capability. Sogeti also scored 5 out of 5 for “Tools” due to its quality of generated data and scalability.

Part of the Capgemini Group, Sogeti is a Managed Service Provider (MSP) with operational presence in over 100 locations globally. Sogeti ADA generates realistic, usable data based on real data sets. it leverages advanced deep learning based on a combination of artificial neural networks to analyze existing data and create similar but new data points. It can generate large volumes of data, helping organizations tackle the data scarcity challenge.

Pricing

Quotes are available upon request.

Key features

• Realistic and diverse data generation.
• Support for different data types.
• Bias and overfitting reduction.

Pros

• Sogeti’s generated data preserves all the characteristics, correlations and properties of the original data.
• It can be customized to suit your specific needs and use cases.

Cons

• Lacks transparent pricing.
• Usability requires training and expertise.

Sogeti Integrations

Sogeti top integrations include:

• SAP S/4HANA
• Azure
• AWS

Also see: Generative AI Companies: Top 12 Leaders

CA Test Data Manager: Best for complex data generation

Overall rating: 2.78

• Cost: 0
• Feature Set: 3.25
• Ease of Use: 4
• Tools: 5
• Support: 2

Significantly CA Test Data Manager focuses on protecting sensitive information – it offers features such as data masking, which helps to protect sensitive and personal information in test environments by replacing real data with realistic but fake data.

Developed by CA Technologies, CA Test Data Manager is a tool allows you to create, generate, mask, and refresh test data for application testing. CA Test Data Manager automates the process of creating test data by integrating with various data sources and providing data management features like data subsetting, data masking, and synthetic data generation. CA Test Data Manager supports 32-bit and 64-bit physical and virtual Windows machines.

Pricing

Quote available upon request.

Key features

• It has a discovery and profiling feature that allows you to identify personally identifiable information (PII) across multiple data sources.
• It allows you to create future scenarios and unexpected results to test boundary conditions.
• CA’s virtual test data manager capability enables you to generate multiple copies of test data in seconds through cloning.

Pros

• Self-service test data provisioning.
• Integration with governance and risk management.
• Data masking.

Cons

• Limited support.
• Limited resource and product information.

CA Test Data Manager integrations

• Oracle RAC 11g
• Oracle RAC 12c
• IBM DB2 11 for z/OS
• IBM DB2 UDB 11.1
• CA IDMS 19.0
• MySQL 5.6

How to choose the best synthetic data software for your business

When shopping for the best synthetic data software, your organization’s unique needs for synthetic data should be your topmost priority – are you most concerned with compliance, with speed? You need to identify the types of data you need to generate and determine the pain point such data will solve for your business.

After identifying your data needs, it’s time to conduct extensive research – look for solutions that align with your requirements and provide the necessary functionalities. Our evaluation has lessened the research burden for you; there’s quite likely a choice that fits your needs in the list above. Next up is to evaluate the tool’s data generation techniques, customizable capabilities and scalability. And be sure to take the software for a test drive – make sure it actually works for your needs.

How we evaluated the best synthetic data software

We weighed the best synthetic data tools across five categories –each category has sub-categories that helped us evaluate and compare the AI writing tools.

Cost – 20%

We examined the different pricing plans offered by each synthetic data software. This included evaluating the cost of the tool on a monthly or annual basis. We also check to see if the tools offer value for money.

Features set – 30%

We assessed the core data generation capabilities of each tool and its functionalities, including the maturity of the product’s ability to finetune the output and we also confirmed if the tool is geared for large enterprises.

Ease of use – 25%

We looked for intuitive and user-friendly tools, allowing users to navigate and utilize the tool’s features easily.

Tools – 10%

We evaluated each tool’s output quality and scalability level.

Support – 15%

We assessed the availability and responsiveness of customer support channels, such as email, live chat, or phone support. We also considered the availability of resources and documentation, such as user guides, tutorials, or knowledge bases.

Bottom line: Top synthetic data software

There is no one-size-fits-all when selecting the best synthetic data software. For instance, data analysts and machine learning engineers may find Datomize beneficial, while Hazy may be the best option for financial service companies.

The best synthetic data software for you will depend on various factors, including your organization’s specific needs, the use case, the industry, and data compliance requirements. Clearly, given the complexity of this category, you’ll need to do your homework to select the best synthetic data software.

Read next: Generative AI Examples

The post 9 Best Synthetic Data Software 2023 appeared first on eWEEK.

These AI writing tools leverage artificial intelligence algorithms, natural language processing, and machine learning techniques to generate human-like text.

We compiled a list of the best AI writing software, including their features, pricing, and areas of strength and weaknesses.

Jump to:

• Top AI writing tools: Comparison chart
• Best AI writing tools
• How to choose the best AI writing software for your business
• How we evaluated the best AI writing tools
• Bottom Line: Top AI Writing Tools

Top AI writing tools: Comparison chart

Copy.ai: Best for beating writer’s block

Copy.ai is an artificial intelligence writing tool designed for freelance writers, marketers, business owners, and copywriters to create various forms of content, including website copy, sales landing pages, email, social media bio, and blog sections.

The tool allows you to add a brand voice by creating content that reflects your brand voice – this helps it generate copy that aligns with your organization’s persona.

Pricing

• Free: They offer a free plan with up to 2000 words per month.
• Pro: Copy.ai’s pro unlimited words cost $49 per month or $36 per month when billed annually – for up to five seats.
• Team: It costs $249 per month or $186 per month when billed annually – for up to 20 seats.
• Growth: It costs $1,333 per month or $1,000 per month when billed annually – for up to 75 seats.
• Scale: It costs $4,000 per month or $3,000 per month when billed annually – for up to 200 seats.
• Custom Enterprise Plan: Request for a custom quote.

Key features

• Offers over 90 copywriting tools.
• Copy.ai allows you to save and reuse key information via its Infobase feature.
• The platform offers a chat feature that enables sales and marketing teams to interact more naturally with AI.
• Support 25 languages.

Pros

• It has a low learning curve and is easy to use.
• Users applaud its brand voice capability.
• Fast-growing community.
• ​​Various email templates.

Cons

• It lacks creativity and easily gets detected as AI content.
• Lacks full-length article writing feature.

Also see: AI Detector Tools

Rytr: Best for copywriters

Rytr is an AI-powered writing assistant capable of producing content on various topics.

The platform supports 40 use cases, including blog ideas, email, job descriptions, blog section writing and more – you can also manually create your use cases by training Rytr for your specific needs. Note that only paid plan users can create custom use cases.

Pricing

• Free plan: Allow users to generate up to 10k characters per month.
• Saver plan: $9 per month or $90 per year. Users can generate up to 100k characters per month with this plan.
• Unlimited plan: $29 per month or $290 per year.

Key features

• Outline & brief generator.
• Business idea generator.
• Support copywriting frameworks like AIDA (Attention–Interest–Desire–Action) and PAS (Problem–Agitation–Solution).
• Serves as keyword extractor and generator.
• You can use it to create an SEO meta description.

Pros

• Support up to 40 use cases.
• Users can write in 30 languages with up to 20 tones.
• Built-in plagiarism checker.

Cons

• Limited support for low-tier plans.
• Can sometimes overuse phrases.

Also see: Best Artificial Intelligence Software

QuillBot: Best for students and academics

QuillBot is an AI-powered writing assistant that allows you to paraphrase and summarize texts and also functions as a translator and citation generation tool.

If you need a quality paraphrasing tool, I recommend QuillBot, especially for content marketers. But students and people in academia may not prefer the tool because its output doesn’t consistently pass AI detection tools.

Pricing

• Free: Available at no cost with limited capability.
• Premium: This plan is billable monthly, semi-annual and annually.
  • Monthly: $9.95 per month.
  • Semi-Annual: $6.66 per month – $39.95 billed every six months.
  • Annual: $4.17 per month – $49.95 billed every 12 months.
• Team plan: Price varies depending on the number of users.

Key features

• Offers Chrome and Word extensions for grammar checking.
• It can create source citations in various styles, including APA, MLA, and Chicago.
• Support up to nine paraphrasing modes, including creative, simple and academic.
• Language translator capability.

Pros

• Supports up to 23 languages.
• It has a grammar checker that functions like Grammarly.

Cons

• There are only two writing modes for free accounts.
• Manual intervention is often needed.

Also see: Top Generative AI Apps and Tools

Frase.io: Best for SEO teams and content managers

Frase.io is an AI writing assistant designed to help you generate content, improve grammar and spelling, provide suggestions for better writing, and even help with SEO optimization. It can be used for brainstorming ideas and improving writing skills for beginners.

Pricing

Unlike the other tools we reviewed above, Frase doesn’t offer a free plan and their free trial costs $1 for five days.

• Solo: $14.99 per user per month or $12.66 per user per month if paid annually.
• Basic: $44.99 per user per month or $38.25 per user per month if paid annually.
• Team: $114.99 per 3 users per month or $97.75 per 3 users per month if paid annually —extra seat cost $25 per month.
• You can also get unlimited AI content with the Pro Add-On at $35 per month.

Key features

• Automated content briefs.
• Content scoring capability.
• Produce SEO-optimized copy with an AI Writer.
• Google search console (GSC) integration.

Pros

• Content optimization.
• Topic research and SERP analysis capability.
• You can also use Frase to optimize existing content to improve the rankings.

Cons

• Lacks free plan.
• It is expensive for small businesses.

Also see: ChatGPT: Understanding the ChatGPT ChatBot

Anyword: Best for blog writing

Anyword is an AI writing tool that uses machine learning algorithms to generate content. It can assist with writing tasks such as creating ad copy, crafting social media posts, generating blog content, and more.

The tool has a Copy Intelligence functionality analyzes your previously published content to determine which messaging works best on your website, ads, social, and email channels.

Pricing

• Starter: $49 per user per month or $39 per user per month when billed annually.
• Data Driven: $99 per 3 users per month or $79 per 3 users per month when billed annually.
• Business: $499 per 3 users per month or $249 per 3 users per month when billed annually.
• Enterprise: Custom pricing.

Key features

• Support up to 30 languages.
• Google Chrome extension available.
• 100+ performance-driven templates.
• Integrates with Grammarly.

Pros

• Brand voice capability.
• Copy intelligence capability.
• It has a friendly user interface.

Cons

• Anyword has a word limit.
• It is costly for individuals on a budget.

Grammarly: Best for grammatical and punctuation error detection

Grammarly is a popular online writing assistance tool that can help you improve your written communication by checking for grammatical and spelling mistakes and offering suggestions for enhancing clarity, conciseness, and style.

It can be used in various contexts, such as writing emails, reports, essays, and social media posts. Grammarly can be used as a browser extension, a desktop application, or a mobile app and is free with limited features or as a premium subscription with additional functionalities.

Pricing

• Free: Available at no cost.
• Premium: $12 per month, billed annually or $30 when billed monthly.
• Business: $15 per month, billed annually or $25 when billed monthly.

Key features

• Real-time grammar correcting.
• Generative AI assistance.
• Plagiarism checker.
• Checks grammar, spelling, and punctuation and improves writing style.

Pros

• Plagiarism checker.
• Writing style improved.
• Tone and voice suggestions.

Cons

• Grammarly can sometimes provide suggestions that don’t align with the intended meaning or writing style.
• The free plan lacks an advanced clarity feature.

Also see: 100+ Top AI Companies

Hemingway Editor: Best for content readability measurement

Hemingway Editor is a writing tool that helps you enhance the clarity and readability of your written work. It analyzes text and provides various readability suggestions. It highlights lengthy, complex sentences, excessive adverbs, passive voice, and hard-to-read phrases.

It assigns a readability score based on the grade level required to understand the text. It is available both as a web-based application and as a desktop app.

Pricing

The platform is free to use.

Key features

• Improves writing clarity and conciseness.
• Provide a readability score.
• Alternative word suggestion.

Pros

• Helpful color coding and suggestions.
• Works well for assessing the readability and complexity of your work.
• Simplifies the editing process.
• Text formatting functionalities such bold, italics, quotes, numbers, bullets and header tags like H1, H2, and H3.

Cons

• Some suggestions by Hemingway Editor may not align with your writing style or desired tone.
• Limited scope.

Also see: ChatGPT vs. Google Bard 

Writesonic: Best for freelancers and social media marketers

Writesonic uses artificial intelligence technology, specifically natural language processing (NLP), to provide content generation services.

Writesonic’s AI can generate text based on prompts and user input, making it useful for content marketing, copywriting, and other writing-related tasks. While it can be a helpful resource for content creation, the quality of generated content may vary, and human editing is often required to ensure accuracy and coherence.

Pricing

• Free: 10,000 free words per month.
• Small Team: $19 per user per month billed monthly or $15 per user per month billed yearly.
• Freelancer: $20 per user per month billed monthly or $16 per user per month billed yearly.
• Enterprise: Starts at $500 per month.

Key features

• Support GPT 3.5 and GPT 4.
• AI Article and blog writer.
• Paraphrasing tool.
• Sentence expander.
• Text summarizer.
• Story generator.
• Landing page generator.

Pros

• Support up to 30 languages.
• 1-Click WordPress export.
• Integration with third-party services.

Cons

• Lacks advanced editing features.
• Not suitable for tech articles.

AI Writer: Best for high-output bloggers

AI Writer is designed to generate full-length articles in minutes.

The platform allows you to tailor the AI’s writing to your specific needs by selecting from a long list of recommended keywords for your topic or by manually inputting your chosen keywords. It also suggests sub-topics for your article and helps you structure your content with headings; it cites its sources.

Pricing

• Basic Plan: $19 per user per month.
• Standard Plan: $49 per month for three users.
• Power Plan: $375 per month for 10 users.

Key features

• AI text generator.
• SEO editor.
• Publish to WordPress.
• Text rewording capability.

Pros

• It provides list of citations for verification.
• Users finds the content it generates SEO friendly.

Cons

• Requires extensive editing of the generated content.
• Basic user interface.

ContentatScale.ai: Best for creating long-form content

Those looking for an AI writing tool to create blog posts and other long-form content may find ContentatScale features suitable.

The platform claims to pass AI detection tests, indicating that its generated content mimics human writing and is not easily distinguishable from human-written content. ContentatScale also offers an AI detector solution that ranks as one of our review’s best AI detector tools.

If you’d like to check ContentatScale’s claims of passing AI detection tests, see: AI Detector Tools

Pricing

• Paid trial: 7-day paid trial at $39.9.
• Solo: 8 monthly posts, $31 per post —$250 monthly.
• Starter: 20 posts per month, $25 per post —$500 per month.
• Scaling: 50 posts per month, $20 per post —$1,000 per month.
• Scaling: 100 posts per month, $15 per post —$1,500 per month.

Key features

• Keyword, YouTube, Podcast, File, Doc to New Blog Output.
• Unique Voice AI Training options.
• AI detection capability.
• Natural language processing analysis.

Pros

• Offers tier pricing plans to fit all needs.
• Offers content optimization tools.
• WordPress and Shopify integration.

Cons

• No free plan.
• The tool is somewhat expensive.

How to Choose the Best AI Writing Software For Your Business

The best AI writing tool for your business depends on your AI writing needs:

If you need a paraphraser, QuillBot and Writesonic may be the best for you.

• Copy.ai and Rytr are ideal for copywriters and social media managers looking to create short-form content and marketing copy.
• AI Writer, Anyword, and Writersonic are solid options for those looking to create long-form contents like blogs.
• Frase can help you optimize your contents for SEO.
• Grammarly and Hemingway are great options for checking grammar, spelling, and style in your AI-generated content.

Some factors to consider when choosing the best AI writing software for your business:

• Features
• Content quality.
• User interface and experience.
• Customization.

These top tools can be used together for better and quality content. For instance, you can use QuillBot to paraphrase Anyword’s AI-generated text, use Grammarly to correct spelling and punctuation errors and use the Hemmingway App to improve readability.

How We Evaluated the Best AI Writing Tools

We weighed the best tools across five categories –each category has sub-categories that helped us evaluate and compare the AI writing tools.

Cost – 20%

We examined the different pricing plans offered by each AI writing tool. This included evaluating the cost of the tool on a monthly or annual basis, as well as any additional fees or hidden costs. We compared each tool’s cost to its value, looking for tools that offer a high level of functionality for a reasonable price.

Features set – 30%

We assessed the writing capabilities of each tool, including its grammar and spelling correction, sentence rephrasing, and content generation capabilities. We looked for tools that provided accurate and high-quality writing suggestions.

Ease of use – 10%

We looked for tools that have an intuitive and user-friendly interface, allowing users to navigate and utilize the tool’s features easily.

Quality of output – 25%

We evaluated the accuracy and coherence of the generated content produced by each AI writing tool. Tools that could generate clear, well-structured, and error-free content received higher scores.

Support – 15%

We assessed the availability and responsiveness of customer support channels, such as email, live chat, or phone support. Prompt and helpful customer support is essential for users who may encounter issues or need assistance with the tool. We also considered the availability of resources and documentation, such as user guides, tutorials, or knowledge bases.

Bottom Line: Top AI Writing Tools

Our review identified the best AI writing tools to help your writing needs. While the above choices are excellent for now, please check back for updates – this market is constantly changing.

Remember, too, that though these tools are solid, they may not fit everyone perfectly. Ultimately even with a leading AI writing tool, the best results derive from a skilled human writer with the help of an AI writing tool. That’s not likely to change anytime soon.

Read next: We also analyzed the best AI chatbots and the top conversational AI platforms to further your research.

The post 10 Best AI Writing Tools 2023 appeared first on eWEEK.

AI certifications demonstrate understanding and competence in various aspects of AI, such as machine learning, natural language processing, computer vision, robotics, and AI software.

The demand for professionals with AI certifications is great: The artificial intelligence market size is projected to grow from $515.31 billion in 2023 to more than $2 trillion by 2030, at a scorching CAGR of 21.6% – and with this growth comes enormous demand for AI experts.

This guide analyzed the best AI certifications to help you advance your careers and stay up to date with the latest AI technologies.

Jump to:

• Best AI certification comparison chart
• Best 10 AI Certifications 2023
• Reasons to take AI courses and certifications
• How to choose the right AI certification course
• Bottom line: Which AI certification is right for you?

Best AI Certification: Comparison Chart

Here is a head-to-head summary chart of the best AI certification courses with the features, certifying institutions and prices.

Best 10 AI Certifications 2023

AI certification programs usually involve completing training courses, passing assessments or exams, and meeting specific criteria set by certifying bodies or organizations.

AI for Everyone (Coursera)

Non-technical professionals looking for a beginner-friendly AI certification course may find the AI for Everyone course beneficial. The course is hosted on Coursera and taught by Andrew Ng, courtesy of DeepLearning.AI.

This course is designed to provide a comprehensive introduction to artificial intelligence (AI) concepts, terminology, and applications without requiring any prior technical knowledge. It aims to equip non-technical professionals with the necessary understanding and skills to navigate the AI landscape.

The course consists of approximately 10 hours of video lectures, quizzes, and exercises to reinforce learning. Upon completion, students will receive a certificate from Coursera, which can be shared on professional platforms.

Experience required

This course has no prerequisites, making it suitable for both technical and non-technical individuals.

Course content

This course has four modules

• What is AI? – 2 hours to complete.
• Building AI Project –  2 hours to complete.
• Building AI In Your Company –  3 hours to complete.
• AI and Society –  2 hours to complete.

Key course details

Also see: 100+ Top AI Companies 2023

Certified Artificial Intelligence Scientist (CAIS)

The Certified Artificial Intelligence Scientist course offered by the United States Artificial Intelligence Institute is one of the top certifications in artificial intelligence. This comprehensive program covers various AI topics, such as machine learning, deep learning, and Computer Vision with Reinforcement Learning. CAIS also provides hands-on training and real-world projects to enhance practical skills in AI.

Experience required

• PATH 01: Bachelor’s degree or equivalent in any academic discipline and at least five years of experience in AI, ML, Data Science, Business Analytics, Business Intelligence, Project Management, or any Programming language.
• PATH 02: ​​Master’s degree or equivalent in any academic discipline and at least four years experience in AI, ML, Data Science, Business Analytics, Business Intelligence, Engineering, Finance, and Management.
• PATH 03: Must have completed CAIC or other equivalent certification and at least four years experience for Bachelor’s Degree holders and three years experience for Masters Degree holders.

Course content

This exam includes the following general domains and their percentage weights on the exam:

• Artificial Intelligence and Machine Learning (18%).
• Strategic data science and management (15%).
• The economics of AI (12%).
• Supervised deep learning and computer vision (18%).
• AI in marketing (10%).
• Reinforcement learning (RL) (12%).
• Artificial Intelligence, cloud, and security (15%).

Key course details

Also see: Top Generative AI Apps and Tools

Computer Science for Artificial Intelligence

Beginners new to the field of computer science and AI may want to consider the Computer Science for Artificial Intelligence course offered by three experts from Havard University: Doug Lloyd and Brian Yu, who are Senior Preceptors in Computer Science at Harvard University, and David J. Malan, a Gordon McKay Professor of the Practice of Computer Science at Harvard University.

This self-paced Harvard certificate includes two courses, including CS50’s Introduction to Computer Science and CS50’s Introduction to Artificial Intelligence with Python. The course provider claims learners can finish the certification program in five months.

The course offers hands-on projects, which can help learners will gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence.

Experience required

This course doesn’t have prerequisites, meaning individuals of all levels can apply. However, a basic understanding of computer programming concepts would be beneficial.

Course content

• Understanding of computer science and programming.
• Graph search algorithms.
• Reinforcement learning.
• Machine learning.
• Artificial intelligence principles.
• How to design intelligent systems.
• How to use AI in Python programs.

Key course details

Fundamentals of Google AI for Web Based Machine Learning

This certification course is designed to help learners understand what AI really is and what it isn’t. Jason Mayes, a Senior Developer Relations Engineer for TensorFlow.js, and Laurence Moroney, Lead AI Advocate – both from Google – cover the relationship between data, machine learning, and artificial intelligence to help you discuss and use these technologies with others.

This program has two courses: Google AI for everyone, which can be completed in 4 weeks, and Google AI for JavaScript developers with TensorFlow.js, which can be completed in 7 weeks.

Experience required

No prior experience is required to take this course.

Course content

• What AI is and isn’t.
• How machine learning works and how ML, AI and deep learning fit together.
• Applied AI and what programming AI looks like.
• Introduction and overview of the TensorFlow.js library and the advantages of using ML in JavaScript.
• Ways to consume existing machine learning models.
• How to write custom models from a blank canvas (Linear Regression, Convolutional Neural Network).
• How to use industry-standard pre-made models for object detection or natural language processing.
• How to convert Python models to TensorFlow.js format to run them client side in a web browser.

Key course details

For more information, also see: Best Machine Learning Platforms

IBM AI Engineering Professional Certificate

Taught by seven experts, this intermediate-level certificate course offered by IBM takes approximately two months at 10 hours a week to complete. It consists of six courses, which will teach learners how to write Python code that implements various classification techniques, including K-Nearest neighbors (KNN), decision trees, and regression trees; image processing and analysis techniques for computer vision problems; and how to build Deep Neural Networks using PyTorch — the last course includes an AI capstone project with deep learning.

By completing this certificate, students will gain the knowledge and skills needed to start a career in AI engineering or further their existing careers.

Experience required

While there is no specific prerequisite for the course, the IBM AI Engineering Professional Certificate is an intermediate-level course which is recommended for individuals with some background knowledge or experience in programming and computer science.

Course content

• Machine Learning with Python.
• Introduction to Deep Learning & Neural Networks with Keras.
• Introduction to Computer Vision and Image Processing.
• Deep Neural Networks with PyTorch.
• Building Deep Learning Models with TensorFlow.
• AI Capstone Project with Deep Learning.

Key course details

Artificial Intelligence A-Z 2023: Build an AI with ChatGPT4 (Udemy)

With over 231,410 students, Artificial Intelligence A-Z 2023 is a best seller on Udemy. It is best for Artificial Intelligence, Machine Learning, or Deep Learning enthusiasts.

The course teaches learners how to make a virtual self-driving car, make an AI to beat games, Q-learning, deep Q-learning, deep convolutional Q-learning and solve real-world problems with AI. The instructors provide learners with downloadable Python code templates for every AI they build in the course.

Experience required

• High School Maths.
• Basic Python knowledge.

Course content

• Part 0: Fundamentals of Reinforcement Learning.
• Part 1: Deep Q-Learning.
• Part 2: Deep Convolutional Q-Learning.
• Part 3: A3C.

Key course details

Artificial Intelligence Engineer (AIE) Certification Process by the Artificial Intelligence Board of America (ARTiBA)

The Artificial Intelligence Engineer (AIE) certification process is offered by the Artificial Intelligence Board of America (ARTiBA), which is a professional membership body dedicated to promoting and advancing artificial intelligence (AI) practices.

To receive the AIE certification, individuals must undergo a structured evaluation process assessing their knowledge and skills in various AI-related domains. The certification process consists of the following steps:

• Check your eligibility.
• Create your Myartiba account.
• AIE registration confirmation.
• Release of AIE learning material.
• Prepare for the exam & register.
• Certification award.

Experience required

ARTiBA has three registration tracks open for the AiE certification.

• AIE Track 1: Learner should have completed an Associate degree or diploma in Computer Science or Information Technology or any other related discipline plus a ​​minimum of 2 years of work history in any of the computing sub-functions.
• AIE Track 2: Learner should have completed a bachelor’s degree in Computer Science or Information Technology or any other related discipline plus a ​​minimum of 2 years of work-history in any computing sub-functions and must have a good understanding of computer programming.
• AIE Track 3: Current and past students have a Master’s degree in Computer Science or Information Technology or any other related discipline plus a ​​minimum two years of work history in any computing sub-functions; must have a good understanding of computer programming.

Course content

• Essentials of Artificial Intelligence & Machine Learning (27%).
• Essentials of AI & ML Programming (21%).
• Essentials of Natural Language Processing (26%).
• Essentials of Neural Networks & Deep Learning (26%).

Key course details

Also see: Best Artificial Intelligence Software 2023

Artificial Intelligence Graduate Certificate

Stanford School of Engineering is the issuing body of the Artificial Intelligence Graduate Certificate. This particular certification process is a bit different from the ones we have analyzed so far: it requires a significant time commitment, as it’s designed like a proper degree course – you should expect an average of 15-20 hours per week for the lecture and homework assignments. To earn the certificate, you must complete one required course and three elective courses and receive a B (3.0) or better in each course.

This program covers various aspects of AI, including the principles and techniques of AI, ML, computational logic, NLP, NLU, robotics, Deep Learning, computer vision and more.

Experience required

• Strong backgrounds in programming (C/C++, python), linear algebra, calculus, as well as statistics and probability.
• Bachelor’s degree with a minimum 3.0 grade point average.
• Each course may have individual prerequisites.

Course content

• Artificial intelligence principles and techniques.
• Machine learning.
• Natural Language Processing with deep learning.
• Computer vision.
• Reinforcement learning.

Key course details

Microsoft Certified: Azure AI Engineer Associate

Azure AI Engineer Associate is a certification offered by Microsoft that validates an individual’s skills in designing and implementing AI solutions using Azure technologies such as Azure Cognitive Services and Azure Applied AI services.

According to Microsoft, this course will allow you to plan and manage an Azure AI solution, implement image and video processing solutions, implement natural language processing solutions, implement knowledge mining solutions, and implement conversational AI solutions.

You can prepare for this certification in two ways: self-paced and instructor-led training.

Experience required

• Knowledge of Python and C# programming.
• Prerequisites vary based on each learning path.

Course Content

• Prepare for AI engineering.
• Provision and manage Azure AI services.
• Process and translate text with Azure AI services.
• Process and translate speech with Azure AI speech services.
• Create a language understanding solution with Azure AI language.
• Build a question-answering solution.
• Build custom text analytics solutions.
• Create conversational AI solutions.
• Create computer vision solutions with Azure AI vision.
• Extract text from images and documents.
• Implement knowledge mining with Azure cognitive search.
• Develop generative AI solutions with Azure Openai service.

Key course details

Also see: Generative AI Startups 

Artificial Intelligence: Business Strategies and Applications

UC Berkeley designed this course for business professionals who are interested in understanding how artificial intelligence (AI) can be leveraged to drive business growth and innovation. The course covers various aspects of AI and its application in different business contexts. It starts by explaining the fundamental concepts of AI and machine learning and then explores neural networks and deep learning, computer vision, and NLP.

Experience required

This course has no specific prerequisites, but knowledge of business management is a plus.

Course Content

• Introduction–AI and business.
• Machine learning basics.
• Neural networks and deep learning.
• Key applications: computer vision & natural language processing.
• Robotics.
• Ai strategy.
• AI and organizations: building your AI team.
• The future of AI in business.

Key course details

Benefits of AI Courses and Certifications

There are several compelling reasons to take AI courses and certifications:

• Skill development: AI courses provide an opportunity to develop new skills and gain a deep understanding of artificial intelligence concepts.
• Career advancement: By acquiring AI skills and certifications, you can stand out, increase your employability, and access higher-paying job roles.
• Industry recognition: AI certifications serve as a recognized proof of your competency.
• Personal growth: AI courses challenge you to think critically, innovate, and approach problems from a different perspective.
• Market demand: The skills gained through AI courses and certifications are highly sought after by industries across sectors, including healthcare, finance, retail, manufacturing, and more. These courses can open up diverse job prospects and increase your job market value.

How to Choose the Right AI Certification Course

When researching the best AI certification course for you, you must consider certain factors unique to you. The best AI certification course for you will depend on your learning objectives, current field/industry knowledge, and learning budget. The list below can help you select the best course for you.

1. Learning objectives: Look for a course that covers the specific areas of AI that you are interested in or want to specialize in, such as machine learning, natural language processing, or computer vision. Also consider the depth and breadth of the course curriculum to ensure it aligns with your learning goals.
2. Course format and delivery: Consider your preferred mode of learning, whether it’s online, in-person classroom training, or a combination of both.
3. Instructor expertise: Check the qualifications, industry experience, and expertise of the course instructors.
4. Course resources: Consider the support and resources available during and after the course.
5. Cost: Evaluate the course fees and compare them with the value and benefits you will receive. Consider any financial aid or scholarships available.
6. Certification and career outcomes: Check if the course provides a recognized certification upon completion and consider the career outcomes and job placement records of the course graduates.

Remember that AI is a practical field, so seek courses that emphasize hands-on projects and real-world applications.

For more information, also see: Top Robotics Startups

Bottom Line: Which AI Certification is Right for You?

The right AI certification for you depends on your specific interests, career goals, and existing knowledge in the field. Truly finding the best course for you means evaluating the full range of AI training, but here are a few picks based on our analysis:

• UC Berkeley Artificial Intelligence: Business Strategies and Applications is best for business executives.
• Microsoft Certified: Azure AI Engineer Associate is ideal for developers interested in Azure AI services.
• AI for Everyone and Artificial Intelligence A-Z 2023: Build an AI with ChatGPT4 are best for beginners.

Read next: The AI Market: An Overview 

The post 10 Top Artificial Intelligence Certifications 2023 appeared first on eWEEK.

Large language model use transformers to perform natural language processing (NLP) tasks like language translation, text classification, sentiment analysis, text generation, and question-answering.

LLMs are trained with a massive amount of datasets from various sources. Their immense size characterizes them – some of the most successful LLMs have hundreds of billions of parameters.

Jump to:

• What is the Importance of Large Language Models?
• How Do Large Language Models Work?
• Types of Large Language Models
• Large Language Model Examples
• What Is the Purpose Behind Large Language Models?
• Bottom Line: Large Language Models

What is the Importance of Large Language Models?

The advancement in artificial intelligence and generative AI is pushing the boundaries of what we once thought of as far-fetched; LLMs are trained on hundreds of billions of parameters and are used to tackle the obstacles of interacting with machines in a human-like manner.

LLMs are beneficial for problem-solving and help businesses with communication-related tasks, as they are used to generate human-like text, making them invaluable for tasks such as text summarization, language translation, content generation, and sentiment analysis.

Large language models bridge the gap between human communication and machine understanding. Aside from the tech industry, LLM applications can also be found in other fields like healthcare and science, where they are used for tasks like gene expression and protein design. DNA language models (genomic or nucleotide language models) can also be used to identify statistical patterns in DNA sequences. LLMs are also used for customer service/support functions like AI chatbots or conversational AI.

Also see: Top Generative AI Apps and Tools

How Do Large Language Models Work?

For a LLM to perform efficiently with precision, it’s first trained on a large volume of data, often referred to as a corpus of data. The LLM is usually trained with both unstructured and structured data before going through the transformer neural network process.

After pre-training on a large corpus of text, the model can be fine-tuned on specific tasks by training it on a smaller dataset related to that task. LLM training is primarily done through unsupervised, semi-supervised, or self-supervised learning.

Large language models are built on deep learning algorithms called transformer neural networks, which learn context and understanding through sequential data analysis.

The concept of the Transformer was introduced in a 2017 paper titled “Attention Is All You Need” by Ashish Vaswani, Noam Shazeer, Niki Parmar, and five other authors. The transformer model uses an encoder-decoder structure; it encodes the input and decodes it to produce an output prediction. The following graphics are from their paper:

Multi-head self-attention is another key component of the Transformer architecture, and it allows the model to weigh the importance of different tokens in the input when making predictions for a particular token. The “multi-head” aspect allows the model to learn different relationships between tokens at different positions and levels of abstraction.

Also see: Best Artificial Intelligence Software

Types of Large Language Models

The common types of LLMs are as follows:

Language Representation Model

Many NLP applications are built on language representation models (LRM) designed to understand and generate human language. Examples of such models include GPT (Generative Pre-trained Transformer) models, BERT (Bidirectional Encoder Representations from Transformers), and RoBERTa. These models are pre-trained on massive text corpora and can be fine-tuned for specific tasks like text classification and language generation.

Zero-shot Model

Zero-shot models are known for their ability to perform tasks without specific training data. These models can generalize and make predictions or generate text for tasks they have never seen before. GPT-3 is an example of a zero-shot model – it can answer questions, translate languages, and perform various tasks with minimal fine-tuning.

Multimodal Model

LLMs were initially designed for text content. However, multimodal models work with both text and image data. These models are designed to understand and generate content across different modalities. For instance, OpenAI’s CLIP is a multimodal model that can associate text with images and vice versa, making it useful for tasks like image captioning and text-based image retrieval.

Fine-tuned or Domain-specific Models

While pre-trained language representation models are versatile, they may not always perform optimally for specific tasks or domains. Fine-tuned models have undergone additional training on domain-specific data to improve their performance in particular areas. For example, a GPT-3 model could be fine-tuned on medical data to create a domain-specific medical chatbot or assist in medical diagnosis.

Also see: Generative AI Companies: Top 12 Leaders 

Large Language Model Examples

You might have heard of GPT – thanks to ChatGPT buzz, a generative AI chatbot launched by Open AI in 2022. Aside from GPT, there are other noteworthy large language models.

• Pathways Language Model (PaLM): PaLM is a 540-billion parameter transformer-based LLM developed by Google AI. As of this writing, PaLM 2 LLM is currently being used for Google’s latest version of Google Bard.
• XLNet: XLNet is an autoregressive Transformer that combines the bidirectional capability of BERT and the autoregressive technology of Transformer-XL to improve the language modeling task. It was developed by Google Brain and Carnegie Mellon University researchers in 2019 and can perform NLP tasks like sentiment analysis and language modeling.
• BERT: Bidirectional Encoder Representations from Transformers is a deep learning-based technique for NLP developed by Google Brain. BERT can be used to filter spam emails and improve the accuracy of the Smart Reply feature.
• Generative pre-trained transformers (GPT): Developed by OpenAI, GPT is one of the best-known large language models. It has undergone different iterations, including GPT-3 and GPT-4. The model can generate text, translate languages and answer your questions in an informative way.
• LLaMA: Large Language Model Meta AI was publicly released in February 2023, with four model sizes: 7, 13, 33, and 65 billion parameters. Meta AI released LLaMA 2 in July 2023, available in three versions, including 7B, 13B, and 70B parameters.

What Is the Purpose Behind Large Language Models?

While LLMs are still under development, they can assist users with various tasks and serve their needs in various fields, including education, healthcare, customer service, and entertainment. Some of the common purposes of LLMs are:

• Language translation
• Code and text generation
• Question answering
• Education and training
• Customer service
• Legal research and analysis
• Scientific research and discovery

Bottom Line: Large Language Models

Large language models represent a transformative leap in artificial intelligence and have revolutionized industries by automating language-related processes.

The versatility and human-like text-generation abilities of large language models are reshaping how we interact with technology, from chatbots and content generation to translation and summarization. However, the deployment of large language models also comes with ethical concerns, such as biases in their training data, potential misuse, and the privacy considerations of their training. Balancing their potential with responsible and sustainable development is essential to harness the benefits of large language models.

Also see: 100+ Top AI Companies 2023

The post What Are Large Language Models? appeared first on eWEEK.

An ever-growing number of generative AI chatbots is now entering the market, but not all chatbots are created equal. We analyzed the best generative AI chatbots to help you determine the best conversational AI app for your business.

Here are our picks for the top generative AI chatbot software. Jump to:

• Top generative AI chatbot software comparison chart
• Bing Chat Enterprise: Best for organizations in the Microsoft ecosystem
• ChatGPT: Best for versatility and advanced generative AI features
• OpenAI Playground: Best for customizability
• Perplexity AI: Best for finding information on the Internet
• YouChat: Best for students and researchers
• ​​Chatsonic: Best for individuals in the creative industries
• Google Bard: Best for brainstorming ideas
• Socrates.ai: Best for internal knowledge-base management
• HuggingChat: Best for developers
• Jasper: Best for marketing and sales team
• Key features of generative AI chatbot software
• How do I choose the best generative AI chatbot software for my business?
• How we evaluated the best generative AI software
• Frequently Asked Questions (FAQ)
• Bottom Line: Best AI Chatbots

Top Generative AI Chatbot Software: Comparison Chart

We compared the key features of the top generative AI chatbot software to help you determine the best option for your company:

Please note: All ratings are based on a range of 1 to 5, with 5 being the best option.

Bing Chat Enterprise: Best chatbot for organizations in the Microsoft ecosystem

Overall rating: 3.13

• Cost: 3.95
• Feature Set: 3.5
• Ease of Use: 1.75
• Quality of Output: 2.5
• Support: 4

Microsoft generative AI tool Bing Chat Enterprise uses GPT- 4 – a large language model – to generate natural language responses to users’ queries. Bing Chat Enterprise has three conversation styles: Creative, balanced and precise. These styles help users set the tone for the expected response to their query. Bing Chat Enterprise is available in 160 regions; significantly, users can also access it via the Windows Copilot Sidebar, making this app easily accessible.

Pricing

Bing AI chat is available at no additional cost for customers who are licensed for Microsoft 365 E3, E5, Business Standard, Business Premium, or A3 or A5 for faculty. If you don’t have those licenses, you can purchase Bing AI as a standalone tool for $5 monthly.

Features

• A versatile mix of conversation styles for different enterprise AI use cases.
• Bing’s citation capability allows you to fact-check its output.
• It allows users to upload an image and it can also generate an image for you.

Pros

• Bing’s citation can enable you to continue your research on your own.
• The user interface is visually appealing and easy to navigate.
• It has an AI built-in image generator.

Cons

• While trying the tool on a browser other than Edge, I got an error message: “You’ve reached the conversation limit for today. Sign in to continue your chat.” I found that other users experience this too, even though they are signed in or haven’t used the tool before. To resolve this issue, I downloaded Microsoft Edge.
• Limited to 30 responses per conversation.

Also see: Top Generative AI Apps and Tools

ChatGPT: Best chatbot for versatility and advanced generative AI features

Overall rating: 4.51

• Cost: 4.15
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 3.75
• Support: 5

Developed by OpenAI as part of the GPT (Generative Pre-trained Transformer) series of models, ChatGPT is a natural language processing tool designed to engage in human-quality conversations with users. The platform can perform NLP tasks, such as answering questions, providing recommendations, summarizing text, and translating languages. Aside from content generation, developers can also use ChatGPT to assist with coding tasks, including code generation, debugging help, and answering programming-related questions.

Pricing

• Free: You can use the free plan at no cost.
• ChatGPT Plus: $20 per month.
• Enterprise plan: Custom quotes.

Features

• Analytics dashboard to understand usage for enterprise users.
• Multilingual features: It can understand and generate text in multiple languages.
• Contextual understanding of extended conversation.

Pros

• Data encryption at rest (AES-256) and in transit (TLS 1.2+).
• ChatGPT can assist in completing sentences or paragraphs for users.
• Explain complex concepts.

Cons

• The free plan is limited to GPT-3.5.
• Platform knowledge is limited to 2021.
• Biases and inaccurate information.

For more information: Full ChatGPT review.

OpenAI Playground: Best chatbot for customizability

Overall rating: 3.0

• Cost: 4.15
• Feature Set: 5
• Ease of Use: 0.55
• Quality of Output: 2.5
• Support: 2

OpenAI Playground was designed by the same generative AI company that created ChatGPT. It is a web-based environment allowing users to experiment with different OpenAI models, including GPT-4, GPT-3.5 Turbo, and others. OpenAI Playground is suitable for advanced users looking for a customizable generative AI chatbot model that they can easily fine-tune to suit their needs.

Pricing

OpenAI Playground is priced per 1,000 tokens (1,000 tokens equals to 750 words). Pricing for this tool varies based on your chosen model. New users can get $5 in free credit to use for their first three months.

GPT-4 models

• 8K context: Input costs $0.03 per 1K tokens while output costs $0.06 per 1K tokens.
• 32K context: Input costs $0.06 per 1K tokens while output costs $0.12 per 1K tokens.

GPT-3.5 Turbo

• 4K context: Input costs $0.0015 per 1K tokens, while output costs $0.002 per 1K tokens.
• 16K context: Input costs $0.003  per 1K tokens, while output costs $0.004 per 1K tokens.

Features

• Text and completion summarization capability.
• Multiple options for model selection.
• Language translation capability.
• Sentiment analysis.

Pros

• Available on the web and app for Android and iOS devices.
• Highly customizable.

Cons

• Limited creativity.
• Privacy concerns.

Also see: The Benefits of Generative AI 

Perplexity AI: Best chatbot for finding information on the Internet

Overall rating: 4.19

• Cost: 4.15
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 5
• Support: 2

Perplexity AI is a generative AI chatbot/search/answer engine that allows users to express queries in natural language​​ and provides answers based on information gathered from various sources on the web. When you ask a question on Perplexity AI, it provides the answer to your query and suggests related follow-up questions; you can either select from the suggested related questions or type yours in the text field.

Perplexity AI’s Copilot feature can guide users through the search process with interactive follow-up questions, multiple searches, and summarized results – this capability is helpful when researching complex topics. However, it’s limited to five searches every four hours for free plan users and up to 300 searches for paid users.

Pricing

• Free: Available at no cost with limited features.
• Pro: It costs $20 per month or $200 per year.

Features

• Support Claude-2 and GPT-4.
• Support 30 languages, including English, Bengali, Danish and more.
• Text and PDF file upload capability.

Pros

• Cites information sources.
• Mobile app for iOS and Android device users.

Cons

• File upload is limited to three per day for free users.
• Customer support can be improved.

YouChat: Best chatbot for students and researchers

Overall rating: 3.64

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 5
• Quality of Output: 3.75
• Support: 1

Designed by You.com, YouChat is an AI-powered generative chatbot that can summarize text, write code, suggest ideas, compose emails and answer general questions based on information available on the web. It also cites its information source, making it easy to fact-check the chatbot’s answers to your queries. YouChat combines various elements in its search results, including images, videos, news, maps, social, code, and search engine results on the subject.

Pricing

• Free: Available at no cost for up to 10 AI writing generations.
• YouPro: $9.99 per month.
• YouPro for Education: $6.99 per month.

Features

• Code generator.
• Multimodal search capability.
• Supports social media profiles.

Pros

• Chrome extension available.
• It provides interactive search results with various elements.

Cons

• Contextual understanding can be improved.
• It sometimes displays outdated links or information.

Also see: Generative AI Examples

Chatsonic: Best chatbot for individuals in the creative industries

Overall rating: 4.03

• Cost: 4.55
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 2.5
• Support: 2

Trained and powered by Google Search to converse with users based on current events. Chatsonic advertises itself as a ChatGPT alternative. The AI chatbot is a product of Writesonic, an AI platform for content creation. When using Chatsonic, you can toggle on the “Include latest Google data” button to add real-time trending information.

Chatsonic has a Generate AI Art feature that enables it to generate digital AI artwork for users’ consumption. It also has a personality functionality that allows users to select from a list of personalities such as interviewer, math teacher, motivational coach, English translator and more – this allows the tool to provide tailored responses based on their chosen persona.

Pricing

• Free trial: Up to 10,000 words per month.
• Unlimited: $20 per month when billed monthly or $16 per month when billed yearly – limited to one user.
• Business: $19 per month when billed month or $12.67 per month when billed annually – for up to 200,000 words for GPT 3.5 or  33,3333 words for GPT 4.0 – limited to one user. With this plan, you can increase your word count and number of users at an additional cost.
• Enterprise: Custom quote.

Features

• It has a Sonic Editor (Google Docs-like editor).
• Integration with third-party apps.
• Offers over 100 AI templates.

Pros

• Support about 25 languages.
• Landing page generator capability.
• Browser extension available.

Cons

• Priority support is limited to business and enterprise plan users.
• Free plan lacks email support.

On a related topic: What is Generative AI?

Google Bard: Best chatbot for brainstorming ideas

Overall rating: 4.28

• Cost: 5
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 1

Google Bard is an AI-powered LLM chatbot built on the PaLM2 (Pathways Language Model, version 2) AI model. You can export your Google Bard conversation to Google Docs or Draft in Gmail – the platform also allows you to create a shareable public link you can send to a third party. Google Bard is still relatively new and is being actively developed.

Pricing

Google Bard is free to use.

Features

• Ability to export conversation.
• Its “Google it” function directs you to a search engine, providing more information on your query.
• It can generate code in at least 20 programming languages.

Pros

• It has a vast knowledge base.
• Cites sources of information.

Cons

• Users reported that Google Bard is slow to respond, especially when users ask complex questions.
• It sometimes has been known to give inaccurate or incomplete information.

Also see: ChatGPT vs. Google Bard: Generative AI Comparison 

Socrates.ai: Best chatbot for internal knowledge-base management

Overall rating: 2.1

• Cost: 0 [no information available]
• Feature Set: 3
• Ease of Use: 3
• Quality of Output: 2.5
• Support: 2

Socrates.ai is an artificial intelligence platform that provides businesses with conversational AI solutions. It enables companies to create and deploy conversational agents that can interact with users naturally. It can be integrated into various channels such as websites, mobile apps, and messaging platforms to enhance user experience and support automation.

Pricing

Available upon request.

Features

• Integration with third-party enterprise apps.
• It has a database of about 1000 of employee questions.
•  Supports natural language processing and understanding.
• Bot-to-bot conversations.

Pros

• Flexible deployment – SaaS or On-Premise.
• It offers a pre-built and pre-tested content that includes a glossary of terms, abbreviations, and acronyms that can be customized for your company.

Cons

• Lacks transparent pricing.
• Support can be improved.

Also see: Generative AI Companies: Top 12 Leaders

HuggingChat: Best chatbot for developers

Overall rating: 3.33

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 4.75
• Quality of Output: 1.25
• Support: 1

Developed by Hugging Face, HuggingChat is a chatbot based on the Open Assistant Conversational AI Model. It uses NLP and ML algorithms to interact with users and can generate answers to questions, write essays, write code, translate text, and construct emails. The platform has been trained on a large dataset of diverse conversations and can learn from new interactions.

Pricing

HuggingChat is free to use. You can also subscribe to the pro plan at $9 per month to get early access to new features. They also offer an enterprise hub plan at $20 per user per month.

Features

• It has a web search functionality that complements its response with web content.
• Multilingual support.
• It can debug and write code and create Excel formulas.

Pros

• Easy to use.
• Highly customizable – the Hugging Face platform allows developers to create their custom intents, entities, and actions.

Cons

• Knowledge-base not up to date.
• The platform sometimes gives an incomplete answer.

Also see: Generative AI Startups

Jasper: Best chatbot for marketing and sales team

Overall rating: 4.23

• Cost: 2.65
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 3

Jasper generative AI chatbot can be trained on your brand voice to interact with your customer in a personalized manner. Jasper partners with OpenAI and uses GPT 3.5 and GPT 4 language models and their proprietary AI engine. The company also sources from other models such as Neo X, T5, and Bloom. One of Jasper’s strong points is its brand voice functionality, which allows teams and organizations to create on-brand content.

Pricing

• Creator: It costs $49 per month when billed monthly and $39 per month when billed annually.
• Teams: It costs $125 per month when billed monthly and $99 per month when billed annually.
• Business: Custom quotes.

Features

• Browser extension available.
• Support up to 30 languages.
• Integrates with  Zapier, Webflow, Make, Google Sheets, and other tools.
• Collaboration capability.

Pros

• Provides up-to-date information and cites sources.
• Offers over 50 built-in templates.
• Its user management capability allows you to control who can access documents in your workspace with user-specific permission settings to make private, view, edit, or be available to everyone.

Cons

• Some users reported that Jasper is somewhat pricey.
• Users may experience incomplete sentences when using Focus mode with Jasper.

Key Features of Generative AI Chatbots

Natural Language Processing

Natural language processing is an important feature of a generative AI chatbot. NLP enables the AI chatbot to understand and interpret casual conversational input from users, allowing them to have more human-like conversations. With NLP capabilities, generative AI chatbots can recognize context, intent, and entities within the conversation.

Context Understanding

Chatbot’s ability to comprehend and retain context during conversations enables a more seamless and human-like conversation flow. A quality artificial intelligence chatbot can maintain context and remember previous interactions, providing more personalized and relevant responses based on the conversation history. This enables chatbots to provide more coherent and relevant replies.

Personalization

When shopping for a generative AI chatbot software, customization and personalization capabilities are important factors to consider, as it enables the tool to tailor responses based on user preferences and history. ChatGPT, for instance, allows businesses to train and fine-tune chatbots to align with their brand, industry-specific terminology, and user preferences.

Multilingual support

AI chatbot’s ability to communicate in multiple languages makes it appealing to global audiences. This functionality also allows the chatbot to translate text from one language to another.

Also see: Best Artificial Intelligence Software 2023

How to Choose the Best Generative AI Chatbot For Your Business

The best generative AI chatbot for your company serves your business’s needs and balances quality service with moderately expensive – or affordable pricing – based on what  works with your budget, plus the necessary AI features you need for your operations.

Organizations in the Microsoft ecosystem may find Bing Chat Enterprise beneficial, as it works better on Edge browser. ChatGPT does not cite sources, but it is one of the most versatile and creative AI chatbots. Google Bard cites sources and provides up-to-date information, but its response time is sometimes slow. Bing Chat and Chatsonic can generate AI images as part of the answer to your query.

What seems like positives to you may be negatives to another user and vice versa. The best tool for your business is unique to you – conduct your own research, identify your goals, and shop for a tool that offers features and capabilities that meet your requirements.

How We Evaluated the Best Generative AI Chatbots

Cost – 20%

We reviewed each AI chatbot pricing model and available plans, plus the availability of a free trial to test out the platform. Our research found that some platforms are completely free while some offer both free and paid plans – a tool like Google Bard gives you access to all its features for free, ChatGPT has a free plan with access to GPT 3.5 capabilities, while GPT 4 requires a monthly subscription. On the other hand, Jasper is a completely paid chatbot offering a seven-day free trial.

Features set – 30%

Features carry the most weight (30%) in our evaluation process. We evaluated various capabilities offered by each generative AI software, including multi-language support, the ability to accept spoken word input, the programmability of the solution, the kind of users it is built for and customization options.

Ease of use – 25%

We assessed each generative AI software’s user interface and overall user experience. This included evaluating the ease of installation, setup process, and navigation within the platform. A well-designed and intuitive interface with clear documentation, support materials and the AI chatbot response time contributed to a higher score in this category.

Quality of output – 10%

To determine the output quality generated by the AI chatbot software, we analyzed the accuracy of responses, coherence in conversation flow, and ability to understand and respond appropriately to user inputs. We selected our top solutions based on their ability to produce high-quality and contextually relevant responses consistently.

Support – 15%

Our analysis also considered the level of support provided by the AI software provider. We assessed the availability and responsiveness of customer support, including customer service hours, email support, live chat support and knowledge base.

AI Chatbots: Frequently Asked Questions (FAQs)

We answered the most commonly asked questions about AI chatbots below.

What features should businesses look for in AI chatbots?

Key features to look for in AI chatbots include NLP capabilities, contextual understanding, multi-language support, pre-trained knowledge and conversation flow management. It is also important to look for a tool with a high accuracy rating, even if the questions asked are complex or open-ended.

Why are AI chatbots important for businesses?

AI chatbots are important to businesses because they enhance customer experience and provide various operational benefits such as improved customer experience, personalized experiences, cost reduction, and increased productivity.

How can AI chatbots enhance customer support and engagement?

AI chatbots can boost customer support by providing 24/7 support, answering common questions, and personalizing interaction based on customer preferences (for instance, multilingual AI chatbots can communicate in multiple languages, enabling businesses to assist customers from different regions.

Bottom Line: Top AI Chatbots

Determining the “best” generative AI chatbot software of 2023 can be subjective, as it largely depends on the business’s specific needs and objectives. The landscape of AI chatbot software is continuously evolving, and new chatbot entrants may offer innovative features and improvements over existing solutions. Therefore, the best chatbot for your business will vary based on factors such as industry, use case, budget, and desired features – there is no “one size fits all” solution.

Read next: 100+ Top AI Companies 2023

The post 10 Best AI Chatbots 2023 appeared first on eWEEK.

We highlight the top Conversational AI platforms empowering enterprises to deliver personalized, efficient, and engaging customer experiences.

Here are our picks for the best conversational AI platforms:

• IBM Watson Assistant: Best for advanced features
• Kore.ai: Best for automation
• Avaamo.ai: Best for conversational analytics
• Amazon Lex: Best for affordability
• Oracle Digital Assistant: Best for performing operational tasks
• Microsoft Bot Framework: Best for developers
• Cognigy.AI: Best for contact center automation
• Yellow.ai: Best for customization
• Acquire: Best for ease of use and simplicity
• Clinc: Best for financial service companies
• Top conversational AI platform: Comparison chart
• Top conversational AI platform for your business
• Key features of conversational AI platforms
• Benefits of working with conversational AI platforms
• How do I choose the best conversational software for my business?
• How we evaluated conversational software
• Frequently Asked Questions (FAQ)
• Bottom Line: Conversational AI Platforms

Top Conversational AI Platform: Comparison chart

Here is a head-to-head comparison summary of the best conversational AI platforms.

IBM Watson Assistant: Best for advanced features

Built on deep learning, machine learning, and natural language processing (NLP) models, the IBM Watson Assistant conversational AI platform enables your teams to build AI-powered voice agents and chatbots that deliver automated self-service support across all channels and touchpoints. It can search and find answers to customer inquiries in existing documents, websites, and knowledge bases in order to complete the user’s intended action.

The platform allows you to build an AI chatbot that can be trained to understand user requests and adapted to your business scenarios – it also can recognize plain-language responses from your customers, like synonyms, dates, times, and numbers. It integrates with various third-party services, including WhatsApp, Slack, Facebook Messenger, Kustomer, Zendesk and more.

Pricing

IBM Watson is available for free with basic features and paid versions with advanced features.

• Lite: Available at no cost. It includes 1,000 unique monthly active users (MAUs), up to 10,000 messages per month, up to five skills (Dialog, Action, Search), seven days of usage analytics, session inactivity timeout of 5 minutes, and services deleted after 30 days of inactivity.
• Plus: Starts at $140 per month. It supports phone and SMS integration and includes 1,000 MAUs. Additional MAUs are billed at $14 per 100 MAUs.
• Enterprise: Quotes available on request.

Features

• Supported channels include webchat, telephony and voice add-ons, SMS and MMS, messaging channel integrations and custom channel API.
• Customer service desk integrations.
• Supports up to 100 concurrent call capacity for its plus plan and up to 1,000 for its enterprise plan.
• Deploy on any cloud, including IBM, Amazon, Google, Microsoft, or on-premises environments.

Pros

• Natural Language Processing (NLP) capability.
• Multi-language support.
• Language, acoustic and voice customization options.

Cons

• Limited duration for its analytics data retention capability.
• Onboard support is only available to enterprise users.

Also see: Best Artificial Intelligence Software 2023

Kore.ai Experience Optimization (XO) Platform: Best for automation

Kore.ai Experience Optimization (XO) Platform is designed to help businesses build, train, and deploy intelligent chatbots and virtual assistants that can understand and respond to customer queries in a natural, conversational manner.

Aside from the XO platform, the company also offers various solutions such as SmartAssist, an AI-native CCaaS solution; AgentAssist, which are virtual assistants supporting agents in real time; and BankAssist, which is an AI-native, omnichannel, conversational banking assistant pre-trained on 400+ retail banking use cases.

Pricing

• Standard: 20 cents per conversation. This plan also includes 10 cents per conversation for pre-built apps and 4 cents per minute for voice automation.
• Enterprise: Custom quotes.

Korea.ai offers optional enhanced support at an additional cost – $2,000 per month for the standard plan and a custom quote for the enterprise plan.

Features

• Support over 100 languages, including English, Arabic, Japanese, French, and Malay.
• Auto-dialog generation.
• On-premise, cloud and hybrid deployment options.
• Conversational IVR (Interactive Voice Response) capability.

Pros

• Integrates with over 75 prebuilt workflows, including CRM, ERP, ITSM, and NLM tools.
• Compliant with industry regulations like SOC2 Type2, HIPAA, GDPR and PCI.
• Easy to use.

Cons

• Advanced support costs extra.
• The documentation can be improved.

Avaamo.ai: Best for conversational analytics

Powered by neural networks, speech synthesis, and deep learning, Avaamo is a conversational artificial intelligence platform that provides businesses with intelligent virtual assistants and chatbots. Avaamo offers fabricated skillsets to help enterprises automate complex business use cases through multi-turn conversations.

Avaamo offers a skills builder that includes a flow designer for designing conversation, dynamic dialog, conversational IVR, and other tools that enable you to automate complex enterprise use cases.

Pricing

Avaamo doesn’t advertise pricing on its website; the company encourages users to request a demo to learn about the platform and get custom quotes based on their needs.

Features

• It supports integration using APIs, Web Services, ESBs, MQs, and Custom Adapters, including over 150 pre-built integrations.
• Branded AI voice capability.
• Conversational analytic tools.
• Compliance with industry regulations such as SOC3, SOC2(Type Ⅱ), CCPA, HIPAA and more.
• IVR channel integration.

Pros

• Supports over 114 languages.
• Flexible deployments – on-premise and cloud deployment.
• It supports over 70 channels across various chats and voice mediums.

Cons

• Some users reported that Avaamo is somewhat expensive.

Amazon Lex: Best for affordability

Amazon Lex is a chatbot-building technology by AWS, so it benefits from the cloud giant’s extensive platform. It’s a service that can help you build conversational interfaces using voice and text. Amazon Lex uses Automatic Speech Recognition (ASR) to convert spoken language into text and Text-to-Speech (TTS) to convert text into spoken language. The platform has various components that work together to enable users to build intelligent conversational AI solutions for their businesses. They include:

• Intent: It represents the desired action.
• Utterance: Phrases or sentences that users input to interact with the chatbot.
• Prompt: Request data.
• Slot: Required data.
• Fulfillment: Amazon Lex can trigger backend business logic to fulfill user requests.

Pricing

Amazon Lex only charges you for what you use. You can also try the tool for free. You can process up to 10,000 text requests and 5,000 speech requests or speech intervals per month at no cost for the first year of trying the tool.

Request and response interaction pricing

• $0.004 per speech request.
• $0.00075 per text request.

Streaming conversation pricing

• $0.0065 per unit per speech interval.
• $0.0020 per unit per text request.

Automated chatbot designer pricing

• $0.50 charges per minute

You can use the AWS pricing calculator to calculate your monthly expense or contact an AWS specialist for pricing assistance to get an estimate.

Features

• Natural conversation capability includes speech recognition and natural language understanding, context management, 8 kHz telephony audio support and multi-turn dialog.
• Builder productivity capability that allows you to build visual conversations, streamline conversations and deploy to multiple platforms.
• Integration with AWS services like Amazon Kendra, Amazon Polly and AWS Lambda.
• Contact center integrations with Amazon Connect, Genesys Cloud CX, Amazon Chime SDK and AWS Contact Center Intelligence (CCI).

Pros

• Offers use cases for financial services, insurance, retail, telecom, and travel.
• Easy to train and configure chatbots.
• Positive reviews from current and past users.
• Users find the solution highly affordable.
• Natural language understanding.

Cons

• Documentation can be improved.
• Some users say the confidence score isn’t always accurate.

Also see: Top Generative AI Apps and Tools

Oracle Digital Assistant: Best for performing operational tasks

With the Oracle Conversational AI platform, you can build chatbots that can engage in natural language conversations, understand user intents, and provide relevant responses and actions. The platform lets you connect with a chatbot through channels like Microsoft Teams or Facebook on your website or embedded inside your mobile app.

Pricing

Oracle Digital Assistant platform pricing is available per request and as a subscription for SaaS customers by employee, named users, or sessions.

• Oracle Digital Assistant Cloud Service: $0.0232 unit price per request. This plan requires a minimum of 250 requests per hour.
• Oracle Digital Assistant Platform for Oracle SaaS – Hosted Employees: $3 per month.
• Oracle Digital Assistant Platform for Oracle SaaS – Hosted Named User: $6 per month.
• Oracle Digital Assistant Platform for SaaS – 1,000 Sessions: $275 per month.

Features

• NLU’s capability to understand conversations to derive intent and context.
• AI-powered voice.
• Prebuilt chatbots for Oracle Cloud applications such as Oracle Cloud ERP, Oracle Cloud SCM, Oracle Cloud HCM, and Oracle Cloud CX.

Pros

• Multilingual support.
• Multi-channel support: web, mobile, SMS texting, smart speakers, Slack, and Microsoft Teams.
• Users applaud its seamless integration with messaging apps.

Cons

• Limited language support.
• Voice recognition can be improved.

Microsoft Bot Framework: Best for developers

Supporting both code-first and no-code approaches, Microsoft Bot Framework provides a platform for creating conversational agents capable of interacting with users via channels such as online sites, Slack, and Facebook. The framework comprises various components:

• A language component that enables you to build natural language experiences.
• Speech component that can reply to customers in a natural language with a branded voice, hear commands, translate, and identify individual speakers.
• QnA Maker, which is a question-and-answer bot.
• Vision components that leverage the capabilities of computer vision services to recognize faces, moderate content, and index images and video.
• Search functionality allows you to search across defined domains or the web.

Pricing

• Standard channels: Free for unlimited messages.
• Premium channels: Free for up to 10,000 monthly messages or $0.50 per 1,000 for the S1 tier.

Features

• It can integrate into existing ecosystems such as Slack, Cortana, Skype, Telegram, Messenger, and SMS.
• Native integration with Azure cognitive services.
• Bot Builder SDK.

Pros

• Offers open source SDK and tools to connect your bot to popular channels and devices.
• Supports integration with Microsoft Azure Language Understanding (LUIS) for entity recognition and intent understanding.
• Rich development ecosystem.

Cons

• Limited customization options.
• Steep learning curve for beginners.

Also see: Generative AI Companies: Top 12 Leaders 

Cognigy.AI: Best for contact center automation

Enhanced with generative AI, Cognigy’s low code Conversational AI platform enables enterprises to automate contact centers for customer and employee communications. The platform offers customer service solutions like Conversational IVR, Smart Self-Service, and Agent + Assist. With Cognigy, users can design conversational flows, integrate with backend systems, and customize the behavior of their chatbots or virtual assistants to suit their specific business needs.

Pricing

The platform doesn’t advertise its pricing on its website. To get quotes, businesses are required to contact the company for a demo to discuss their needs. Publicly available information revealed the platform costs as follows.

• Basic 5K pm: Platform & Setup fee, 60K conversations pa, Standard Support costs $43,080 for 12 months.
• Basic 5K pm + VG: Platform & Setup fee, 60K conversations pa, 5 VGs, Standard Support costs $53,916 for 12 months.

Features

• Generative AI capability.
• AI-based voice gateway services.
• Omni-Channel Support – deployment across various channels, including websites, messaging apps, and voice assistants.
• Integrates with messaging apps like Teams, Slack, andWhatsApp; CCaaS and CPaaS such as Avaya, 8X8, NICE, and GENESYS; enterprise tools like Salesforce, ServiceNow, SAP, Zendesk, and Microsoft Dynamic 365.

Pros

• Reporting and analytics capabilities.
• Real time insight into your operations.

Cons

• Some users reported difficulty with building custom extensions.
• Limited documentation.

Yellow.ai: Best for customization

Our analysis found that Yellow.ai is a battle-tested conversational AI platform used by over 1,000 enterprises across 70 countries. Yellow.ai dynamic automation platform is designed to automate customer and employee interaction and conversations across text, email, and voice. The platform is fluent in over 135 languages and supports over 35 channels.

Pricing

Yellow.ai AI chatbot pricing are as follows:

• Free: Available at no cost for 100 MTU per month and limited to two agents.
• Enterprise: Usage-based pricing. Quotes are available upon request.

Publicly available information on the AWS marketplace reveals that the Yellow.ai Basic Plan, which includes a basic chatbot with one use case and tiered conversation limits, costs $10,000 for 12 months, while the Standard Plan, which includes a Standard chatbot with four use cases and tiered conversation limits, costs $25,000 for 12 months.

Features

• No code builder.
• Integrates with 100+ third-party services, including Zendesk, Freshdesk, Jira, ServiceNow, HubSpot, and Jira.
• Supports up to 135 languages.
• Text automation capability.
• Supports 35+ channels, including Slack, Messenger, Instagram, and WhatsApp.
• Pros
• Natural language understanding capability.
• Highly customizable.
• Drag and drop studio for building bots.

Cons

• Advanced features may be complex to implement.
• Some users reported that the integration of Yellow.ai with other tools is somewhat complex.

Acquire.io: Best for ease of use and simplicity

Featuring live chat, video and voice calling, AI chatbots, co-browsing and centralized interaction management, Acquire conversational AI platform empowers users to help customers resolve complex issues in real time. The platform aims to improve customer satisfaction, increase conversions, and enhance customer support efficiency.

Pricing

• Self service: This plan costs $500 per month billed annually plus $25 per agent per month.
• Integration solution: This plan costs $2,000 per month billed annually plus  $45 per agent per month.

Features

• One-way and two-way video capability.
• Live chat messaging.
• Translate conversations into 25+ languages.
• Dynamic prioritization and intelligent routing.

Pros

• Voice and video call options.
• Call deflection capability.
• Allows users to manage multiple chats simultaneously.

Cons

• Some users reported that the notification capability doesn’t function well, causing them to miss live chats.
• It may be somewhat expensive for small businesses.

Clinc: Best for financial service companies

Clinc’s AI platform is designed to provide personalized and natural language-based experiences for applications like virtual assistants, chatbots, and voice-controlled devices. The company has been particularly involved in developing  AI systems for the financial and banking sectors, where their technology is used to create virtual banking assistants that allow customers to check balances, report lost or stolen cards, transfer funds, and gain deep insights into their spending habits.

Pricing

Pricing is available upon request.

Features

• Flexible deployment – cloud or on-premise.
• IVR capability.
• Advanced Natural Language Processing.
• Omni-channel support – Alexa, web messenger and mobile apps.

Pros

• Voice and text support.
• Multi-lingual support.
• Context retention capability.

Cons

• Initial setup complexity.
• Documentation can be improved.

Key Features of Conversational AI Platforms

Natural Language Processing

The computer’s ability to understand human spoken or written language is known as natural language processing. NLP combines computational linguistics, machine learning, and deep learning models to process human language. This feature enables the conversational AI system to comprehend and interpret the nuances of human language, including context, intent, entities, and sentiment.

Omini-channel experience

The best conversational AI platform allows you to engage with your customers across multiple channels and touchpoints such as websites, mobile apps, messaging platforms (like Facebook Messenger, Instagram or WhatsApp), voice assistants (such as Amazon Alexa or Google Assistant), and more. The tools we analyzed in this guide allow you to engage with your customers across various channels.

Sentiment Analysis

The best conversational AI tools are trained to analyze digital text to deduce the emotional tone of the message – which could be positive, negative, or neutral. This capability allows chatbots to respond to customers in a more personalized way or empathetic manner.

Integration with third-party services

Integration capability is an important feature of any modern-day digital solution, especially for conversational AI platforms. Seamless integration with third-party services like CRM systems, messaging platforms, payment gateways, or ticketing systems allows businesses to provide personalized experiences.

Analytics and insights

Conversational AI platforms often provide analytics and insights into user interactions. This data can help businesses understand user behavior, identify common queries, and improve the effectiveness of the AI system.

How to Choose the Best Conversational AI Software for Your Business

While there are hundreds of conversational AI platforms marketed as the best system, each tool has its strengths and areas of weaknesses. What seems to be a strength for company A may be a weakness for company B and vice versa. Choosing the right conversational AI software for your business can significantly impact customer interactions, operational efficiency, and overall success. So, how do you select the best conversational AI platform for your business?

• Identify your conversational AI needs – the current gap in your existing system, and also define your expectations.
• Research various platforms and narrow your list to the best three that stand out.
• Evaluate these tools’ features and compare them to your requirements list.
• Select the platform with features that align with your needs.
• Consider the affordability of the tool, ease of use/usability and scalability.
• Research the vendor reputation – a well known, established vendor is more likely to provide reliable software and support. Then again, there are eager start-ups that provide a lot of value for the money.

Keep in mind that the best conversational AI software for your business will depend on your unique needs, goals, and the preferences of your customers.

How We Evaluated the Best Conversational AI Platforms

The best conversational AI platform is easy to use, offers features that meet the intended users’ needs, balances quality service and affordability, and allows businesses to integrate with tools and services they already use.

Core features – 30%

We evaluated each platform’s core offerings and their ability to serve the needs of businesses in various industries. Our analysis considered features like NLU, multi-channel support, flexible deployment, multi-lingual and other essential features.

Cost – 25%

We researched each conversational AI platform pricing strategy and model. We also checked for pricing transparency and the availability of free demos and trials to allow potential buyers to test out the platform before making a purchase decision.

Integration – 15%

We checked whether the conversational AI platform integrates with third party services such as CRM, ITSM, and various communication channels such as websites, messaging apps, voice assistants, and social media platforms.

Ease of use – 15%

We reviewed each platform’s usability to determine if it’s beginner-friendly. A user-friendly dashboard makes it easier for non-technical team members to manage the AI. So we checked if the platform has an intuitive interface for setting up and managing conversational flows.

Customer support – 15%

To score each conversational AI platform for this category, we analyzed user feedback on review sites and considered the types of support offered by each company.

Frequently Asked Questions (FAQs)

What features should I look for when evaluating conversational AI platforms?

Consider the following features when shopping for a conversational AI platform:

• Natural Language Understanding (NLU)
• Multi-turn dialog management
• Intent recognition
• Entity recognition
• Integration with existing systems
• Analytics and reporting
• Multi-channel support
• Language support
• Testing and debugging tools

What are conversational AI platforms and how do they work?

Conversational AI platforms are software solutions that leverage the innovations of AI, deep learning, and NLP technologies to enable automated, human-like interactions between computers and users through natural language.

These platforms facilitate seamless communication across various channels, such as chatbots, voice assistants, messaging apps, websites, and more. They are designed to understand user inputs, interpret their intentions, and provide relevant and contextual responses.

Which industries can benefit from adopting conversational AI platforms?

The potential applications of conversational AI are vast. Any industry that involves customer interactions, information dissemination, and process automation can benefit from leveraging conversational AI platforms.

Bottom Line: Conversational AI Platforms

As businesses seek to enhance their customer interactions and improve overall efficiency, conversational AI platforms offer organizations the opportunity to forge stronger connections with their audience, provide instant assistance, and gather valuable insights from user interactions. From understanding user intent to generating coherent responses, conversational AI platforms help business create lifelike conversations that meet customer needs efficiently.

Read Next: Top Natural Language Processing Companies

The post Top 10 Conversational AI Platforms 2023 appeared first on eWEEK.

As the demand for RPA continues to soar, numerous RPA companies have entered the market, offering their unique blend of AI and software robotics expertise and solutions. With their innovative approaches and proven track records, these companies have set the bar high for RPA excellence.

Below we review the best 10 RPA companies transforming various industries and reshaping the future of work.

Jump to:

• • Best RPA Companies: Comparison chart
  • Top 10 Robotic Process Automation Companies in 2023
  • How to choose the best RPA company for your business
  • Review methodology
  • Bottom Line: RPA Companies

Best RPA Companies: Comparison Chart

Here is a head-to-head comparison of the best RPA companies:

Top 10 Robotic Process Automation Companies in 2023

UiPath: Best RPA company for advanced features

UiPath is a leading enterprise automation software company founded in Bucharest, Romania, and headquartered in New York City. The company offers both SaaS and self-hosted robots, allowing organizations to easily automate their business processes.

UiPath can help you automate processes with drag-and-drop AI and pre-built templates. Additionally, Uipath offers pluggable integration with Active Directory, OAuth, CyberArk, and Azure Key vault and also complies with regulatory standards such as SOC 2 Type 2, ISO 9001, ISO/IEC 27001, and Veracode Verified.

UiPath pricing

UiPath offers four pricing plans – one free plan and two paid plans. You can also try the UiPath RPA tool for 60 days before buying, giving you time to better understand the platform features and functionalities before purchasing.

• Free: Available at no cost with limited features.
• Pro: This plan starts at $420 per month. It is ideal for small teams and businesses getting starter with automation. This plan is available on the cloud only.
• Enterprise: Quote is available upon request. Companies looking for comprehensive RPA platform capabilities will find this UiPath plan suitable.

UiPath key features

• Multi-tenancy.
• Offers various robots to help with users’ data and applications, including automation cloud robots, unattended robots, attended robots and test robots.
• Extensive integration options, including Tableau, ServiceNow, SAP, Salesforce, Oracle, AWS, Microsoft, Alteryx and more.
• UiPath Business Automation includes various RPA solutions like Automation Hub, Task Capture, Process Mining, and Task Mining.

UiPath pros

• Feature-rich RPA tool.
• Users reported that they find the user interface visually appealing.
• The company provides low-code development tools.
• Their solution is deployable as SaaS or self-hosted – depending on your needs.

UiPath cons

• The steep learning curve for RPA beginners and those with limited experience.
• Support can be improved for non-enterprise plan subscribers.

Also see: Best Artificial Intelligence Software 2023

Automation Anywhere: Best for large enterprises with complex automation needs

Automation Anywhere is clearly a RPA market leader. The company focuses primarily on enterprise automation and serves users in various industries, including BPO, financial services, healthcare, insurance, life sciences, manufacturing, public sector and telecom. Automation Anywhere digital workspace is built to serve the needs of business users, citizen developers, and professional programmers, allowing them to create a bot or design business process automation workflows. It includes:

• Control room
• Bot runner
• Bot editor
• Bot creator
• Credential vault

Automation Anywhere offers a range of Robotic Process Automation products, including IQ Bot, and Bot Insight, and a “Bot Store” – an online marketplace for ready-to-use bots and digital workers running on the Automation 360 platform.

Automation Anywhere pricing

Automation Anywhere encourages businesses to book a demo to discuss their needs before a quote is sent to you. The company offers three plans for its SaaS packages.

• Community Edition: A free version of the complete digital workforce platform, which includes RPA, AI and analytics.
• Cloud Starter Pack: Starts at $750 per month and includes one bot creator, control room and unattended bot runner. Additional unattended and attended bot runners can be added for $500 per month per user and $125 per month for each user, respectively.
• Advanced Pack: Custom quote.

While these Automation Anywhere product prices may change based on a discussion with a sales rep, the list above should give you an idea of how their solution is priced. You should contact the company sales team to discuss your needs and get quotes.

Automation Anywhere key features

• Document automation capability.
• Automation of complex tasks.
• Code optional capability, including no code, low-code, and bring-your-own-code automation.
• Connects with numerous third-party solutions, including AWS, Google AutoML, Salesforce and more.
• Allow users to manage, schedule, and execute bots.

Automation Anywhere pros

• They offer highly scalable automation solutions.
• Responsive customer support team.
• Some users reported that the company’s product allows them to adjust the level of automation to meet their business-changing demands.

Automation Anywhere cons

• Complex automation requires technical expertise.
• Complex initial setup process.

EdgeVerve AssistEdge RPA: Best for enterprises with a focus on consumer customer service

EdgeVerve is an Infosys Company (subsidiary) with a focus on automation. EdgeVerve AssistEdge RPA is largely favored by customers in finance, with many customer interaction activities like call centers.

Aside from AssistEdge, EdgeVerve offers other automation tools, including XtractEdge, a document AI platform that provides insight from documents like SOPs, legal contracts, images, commercial insurance papers, images, handwritten notes, PDFs, and emails; and TradeEdge, which is ideal for supply chain order management.

EdgeVerve ​​AssistEdge RPA pricing

The company doesn’t publicize its product pricing on its website. Potential buyers must request a demo to speak with an EdgeVerve expert about their needs before receiving personalized quotes tailored to them. Our research found that the company offers a pay-as-you-go pricing model.

EdgeVerve AssistEdge RPA key features

• Automation process discovery.
• Users can scale the AssistEdge RPA BOTs and Infrastructure up and down based on their business needs.
• Automatic bot upscaling, downscaling, and management.
• You can monitor your bot’s health via their centralized management dashboard.

EdgeVerve AssistEdge RPA pros

• Improve business process agility.
• Easy to deploy bots in both attended and Unattended Automation.
• It has OCR capability.

EdgeVerve AssistEdge RPA cons

• Some users reported that the AssistEdge profile mapping process is complex.
• Difficult to integrate with third-party tools.

On a related topic: What is Generative AI?

SS&C Blue Prism: Best RPA for unattended use cases

SS&C Blue Prism intelligent automation platform (IAP) combines the capabilities of RPA, artificial intelligence, and business process management (BPM) to help automate business processes and streamline decision-making across organizations.

The company’s digital worker — a software robot powered by RPA technology  – can be integrated into your existing systems to help you execute business processes and drive results. SS&C Blue Prism was ranked as one of the RPA leaders by Forester Wave in Q1 2023. The company offers support from automation specialists, prebuilt automation, and training and certification.

SS&C Blue Prism pricing

The company doesn’t advertise its product pricing on its website – they encourage buyers to contact an in-house expert for quotes. However, publicly available pricing information on the AWS marketplace reveals the following rates for SS&C Blue Prism Intelligent Automation.

• 5 BPC Digital Workers with production support plus knowledge support: It costs $131,800 for 12 months.
• 5 BPC Digital Workers with production support without knowledge support:  It costs $115,600 for 12 months.
• 5 BPC Digital Workers with production support  – License Only: It costs $74,750 for 12 months.

SS&C Blue Prism key features

• Allow both centralized and federated automation setups.
• Automation building capability.
• Bot management and execution.
• OCR capabilities.
• UX Builder helps businesses reduce app development time.

SS&C Blue Prism pros

• Easy to learn and use.
• Users applaud Blue Prism’s security and data encryption capabilities.
• Blue Prism product includes capabilities for Optical Character Recognition (OCR), Intelligent Document Processing (IDP), and Natural Language Processing (NLP).

SS&C Blue Prism cons

• Initial setup can take a while to achieve.
• While it is easy for technical users to use, business users may experience a steep learning curve.

WorkFusion: Best for banking and financial services organizations

WorkFusion is a no-code/low-code intelligent automation provider offering “AI Digital Workers,”  which combines AI, ML, IDP and RPA technologies to help organizations manage jobs. The company’s tool is built for banking and financial services organizations to help with functions like anti-money laundering (AML), sanctions screening, and Know Your Customer (KYC).

You can also leverage WorkFusion AI digital workers for various jobs like data analytics, customer service, human resources, accounting and logistics.

WorkFusion pricing

WorkFusion doesn’t advertise rates on their page. You can request a demo to discuss your needs and get custom quotes afterward.

WorkFusion key features

• It incorporates AutoML capabilities and RPA components for financial use cases.
• They offer pre-trained bots for the primary processes like LIBOR transition, account opening and KYC, claims processing and more.
• Document intelligence capabilities.
• It has an automation studio, a cloud and desktop development tool for business users and automation professionals.

WorkFusion pros

• Fast learning curve.
• Automates document-heavy processes with document intelligence.

WorkFusion cons

• Some users reported that WorkFusion products are expensive.
• WorkFusion OCR technology can be improved.

Also see: The Benefits of Generative AI 

NICE RPA: Best for contact center operations

Large enterprises in the customer service segment will find the automation capability of NICE RPA valuable. NICE RPA provides real-time visibility through their web-based centralized task automation bot management. The company robots are deployed on enterprise backend servers and have the potential to automate mundane, administratively-driven manual tasks that employees perform regularly.

NICE RPA pricing

Nice RPA doesn’t advertise its rates on its website. You can contact them for quotes.

NICE RPA key features

• It has a built-in drag-and-drop design studio, allowing users to create visual workflow views.
• Integrates with numerous third-party services.
• Allow you to create attended and unattended automation.
• Native ability to develop robots using voice commands.

Nice RPA pros

• Easy to use.
• Pre-built templates.
• Custom automation capabilities.

Nice RPA cons

• Niche centered: it may not be suitable for every use case.
• Limited community support.

ServiceNow: Best RPA for customization

ServiceNow is popular for an array of service and IT operations management tasks. The company also offers low-code workflow automation solutions that enable users to create applications with limited coding knowledge to help with their business processes.

With ServiceNow App Engine, you can create custom applications to meet your specific business requirements – you can also leverage pre-built application templates and components to accelerate the development process.

ServiceNow pricing

Quotes for this company’s tools are available upon request.

ServiceNow key features

• It has a centralized bot management hub.
• Desktop design studio.
• They offer 1,300+ tools, including connectors, templates, and optical character recognition (OCR), allowing companies to select the components they want to use.
• It has attended and unattended automation options.

ServiceNow pros

• Low learning curve.
• Users speak highly of its user interface.
• Low code option makes it suitable for business users.

ServiceNow cons

• The UI Builder can present a steep learning curve.
• Some users say the tool is pricey.

AutomationEdge: Best RPA for data processing

AutomationEdge Hyperautomation Platform offers tools to help you define and deploy software robots that can mimic human actions and perform repetitive tasks, which reduces human error. This helps to streamline business processes, manage data, and integrate systems. AutomationEdge can integrate with various data sources, databases, and applications, enabling seamless data flow and synchronization.

AutomationEdge pricing

The company offers a free plan and two paid plans. Although AutomationEdge doesn’t advertise their rates on their website, they charge clients based on usage.

• Starter: Free for 30 minutes per month for a lifetime.
• Professional: Quotes available upon request. License type: Consumption.
• Enterprise: Quotes available upon request. License type: Subscription/ Consumption.

AutomationEdge key features

• Integration with third-party services, over 400 tools.
• Conversational AI and chatbot.
• Intelligent document processing capability.

AutomationEdge pros

• Consumption based pricing model option.
• Users speak highly of the company’s support team.
• On-premise and cloud deployment options.

AutomationEdge cons

• The solution can get overwhelming for newbies.
• Knowledge base can be improved to help with the learning curve.

Also see: Top Digital Transformation Companies

Pega platform: Best for large enterprises with complex business processes

Pega Platform, also known as Pega Systems, is a low-code, model-driven application development platform that enables companies to build and deploy automated applications. Pega Platform supports business process management (BPM), customer relationship management (CRM), case management, and other types of applications. It is used by businesses across various industries to improve customer engagement, streamline operations, and drive digital transformation.

Pega platform pricing

Custom pricing, contact the company for quotes. Pricing information found on the AWS marketplace reveals the price of Pega cloud services at $990,000 for 12 months, $1,980,000 for 24 months and $2,970,000 for 36 months. For your actual rates, contact the company for pricing.

Pega platform key features

• Attended and unattended automation options.
• Integrates with services like Salesforce, DocuSign, Avaya, SAP, Cisco and more.
• Support the use of NLP to automate email.
• Process management.
• Process modeling and designing.

Pega platform pros

• Business process control.
• Reporting and analytics.
• It allows you to use AI for self-healing automation.

Pega platform cons

• Support can be improved.

MuleSoft RPA: Best for organizations with many routine processes

MuleSoft is a company that provides a platform for building and integrating applications, data, and devices. They offer application and data integration products, API management, and robotic process automation – enabling no-code and pro-code teams to build automation across enterprise systems.

MuleSoft Anypoint Platform allows businesses to connect applications, data, and devices across on-premises and cloud environments. It provides a range of tools and services to build, deploy, manage, and monitor APIs and integrations.

MuleSoft RPA pricing

Mulesoft automation pricing starts at $57,000 per year. They offer different pricing models, including pay-per-use, which charges you for RPA Bot Minutes, the number of API calls made by RPA automation, and the number of Composer Tasks. You can also select the credits for RPA and Composer model. The company requires interested buyers to contact them for quotes.

MuleSoft RPA key features

• It has RPA Manager that manages user access and permissions.
• Extract data from documents, web pages, emails, spreadsheets, and more.
• Automate data entry and data retrieval in legacy and modern applications.
• Mulesoft offers various RPA components to help with your business processes; they include MuleSoft RPA Manager, MuleSoft RPA Builder, MuleSoft RPA Recorder, and MuleSoft RPA Bots.

MuleSoft RPA pros

• Comprehensive documentation.
• Multi-language support.
• Integrates with CRM and ERP tools.

MuleSoft RPA cons

• Some users reported that Mulesoft RPA is costly.
• Needs more integration.

For more information, also see: Top Robotics Startups

How to Choose the Best RPA Company for Your Business

While the hundreds of RPA tools in the market all claim they are the best for you and your organization, you need to understand that the best RPA is relative, not absolute. Meaning what works for company A might not serve the needs of company B. What are the specific workflow automation needs of your company?

With your goals specified, here are the steps to take to select the best RPA company for your business.

• Conduct extensive research about the best RPA companies.
• To assist with that research, create a list of the top RPA features you need. This list below can be a starting point for your research:
  • Process orchestration
  • Analytics and monitoring
  • Exception handling
  • Low-code or no-code development
  • User interface interaction
  • Scalability
  • Cognitive automation
  • Audit trails and compliance
  • Customizability
  • Integration capability
  • Community and support
• Identify the top three companies that stand out for you.
• Request for a demo of your desired tool from these companies and also try a free trial if available to help you get a better understanding of the platform before you invest.
• Don’t forget to consider cost – choose a tool within your budget; RPA tools won’t be getting cheaper in the future.

Review Methodology

We reviewed more than 50 RPA companies using 15+ individual data points across five key categories: Cost, features set, ease of use, the versatility of audience service and support. We gathered products and services info, features, pricing, and other relevant information from each RPA company’s websites, whitepapers and documentation – we then used the data to score the best RPA companies as follows:

• Cost (20%)
• Features set (30%)
• Ease of use (25%)
• Versatility of audience service (10%)
• Support (15%)

We considered several individual data points that carry the most weight in each ranking criteria category when choosing the best RPA company. After careful consideration, calculation and extensive research, our top picks were determined with enterprise use in mind.

Bottom Line: Best RPA Companies 2023

As automation continues to gain traction, organizations need to identify the best RPA company for their specific needs.

Ultimately, choosing the best RPA company for your business will depend on your unique requirements, budget, and long-term automation goals. It is crucial to thoroughly evaluate each company’s offerings, customer reviews, and track record before making a decision.

Ultimately, companies should realize that while RPA can be a costly investment, it’s an investment that should pay itself back. The returns are numerous, but chiefly reside in RPA’s capacity to dramatically streamline workflow and improve staff productivity.

On a related topic: The Future of Artificial Intelligence

The post Top Robotic Process Automation Companies appeared first on eWEEK.

Consequently, there is a great need for AI detector tools. AI content detector software uses artificial intelligence (AI) to identify text written with a generative AI model. The software aims to provide readers with transparency and ensure that only quality content is published.

We analyzed the best AI ​​detector software, including their unique features, costs, pros and cons to help you determine the best option for your organization’s needs.

On a related topic: What is Generative AI?

Also see: ChatGPT: Understanding the ChatGPT ChatBot

Jump to:

• Top AI Detectors: Comparison Chart
• Originality AI: Best Overall AI Detector
• Content at Scale AI Detector: Best Free AI Detector
  
• Winston AI: Best for Content Writers
• GPTZero: Best for Educators
• GLTR: Best for GPT2 Model-Generated Content
• Writer AI Content Detector: Best for Integration
• Copyleaks: Best for Content Marketing Agencies
• Sapling.ai: Best for Agencies and Customer-Facing Teams
• Hugging Face: Best for Technical Teams
• Crossplag AI Content Detector: Best for Institutions
• Honorary Mentions: AI Detectors
• Key Features of AI Detector Software
• How to Choose the Best AI Detector for Your Needs
• FAQs about AI Detector Tools
• AI Detectors: Review Methodology
• Bottom Line: AI Detector Software

Top AI Detectors: Comparison Chart

Also see: Generative AI Companies: Top 12 Leaders

10 Best AI Detector Software

Originality AI: Best Overall AI detector

Originality AI is one of the best AI detector tools in the market. It can be used to scan text for AI and plagiarism. It requires 50-word counts and above. It boasts 94%+ accuracy on the text generated with GPT-3, GPT-3.5, and ChatGPT, 99%+ accuracy on GPT-4 content and 94.5% accuracy on paraphrased content. Scanning content with this tool returns the AI percent score and the original percent or human score.

Cheat code to save on credit: You can reduce Originality AI credit usage by selecting only one action at a time. See Figure A below.

With Originality AI, managers or owners can manage teams by assigning roles to team members, making it ideal for organizations with distributed editorial teams. Compared to other tools, originality AI uses great computing power to scan text when running its detection model.

Pricing

Originality AI charges based on the number of credits you purchase. It costs $0.01 to scan 100 words.

• 2,000 credits: $20
• 5,000 credits: $50
• 10,000 credits: $100
• 25,000 credits: $250
• 50,000 credits: $500
• 100,000 credits: $1,000

Originality AI’s Standout Features

• Team management capability.
• It can predict AI writer text from tools like ChatGPT, GPT-4, GPT-3, GPT-2, GPT-NEO, GPT-J or Quillbot.
• Offers Chrome extension that enables users to scan text in Google documents.
• The tool can be used to scan email text, Google doc, WordPress content and website content.

Pros

• Responsive customer support team.
• High accuracy score.
• 83% accurate on ChatGPT.
• Built-in plagiarism checker.
• Chrome extension.
• Hard to fool.

Cons

• False positives.
• Doesn’t offer a free trial.
• Sometimes highlight human text as AI.
• Only supports English.

Also see: 100+ Top AI Companies 2023

Content at Scale AI Detector: Best Free AI Detector

Content at Scale is a free AI detector tool designed for content marketers and academics. The tool can check for AI content generated with ChatGPT, GPT-3 and other AI models. Its content score is based on the text’s predictability, probability and pattern. Content at Scale is also in the generative AI business, the tool can be used to create long-form content with over 2,000 words.

Content at Scale’s sentence-by-sentence breakdown helps users identify sentences written with the AI tool by highlighting its AI detectability using various colors.

Pricing

Content at Scale AI detector tool is free to use.

Content at Scale AI Detector’s standout features

• Detects GPT-2, GPT-3, 3.5, and ChatGPT.
• It can be used to scan various types of text, including SEO, educational, marketing and academic content.
• API is available on request.
• It can scan up to 25,000 character text.
• Multiple language support.

Pros

• Easy to use.
• Highlights AI text.
• Scan starts from 25 words.
• Offers additional content optimization services.

Cons

• False negatives – it sometimes highlights human written text as AI generated when the content is long form.
• The tool detection capability can be improved.

Winston AI: Best for content writers

Winston AI is an AI detector tool built for writers, educators and web publishers. It can detect content generated with generative AI tools like Bard, ChatGPT, GPT-4, and other Large Language Models (LLM). Wiston AI support Optical character recognition (OCR) technology which allows users to scan image files for AI content.

The tool is straightforward to use, it allow you to scan for AI content in few steps.

• Paste the text you want to scan into the text area
• Toggle the plagiarism button ON or OFF depending on your need
• Click on scan text at the buttom right of the page.

You will receive a prompt to view your results in few seconds.

Pricing

Winston AI offers a free plan and two paid plans, payable monthly or annually.

• Free: Available at no cost for up to 2,000 words scan or for one week.
• Essential: It cost $12 per month when billed annually or $18 per month when billed monthly. It allow you to scan up to 80,000 words per month.
• Advanced: It cost $19 per month when billed annually or $29 per month when billed monthly. It allow you to scan up to 200,000 words per month.

The also give users the option to request for a custom plan. You can contact Wiston AI sales team to request for quotes.

Wiston AI standout features

• Its OCR capability enable it to scan pictures and handwriting.
• Plagiarism detection capability.
• Enables users to generate shareable PDF reports.

Pros

• It shows human, plagiarism and readability score.
• Supports multiple file documents including .docx, .png and .jpg.
• Multi language support: English and French.

Cons

• The free plan is limited to 2000 words scan.
• Requires sign-up to use.

Also see: ChatGPT vs. Google Bard: Generative AI Comparison 

GPTZero: Best for Educators

GPTZero is a classification model developed by Princeton University student Edward Tian to help educators predict and detect AI written text. It analyzes texts based on their perplexity – a measurement of the randomness of a text – and burstiness, which measures the predictability of content based on patterns. According to the developer, the tool was trained on a large and diverse human-written and AI-generated text, with a focus on English prose. Those looking to integrate GPTZero into their system can request the API, but it comes with a fee.

Pricing

GPTZero offers a free plan and three paid plans.

• GPTZero Classic: No charge for up to 5,000 character limit per document and three files limit per batch upload.
• GPTZero Educator: $9.99 per month for up to 50K character limit per document, unlimited batch file uploads per run and up to 1 million words per month.
• GPTZero Pro: $19.99 per month for up to 50K character limit per document, unlimited batch file uploads per run and up to 2 million words per month.
• Enterprise/business API plan: Contact for quotes.

GPTZero’s Standout Features

• Batch file upload.
• Detects ChatGPT, GPT-3, GPT-2, and LLaMA.
• Perplexity score to show the randomness of text.
• Burstiness score to determine the uniformity or pattern of text.
• Requires a minimum of 250 characters

Pros

• Highlight AI text.
• Free plan option.
• Accepted file types include pdf, docx, and txt.

Cons

• False negatives, though infrequently.
• Presentation of scores can be confusing.

GLTR: Best for GPT2 Model-Generated Content

GLTR, or Giant Language model Test Room is a project jointly developed by the MIT-IBM Watson AI lab and Harvard Natural Language Processing group. The tool analyzes each word in a sentence or document and predicts the likelihood of it being generated by a GPT-2 model or AI services built on the model. While this tool efficiently detects GPT-2 text, it may not be suitable for analyzing text from recent models like ChatGPT or GPT-4. GLTR integrates with the 117M language model from OpenAI, making it easy to detect AI text produced by GPT-2 117M.

Pricing

GLTR is free to use.

GLTR’s standout features

• Breakdown different language patterns used in a text via histogram.
• Provides forensic analysis of a language model’s text input.

Pros

• High accuracy for GPT 2 generated text.
• Visual feedback.

Cons

• Complex UI.
• Model capability is limited to GPT2 NLP.

Writer AI Content Detector: Best for Integration

Writer is an AI writing assistant tool with a generative AI feature, plagiarism checker and AI detection capability. Writer standouts due to its extensive integration with third-party services like Contentful, Figma, and Chrome. Unlike other tools that require you to copy and paste text in their text box area, Writer AI allows you to enter the URL of the page containing the text and it will automatically extract the first 1,500 characters and analyze for AI content.

Although Writer doesn’t highlight AI text, it displays the content score as percentage. The first sample in is a text generated with ChatGPT, which the writer accurately scored 0% human-generated, while the second sample in is 100% human written, and the tool scored it 99% human generated.

Pricing

Writer offers a free plan and two paid plans. You can also try their paid plan for free for 14 days. Note that Writer AI detection is free, those looking for more than AI detection may consider the paid plan for additional features.

• Free plan: No charge for basic AI content detection.
• Team (for up to 5 people): $18 per user per month, billed monthly or $162 per user per month, billed annually.
• Enterprise: Custom quotes.

Writer AI Content Detector’s Standout Features

• Teams role and permission.
• Integrates with third-party services like Chrome, Google Docs, Word, Outlook, Figma, and Contentful.
• Bulk upload capability.
• Detects GPT-3 and ChatGPT.

Pros

• 24/7 phone, video, and email support.
• Easy to use.
• Scans content via website URL.

Cons

• 1,500 character limit per analysis.
• Easy to trick.
• Accuracy rate can be improved.

Copyleaks: Best for Content Marketing Agencies

Copyleaks is a plagiarism and AI content detection tool designed to help individuals, educators, and companies detect AI generated text. The platform boasts 99.12% accuracy and it detects content created with ChatGPT, GPT-4, GPT-3, Jasper, and other language models. We tested Copyleaks with original human written text (first image) and Google Bard AI generated text (second image) to check its accuracy. The platform scored our AI text with 99.9% probability for AI and scored our human text with 99.9% probability for human – this test validates Copyleaks accuracy claims. However, there are instances where human text is ranked lower than 99.9% but still accurately categorized as human written.

Pricing

Copyleaks pricing depends on the number of credits you need. It starts from $8.33 per month with no specific upper limit. Copyleaks’ trial plan offers 25 credits. Note that each Copyleaks credit covers up to 250 words of scanned content.

Copyleaks’s standout features

• Supports multiple languages, including Portuguese, English, German, French, and Spanish.
• LMS integration.
• Source code plagiarism detection.
• OCR (Optical Character Recognition) technology.
• ​​GPT-2, GPT-3, ChatGPT, GPT-4, T5, Bert, and Jasper.

Pros

• White-label option available.
• API integration into your enterprise system.
• Chrome extension available.

Cons

• Users must hover over text to get a percentage score.
• False positives.

Sapling.ai: Best for Agencies and Customer-Facing Teams

Developed by former researchers at Berkeley University of California, Stanford and Google, Sapling is a multipurpose AI tool with various functions, including grammar checker, punctuation check, sentence rewriter and AI detector. It detects GPT-3, GPT-3.5, ChatGPT, and GPT-4 AI contents. Sapling provides the total percentage of fake or AI generated content in a given text and highlights the AI generated content in red. Sapling boasts of detecting 97% of AI-generated text.

Pricing

Sapling offer a free plan and two paid plans – pro and enterprise. Users can test-run the Pro plan for 30 days before making a purchase decision.

• Free: No monthly or annual charges.
• Pro: $25 per month.
• Enterprise: Custom quote.

Sapling’s Standout Features

• Detects GPT-3, GPT-3.5, ChatGPT, and GPT-4.
• Boasts of 97% accuracy rating.
• Auto-complete, snippets, and chat assist.
• Integration with third-party apps like Salesforce, Pipedrive, HubSpot, Jira, and more.

Pros

• Generous free plan.
• Fast analysis.
• It can analyze 50 words and above.

Cons

• False positives and false negatives.
• Lacks plagiarism checks.

Hugging Face: Best for Technical Teams

Hugging Face is an AI tool designed to help AI and ML experts develop and deploy deep learning models. The AI content detector scan and analyzes text for the probability of real (human-generated) and fake (AI-generated) content. Hugging Face AI detectors result is displayed in decimal, making it difficult and complex for non-technical users to understand. The platform makes up for this by redirecting users to a more user-friendly free AI Content Detector, which analyzes text based on patterns and perplexity. The tool highlights AI text and shows the perplexity score when you hover over the text – it also displays the human score result in  percentage.

Pricing

Hugging Face AI detector is free to use. However, individuals looking for additional AI capability may be charged a fee for the service.

Hugging Face’s standout features

• PDF upload option via the AI content detector.
• Open source.
• Community support.

Pros

• Easy to use.
• Fast analysis.

Cons

• Lacks plagiarism checker.

Crossplag AI Content Detector: Best for Institutions

Crossplag AI detecting tool can be used to flag AI generated content. To use this tool, copy and paste text in the text box, click check and wait for a few seconds for the analysis to complete. The result is displayed via the AI Content Index, which ranges from 0% to 100%, with the latter being Human written and the former being AI generated. A score of 50% means the copy is both AI and human written.

Pricing

Crossplag offers tier pricing plans for different user categories.

For individuals

• Free: No charge for up to 1,000 words.
• Pay-as-you-go: $9.99 for up to 5,000 words.
• Bundle: $149.99 for up to 100,000 words.
• Custom: Contact sales.

For Education institutions

• Small: $3.99 per user for up to 500 users.
• Medium: $2.99 per user for up to 5,000 users.
• Large: $1.99 per user for up to 30,000 users.
• E-learning: White labeling for over 30,000 users – custom quotes.

For businesses: Contact the Crossplag sales team for custom quotes.

Crossplag AI Content Detector’s standout features

• Detects citations in the document.
• Plagiarism checking capability.
• Supports over 100 languages.
• LTI integrations.

Pros

• Dedicated reporting APIs.
• Free plan available.
• Supports multiple file formats.

Cons

• False negatives.
• Accuracy can be improved.

Honorary Mentions: AI Detectors

Although the following six noteworthy AI detector software didn’t make it to our top 10 list, they are also worth considering.

• Corrector App
• Kazan SEO
• Hive Moderation’s AI-Generated Content Detection
• AI Writing Check
• TurnItIn’s AI Detection Model

Also see: Generative AI Startups

Key Features of AI Detector Software

When shopping for the best AI detector software for your organization’s use cases, there are certain key features to look out for. While not all the tools embody all these features, it’s important to select a solution that has the most important feature for your needs.

AI Text Highlight

AI detector software that highlights text makes it easy for users to identify parts of their content that needs to be rewritten to sound more human. Some parts of your copy may be flagged as AI generated when in fact, it was 100% human-written – the highlighted text might help you know where to adjust or modify so that your text won’t be flagged.

Plagiarism Checker

Educators, content marketers, and SEO experts may find this feature beneficial. Using multiple tools to evaluate content based on different parameters like grammar, plagiarism, readability and AI generated may be time consuming and inefficient. AI detectors with plagiarism checkers take the burden of using multiple tools off editors and managers (think of it as killing two birds with one stone), as it enables them to check copy originality and quality.

API Integrations

With API integrations, AI content detector software can seamlessly integrate with other tools and platforms, such as content management systems (CMS), social media platforms, and e-commerce platforms. This feature makes it easier to automate the content moderation process and reduces the need for manual review.

Cost

The cost of AI content detector software is a major factor to consider. Before making a purchase decision, consider your budget. Different tools have different pricing models; ensure you select a tool that balances quality service and affordability.

Accuracy

The accuracy of the AI content detector software is critical to its effectiveness. The tool should be able to accurately identify and flag inappropriate or harmful content, as well as spam and copyrighted material. It’s important to select a solution that has a high accuracy rate, as false positives and false negatives can have significant consequences.

How to Choose the Best AI Detector For Your Needs

No one-size-fits-all exists when it comes to choosing an AI content detector tool. Most of the solutions in the market boast of over 90% accuracy rates, but keep in mind that these solutions are still being trained and have a long way to go.

Nonetheless, the best solution for your business is one that meets your needs and serves your company’s purpose. Follow the steps below to select the best AI software for your business.

• Research multiple solutions.
• Consider the features you need.
• Analyze at least 5-10 AI generated articles and human-written copy, respectively.
• Compare each tool, false positives and false negatives.
• Pick the one with the highest accuracy rates, within your budget.

You can also keep the second runner-up and the third-best as a backup analysis tool to double-check your scan texts in order to eliminate doubts.

Also see: What is Artificial Intelligence?

FAQs about AI Detector Tools

To help you make the best decision, we answered the most commonly asked questions about AI detector software.

How AI Content Detectors Work?

AI content detectors measure content’s perplexity and burstiness to identify patterns in the text. Perplexity and burstiness are two techniques that can be used by AI content detectors to identify patterns in text. Perplexity is a measure of how well a language model can predict a sequence of words – think of it as the randomness of words. While burstiness is the frequency of word usage in a given context – consider burst as the uniqueness of the random words.

Are AI content detectors accurate?

While most AI content detectors boast of over 90% accuracy rate, it’s important to note that these tools are still a work in progress. Generative AI companies are training their models to pass as human writers or creators, AI content detectors need equal or greater training to compete. Some tools have high accuracy rate than others – but none is perfect.

Can Google detect AI content?

Yes, Google can detect AI generated content by by searching for patterns like text structure, grammar, syntax in the text and inconsistencies.

Should I use an AI content detector?

AI content detectors are invaluable solutions for your overall SEO strategy. Consider using it if you need to verify the authority, authenticity, quality and transparency of your content.

Can an AI detector detect AI text with 100% accuracy?

No, AI content detectors cannot detect AI-generated text with 100% accuracy. While AI content detectors have improved significantly in recent years, they still have limitations and can produce false positives and false negatives.

AI Detectors: Review Methodology

We analyzed hundreds of AI detector tools and narrowed down our list to the top ten. We used each tool to gain first-hand experience. We also gathered primary data from each tool provider’s website, including pricing details, features, support and more. We selected each software based on five key data points: Ease of use, over 90% AI detection accuracy rate, affordability, quality service and user satisfaction.

Bottom Line: AI Detector Software

With the stunning rise in generative AI, an untold number of individuals are using tools like ChatGPT to create content in a manner that is partially or totally not ethical. Use of these powerful tools can invalidate an educational experience, or in some cases expose sensitive corporate data to security and compliance risks.

With these risks in mind, organizations of all types will likely want to select an AI detector tool that works best for their unique situation. Also realize: generative AI will be changing rapidly in the years ahead, so a solution that’s chosen today may need to be upgraded on a constant basis.

On a related topic: The Future of Artificial Intelligence 

The post Top 10 AI Detector Tools for 2023 appeared first on eWEEK.

By 2025, deep learning technology is predicted to have a global market revenue of $10.2 billion. This figure suggests that deep learning will see even more widespread adoption in the future. To help you stay ahead of your competition and develop AI models to enhance your business, we analyzed the best deep learning software currently leading the market.

Jump to:

• Best Deep learning software: Comparison chart
• PyTorch: Best for deep learning research and prototyping
• TensorFlow: Best for high-level model development
• H2O.ai: Best for building AI models and applications
• Keras: Best for beginners and researchers
• Neural Designer: Best for building predictive models
• Gensim: Best for natural language processing (NLP) tasks
• Caffe: Best deep learning framework for speed
• Apache SINGA: Best for heterogeneous computing environments
• Deeplearning4j: Best for Java-based projects
• Apache MXNet: Best for large scale deep learning and flexibility
• How to choose the best deep learning software for your business
• Review methodology
• Bottom Line: Best deep learning software

Best Deep learning software: Comparison chart

PyTorch: Best for deep learning research and prototyping

PyTorch is an open source machine learning (ML) framework based on Python and Torch library and is used for building deep learning models such as computer vision and natural language processing. It was originally developed by Meta AI, but it’s currently part of the Linux Foundation. The PyTorch ecosystem includes many high-level APIs and tools that simplify tasks like data loading, natural language processing, and reinforcement learning.

PyTorch pricing

PyTorch is free to install and use.

PyTorch key features

• Interoperates with major cloud platforms such as AWS, GCP, Alibaba Cloud, and Azure.
• Supports various neural network architectures like convolutional networks, recurrent networks, and transformers.
• Dynamic computational graph.

PyTorch pros

• PyTorch has a vibrant community of researchers, developers, and enthusiasts who actively contribute to its development.
• Easy debugging and rapid prototyping.
• Large community and ecosystem.

PyTorch cons

• Less mobile and embedded device support.
• Limited visualization tools.

For more information, also see: Best Machine Learning Platforms

TensorFlow: Best for high-level model development

TensorFlow is an end-to-end open-source machine learning framework developed by the Google Brain team. TensorFlow is used to facilitate the development of deep learning models. It provides an ecosystem of tools, libraries, and resources, enabling researchers and developers to build and deploy machine learning applications efficiently.

TensorFlow pricing

TensorFlow is free, open-source software.

TensorFlow key features

• TensorFlow includes automatic differentiation capabilities.
• It supports many different platforms and programming languages, including Python, C++, and JavaScript.
• Contains pre-trained models and datasets.
• Availability of statistical distributions.

TensorFlow pros

• Keras friendly.
• It offers visualization tools.
• Flexible deployment – web, mobile, edge and servers.

TensorFlow cons

• Limited support for Windows OS users.
• Only offers support for NVIDIA GPU and Python GPU.

On a related topic: Top Natural Language Processing Companies

H2O.ai: Best for building AI models and applications

H2O.ai is a fully open source, distributed in-memory machine learning platform that supports widely used statistical & machine learning algorithms, including gradient boosted machines, generalized linear models, and deep learning. Its Driverless AI tool, which is an automated machine learning platform, uses advanced algorithms and techniques to automate various steps in the machine learning workflow, including feature engineering, model selection, hyperparameter tuning, and model interpretation.

H2O.ai pricing

The H2O.ai platform has an open-source, freely available version. This version includes the core functionality of H2O and allows users to build models using a wide range of algorithms. H2O.ai also offers enterprise-level solutions and services, which may have additional pricing considerations. For instance, the H2O.ai AI Cloud costs $50,000 per unit, you must buy a minimum of four units.

H2O.ai key features

• Real-time data scoring.
• Automated machine learning.
• L1 or L2 regularization.
• Distributed in-memory computing.

H2O.ai pros

• Its user-friendly interface makes it accessible to non-experts.
• High-performance capabilities.

H2O.ai cons

• H2O.ai proprietary tools are expensive.
• Advance features require a strong statistics and machine learning background.

Also see: Best Artificial Intelligence Software 2023

Keras: Best for beginners and researchers

A top deep learning software worth considering is Keras. It stands out for its simplicity and ease of use. Keras, a Python-based deep learning library, was developed to enable fast experimentation and ease of use for building and training deep neural networks. It works as an interface for the machine learning platforms TensorFlow and Theano. These types of tools are expanding as artificial intelligence and generative AI sees dramatic growth.

Keras pricing

Keras is available for free.

Keras key features

• Built on top of the TensorFlow platform.
• Users can export Keras models to JavaScript to run directly in the browser to TF Lite to run on iOS, Android, and embedded devices.
• Support convolutional and recurrent networks.
• Allows users to define, compile, and train neural networks with a concise and intuitive syntax.

Keras pros

• User-friendly API.
• Designed to be backend-agnostic, meaning it can run on top of various deep learning frameworks.
• High-level abstractions.

Keras cons

• Limited flexibility.
• Limited documentation.

Also see: Top Generative AI Apps and Tools

Neural Designer: Best for building predictive models

Neural Designer is an AI platform that allows you to build AI-powered applications without without creating block diagrams or coding. This deep learning software can be used to discover relationships, recognize patterns, and predict trends from your data. Neural Designer is used extensively in several industries, including environment, banking, energy, insurance, healthcare, manufacturing, retail and engineering.

Neural Designer pricing

Neural Designer offers various pricing plans for different categories of users.

Standard licenses

• Small: $2,495 per user per year or $6,245 per user, lifetime access.
• Medium: $4,995 per user per year or $12,495 per user, lifetime access.
• Large: $7,495 per user per year or $18,745 per user, lifetime access.

Academic licenses

• Research: $2,495 per user per year or $6,245 per user, lifetime access.
• Teaching: $4,995 per module per year or $12,495 per user, lifetime access.
• Campus: Custom quotes.

Training programs

• Standard Training Program: Costs $1,495 for 8 hours.
• Personalised Training Program: Custom pricing.

Neural Designer key features

• GPU acceleration (NVIDIA CUDA).
• Multi-core parallelization (Intel MKL).
• High performance computing.

Neural Designer pros

• User-friendly graphical interface.
• It can handle different types of machine learning tasks, including classification, approximation, text classification, and forecasting.

Neural Designer cons

• Neural Designers require a license or subscription fee, which could be a consideration for individual users or small businesses on a budget.
• Dependency on user expertise.

Also see: Generative AI Startups

Gensim: Best for natural language processing (NLP) tasks

Gensim is an open-source Python library designed for topic modeling and natural language processing (NLP) tasks. For context, topic modeling is a technique used to discover hidden thematic structures in large collections of text documents. Gensim allows you to analyze, compare, and interpret large collections of textual data by enabling the creation of high-quality semantic representations.

Gensim provides implementations of popular topic modeling algorithms, such as Word2Vec, Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA), and others, for topic modeling and natural language processing tasks.

Gensim pricing

Gensim is a free deep learning software licensed under the OSI-approved GNU LGPLv2.1 license, making it free for both personal and commercial use.

Gensim key features

• Gensim runs on Linux, Windows and OS X.
• Also runs on platforms that support Python 3.6+ and NumPy.
• Provides implementations of popular algorithms like Word2Vec, LSA, and LDA.
• Non-negative matrix factorization.

Gensim pros

• Gensim is designed to handle large datasets efficiently, using memory-friendly techniques like streaming, which reduces memory consumption during processing.
• Memory independence.

Gensim cons

• While Gensim excels in traditional NLP techniques like topic modeling and word embeddings, it may not be the best choice for a wide array of Machine learning tasks.
• Lack of extensive documentation.

For more information: AI vs. ML

Caffe: Best deep learning framework for speed

Caffe is an open-source deep learning framework developed by Berkeley AI Research (BAIR) and community contributors. Yangqing Jia created the project during his Ph.D. at UC Berkeley.  It is written in C++ and provides a Python interface for ease of use. Caffe is designed to be efficient and flexible, allowing users to define, train, and deploy deep learning models for tasks such as image classification, object detection, and segmentation. It has gained popularity for its speed and ease of use in training and deploying convolutional neural networks (CNNs).

This deep learning software is mainly used for academic research projects, startup prototypes, and large-scale industrial applications in vision, speech, and multimedia.

Caffe pricing

Caffe is released under the BSD 2-Clause license, making it free to use.

Caffe key features

• Expressive architecture.
• Extensible code.
• Deployable on mobile devices.

Caffe pros

• Can process over 60M images per day with a single NVIDIA K40 GPU.
• Wide community support.

Caffe cons

• Limited language support.
• Steep learning curve.

Also see: Generative AI Companies: Top 12 Leaders

Apache SINGA: Best for heterogeneous computing environments

Apache SINGA is an open-source deep learning library and distributed training framework. The project ​ was designed to support and accelerate the training of large-scale machine learning models, particularly deep learning neural networks, across distributed computing resources. The deep learning software stack includes three major components: core, IO and model. It is widely used by various companies, including National University Hospital, Net Ease, Foodlg and more.

Apache SINGA pricing

It is free to use.

Apache SINGA key features

• Automatic gradient calculation.
• Memory optimization.
• Can be easily installed using Conda, Pip, Docker and from Source.
• Supports loading ONNX format models and saving models defined using SINGA APIs into ONNX format.
• Neural network model zoo.

Apache SINGA pros

• SINGA supports various popular optimizers, including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad.
• Time profiling capability.
• Multiple programming language support.

Apache SINGA cons

• Small community compared to some other deep learning frameworks.
• Limited documentation.

Also see: 100+ Top AI Companies 2023

Deeplearning4j: Best for Java-based projects

Released under Apache License 2.0, Deeplearning4j (DL4J) is an open-source, distributed deep learning library written for Java and Java Virtual Machine (JVM) languages. DL4J includes implementations of various deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more. The library supports distributed computing using Apache Hadoop and Apache Spark. This allows users to leverage multiple machines and GPUs to speed up the training process and handle large-scale data sets.

Deeplearning4j pricing

It is free to use.

Deeplearning4j key features

• GPU support for scaling on AWS.
• DL4J supports interoperability with other popular deep learning frameworks.
• Deeplearning4j can be used through multiple API languages, including Java, Scala, Python, Clojure and Kotlin.

Deeplearning4j pros

• Excellent community support and documentation.
• Incorporates ETL as part of the library.

Deeplearning4j cons

• Limited capabilities compared to TensorFlow or PyTorch.
• Less Python-Centric.

MXNet: Best for large scale deep learning and flexibility

MXNet is an open-source deep learning framework used for training and deploying artificial neural networks. It is designed to scale from large clusters of GPUs to multiple machines, and it supports various programming languages such as Python, R, Scala, and Julia. MXNet provides automatic differentiation, a crucial feature for training deep learning models, enabling the computation of gradients based on the model’s parameters.

MXNet pricing

It is free to use.

MXNet key features

• Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl.
• Hybrid front-end.
• Auto-Differentiation capability.
• Distributed training capability.

MXNet pros

• It supports multiple platforms, including Linux, MacOS. Windows and Cloud.
• Strong performance.

MXNet cons

• Steep learning curve.
• Limited documentation.

For more information, also see: Top AI Software

How to Choose the Best Deep Learning Software for Your Business

When shopping for the best deep learning software for your business, keep in mind that the best tool for you depends on your unique business needs. There are best practices to follow when looking for the best deep learning software that, if followed rigorously, will lead you to the best deep learning software for your organization.

• Start by defining your requirements.
• If your team is not already well-versed in deep learning, consider ease of use.
• Evaluate the scalability and performance of the software.
• Check which deep learning frameworks and libraries the software supports.
• Consider GPU and hardware support. Is your business equipped with what the software needs?
• Decide whether you want to use cloud-based deep learning platforms or host the software on-premise. In many cases, cloud-based offers advantages like scale and on-demand pricing.
• Consider integration with existing systems.
• Community and support: will you be able to get help from other users?
• Trial and experimentation – whenever possible, try out the software through free trials or demos.

Before making a final decision, make sure to read reviews and testimonials from other businesses that have used the software.

Review Methodology

To determine the top-rated deep learning software, we conducted extensive research to identify the best deep learning software that is currently popular and widely used in various industries. Our research process involved studying user reviews, expert opinions, and industry reports to gather insights into the performance, features, and user satisfaction of different software solutions.

We evaluated the available tools based on six key data points: usability and user interface, range and flexibility of algorithms, compatibility with popular deep learning frameworks, scalability and performance, availability of support and documentation, and overall user experience.

We then ranked the best deep learning software based on their performance against the criteria and user feedback.

Bottom Line: Best Deep Learning Software

The best deep learning software depends on your specific needs and preferences. We analyzed several popular and high-performing deep learning software, each with its strengths and limitations – no tool is perfect for every situation.

Still, there is likely a deep learning tool that is the best for your particular use case. If you need more than deep learning software, we also analyzed the top AI as a service companies and their offerings to expand your options beyond this immediate AI sector.

Also see: What is Artificial Intelligence?

The post 10 Best Deep Learning Software 2023 appeared first on eWEEK.

AIaaS companies are driven by a key mega-trend: Artificial intelligence (AI) is becoming commonplace in enterprises across industry sectors. Almost all businesses use at least one AI or cloud-based service to gain a competitive edge and outsource their needs to third-party vendors. Consequently, AIaaS companies are forecast to grow dramatically in the years ahead.

Jump to:

• • AI as a Service Companies: Comparison chart
  • IBM Watson: Best for automating complex processes
  • AWS AI Services: Best for features and global presence
  • Microsoft Azure AI: Best for developers and data scientists
  • Google Cloud AI: Best for data analytics
  • ServiceNow: Best for workflow automation
  • Salesforce Einstein AI: Best for marketing teams
  • Alibaba Cloud: Best for affordability
  • MonkeyLearn: Best for text analysis
  • DataRobot: Best for building custom models
  • Oracle Cloud Infrastructure (OCI): Best for anomaly detection
  • The Future of AIaaS
  • How to Choose the Best AI as a Service Company
  • Bottom Line: AI as a Service Companies

AI as a Service Companies: Comparison Chart

Best AI as a Service Companies

IBM Watson: Best for Automating Complex Processes

In the field of artificial intelligence, IBM has developed and offers a cognitive computing platform called IBM Watson. Watson is an AI system that combines natural language processing, machine learning, and other advanced technologies to analyze and understand large amounts of data. It has been used in various industries, including healthcare, finance, retail, and customer service, to provide insights, make recommendations, and assist with decision-making.

You can select from a variety of prebuilt apps from IBM Watson, including Watson Orchestrate for automating complex processes, Watson Assistant for building virtual agents, Watson Code Assistant, which helps developers write code with AI-generated recommendations, and Watson Discovery for content analysis.

Key features

• Natural language processing (NLP).
• Developer Tools and APIs.
• Data virtualization.
• Model development.
• Text, image and video analysis.

Pros

• Discovery and insights.
• It can help you generate code with applicable syntax from a natural language request.
• Speedy data discovery capability.

Cons

• Users reported that the tool has a steep learning curve.
• It may be too expensive for small businesses.

Pricing

IBM charges different rates for its various products and services. The amount you will pay depends on your chosen product. For instance, the IBM Watson Orchestrate base edition costs $200 per seat per month, Watson Assistant Plus plan starts at $140 per month. Watson Discovery Plus plan starts at $500, while its Enterprise plan starts at $5,000. Contact the IBM sales team to get the actual rate for your selected AI service.

AWS AI Services: Best for Features and Global Presence

Amazon Web Services (AWS) is a leading provider of cloud computing and AI services. The company offers various AI and ML services that can be segmented into different categories, including computer vision services like Amazon Rekognition, an image and video analysis tool, and Amazon Lookout for Vision for detecting defects and automating inspection. AWS also offers language AI tools such as Amazon Lex, a tool for building chatbots and virtual agents, and Amazon Transcribe for automatic speech recognition.

AWS offers hundreds of services worldwide, with data centers in multiple regions. This makes it an ideal choice for companies seeking an AI service provider with a global presence.

Key features

• AWS marketplace – an online store where a customer can search for software to buy for their business.
• Amazon Fraud Detector for online fraud detection.
• Amazon Forecast for forecasting business metrics.
• Code and DevOps services to improve application availability, perform automated code reviews and eliminate costly, inefficient code.

Pros

• Global presence and cost-effectiveness.
• Highly performant.
• Unlimited server capacity.

Cons

• Confusing billing due to price variations.
• Charges technical support fees.

Pricing

The amount you pay AWS depends on your selected service. You can also use the AWS calculator to get an estimate. Select the service you want to buy and follow the prompt on the screen to get an estimate.

Also see: Top Generative AI Apps and Tools

Microsoft Azure AI: Best for Developers and Data Scientists

Azure AI is a portfolio of AI services built for data scientists, developers, engineers and machine learning experts. With its knowledge mining platform, you can use Azure cognitive search to get insights from various types of content, including documents, images and media. Businesses looking to make their customer service more efficient and free up agents’ time to focus more on complex support tasks may find Azure conversational AI beneficial, as the Azure bot services let you build a multilingual and multimodal bot for your enterprise use case.

Key features

• Its machine translation capability lets you translate text and documents in real time in over 100 languages and dialects.
• Document process automation.
• Natural language processing.
• Built-in governance, security, and compliance.

Pros

• High availability.
• Users praise its role base access control capability.

Cons

• Requires platform expertise.
• Users reported that the Azure solutions are pricey.

Pricing

Microsoft Azure pricing varies based on your selected service. For instance, Azure Bot Services Premium Channels give you up to 10,000 messages per month and charge $0.50 per 1,000 messages. Azure Cognitive Search Basic plan costs $0.11 per hour, while its Storage Optimized L2 costs about $7.68 per hour. Its Open AI pricing also varies based on your model. To get the actual rate for your use cases, check the pricing page of your chosen Azure AI service or contact a sales representative for detailed quotes.

Google Cloud AI: Best for Data Analytics

Google, a leader in AI and data analytics, has been at the forefront of AI research and development, and its AI efforts encompass a wide range of applications, tools, and services.

Google has made significant contributions to the field of machine learning and deep learning. Its framework, TensorFlow, is an open-source library widely used for building and deploying machine learning models. Google also provides a suite of AI services through its Google Cloud Platform (GCP). This includes pre-trained models, APIs, and tools for natural language processing, computer vision, speech recognition, translation, recommendation systems, and more. Developers can leverage these services to integrate AI capabilities into their applications and workflows.

Key features

• Its generative AI tool, Google Bard, can help users create content.
• Its Studio Bot, which is an AI-powered coding assistant, can help Android developers fix bugs.
• Google’s PaLM 2 model can be used to build generative AI applications.
• The Cloud Vision API can identify objects, detect faces, read expressions and find similar images on the Web.

Pros

• Straightforward initial setup.
• Easy to train models.
• Integration with Google ecosystem.

Cons

• Limited customization.
• Customer support can be improved.

Pricing

Contact Google’s sales team for the price of your desired services. You can also check Google’s Vertex AI pricing page for the consolidated prices of their AI services.

Also see: Generative AI Companies: Top 12 Leaders

ServiceNow: Best for Workflow Automation

ServiceNow is known for its focus on automating workflows and improving service delivery across various departments within an organization. ServiceNow AIOps is a capability within the ServiceNow platform that combines artificial intelligence, machine learning, and automation to enhance IT operations management and drive proactive problem resolution.

Key features

• Search and automation, which includes AI search and automation discovery.
• Natural language processing capabilities which include foundational NLP, natural language understanding, NLU workbench and natural language query.
• Machine learning frameworks like similarity, classification, clustering and regression.
• Root cause analysis.

Pros

• Automation and remediation.
• Improve DevOps.
• Enhance the organization’s configuration management database (CMDB).

Cons

• The reporting feature can be improved.
• Steep learning curve for new users.

Pricing

ServiceNow encourages buyers to book a demo to learn more about the platform and also learn about the customer’s needs. Your requirements will be used to create your rates.

Salesforce Einstein AI: Best for Marketing Teams

Einstein is a Salesforce AI platform. It is integrated into various Salesforce products and offers a range of AI-driven features and capabilities to enhance sales, marketing, service, and overall customer engagement. The platform enables businesses to build AI-powered apps, automate processes, and gather insights to transform customer experiences. Einstein AI can perform complex tasks such as natural language processing, predictive analytics and machine learning to automate operations and uncover insights into customer data and behavior.

Key features

• Einstein’s vision lets you see the conversation about your brand on social media.
• Recognize text in images.
• It lets you build natural language processing into your apps to classify the underlying intent and sentiment.
• The platform allows users to build, train, and deploy custom bots on digital channels connected to their CRM data.

Pros

• Automatic speech recognition.
• Social image recognition.
• Lead scoring.

Cons

• Limited end-user customization.
• Some users reported that the Tableau CRM lacks some functionalities and can be improved.

Pricing

Sales Cloud Pricing:

• Starter: $25 per user per month, billed annually.
• Professional: $75 per user per month, billed annually.
• Enterprise: $150 per user per month, billed annually.
• Unlimited: $300 per user per month, billed annually.

You can add Einstein AI and Analytics to Service Cloud at $50 per user per month, billed annually.

Alibaba Cloud: Best for Affordability

With their expertise in big data analytics, natural language processing, image recognition, machine learning algorithms, and more, Alibaba’s AI and Data Intelligence platform is enabling companies to build intelligent applications that drive business value. The company provides numerous services, including virtual cloud servers, databases, storage systems, security solutions, big data services, and analytics tools.

Key features

• Vision AI includes optical character recognition, image recognition and videos.
• Intelligent Speech includes intelligent speech interaction, speech synthesis and speech analysis.
• Natural language processing includes machine translation and content moderation.
• It offers conversational AI capabilities and allows users to build multilingual chatbots over multiple channels to respond quickly to customers 24/7.

Pros

• Real-time speech transcription.
• Data intelligence application and visualization.
• Reliable documentation and support.
• Affordable pricing compared to some of its competitors.

Cons

• Limited presence outside Asia.
• Less familiar to engineers.

Pricing

Alibaba doesn’t advertise rates on its website. Interested buyers must contact the company for custom quotes.

Also see: Generative AI Examples

MonkeyLearn: Best for Text Analysis

MonkeyLearn is one of the best text analysis tools. With MonkeyLearn, users can access a repository of pre-trained models or train their own models to handle different tasks such as sentiment analysis, topic classification, keyword extraction, and content categorization.

With customer sentiment analysis, users can know their customers’ opinions about their products and services. This insight can be used to improve their customer experience. MonkeyLearn also makes it easy to analyze large amounts of unstructured data, such as social media posts and customer reviews.

Key features

• Data visualizations.
• Pre-built and custom machine learning models.
• Supports NPS, CSAT, survey, VoC, review, and support analysis.
• Text extraction includes feature extraction, keyword extraction, and entity extraction.
• Integrates with third-party services like Zendesk, Freshdesk, Medallia, Typeform, Airtable and more.

Pros

• Highly-customizable.
• Intent detection capability.
• Offers low-code, no-code text analytics.

Cons

• Expensive for small businesses and startups.
• Limited integration with third-party services.

Pricing

MonkeyLearn offers two pricing and plans.

• Team: $299 per month for up to three seats, three models and workflows, and 10K queries per month.
• Business: Custom pricing.

DataRobot: Best for Building Custom Models

DataRobot is an enterprise AI provider that helps companies build and deploy AI and machine learning models. It uses automated machine learning techniques to streamline the model development process. DataRobot automates various steps such as data preprocessing, feature engineering, model selection, and hyperparameter optimization.

Key features

• Production model lifecycle management.
• Prepare modeling data.
• Connects with data platforms like Google Big Query, Databricks, Amazon S3, Snowflake and more.

Pros

• Service health monitoring.
• Process large amounts of data quickly.
• Extensive feature engineering capability.

Cons

• Pricing is on the high side.
• The user interface can be improved.

Pricing

Although DataRobot doesn’t advertise its pricing on its website. Public available data shows that DataRobot AI Cloud, Starter Pack for AutoML, AutoTS, and MLOps costs $98,000 for 12 months.

H2O.ai: Best for Analytics and Predictions

H2O.ai is a platform of artificial intelligence and machine learning technologies powered by AutoML and no-code deep learning engines. It provides open source software, support, and services for developing machine learning models. H2O.ai specializes in developing predictive analytics and deep learning models that automate business processes and provide actionable insights. It offers a suite of products and services, including H2O Driverless AI, H2O AI Cloud, H2O Sparkling Water, H2O document AI, H2O-3, H2O Feature Store, and H2O Wave.

H2O.ai featured use cases include claims management, hospital capacity simulator, fraud detection and prediction of out-of-stock risks.

Key features

• Distributed, in-memory processing.
• Machine learning interpretability.
• It can automatically visualize and address data quality issues.
• Automates data science and machine learning workflows such as model tuning, model deployment, feature engineering, model validation, and model selection.

Pros

• The user interface is user-friendly and easy to use.
• A large community of users and developers supports it.
• H2O.ai’s models are able to handle complex data structures and large data sets.

Cons

• Documentation can be improved.
• It can be expensive and out of reach for small businesses or individuals.

Pricing

H2O.ai doesn’t advertise rates on their websites, they encourage buyers to contact their sales team for quotes. Publicly available data shows that H2O.ai Cloud costs $50,000 per unit – at least four AI units. They charge $200,000 for 12 months, $400,000 for 24 months and $600,000 for 36 months. H2O.ai Driverless AI Latest (BYOL) estimated infrastructure costs $3.06 per hour.

Oracle Cloud Infrastructure (OCI): Best for Anomaly Detection

Oracle provides multiple AI services, including digital assistant, which enables organizations to build conversational agents for business applications through text, chat, and voice interfaces. Speech-to-text services that help customers convert audio to text. Their AI Vision service allows customers to add image recognition capabilities.

Additionally, the company offers document analysis, AI forecasting, and anomaly detection. Customers can use these services to derive insights, glean new understanding from data, and automate processes.

Key features

• Prebuilt, conversational chatbots.
• Anomaly detection for managing assets and predictive maintenance.
• Text analysis capability.
• Real-time speech recognition.

Pros

• Sentiment analysis capability.
• High availability and fault tolerance.

Cons

• High-end cost.
• Technical support response time can be improved.

Pricing

Oracle pricing varies based on your selected service. For instance, Oracle Digital Assistant Cloud Service costs $0.0232 per unit, text translation costs $10 per unit, and pre-trained inferencing for over 5,000 transactions costs $0.25 per unit, and so on. Your actual price depends on your selected service, transaction volume and other factors unique to you.

Also see: 100+ Top AI Companies 2023

The Future of AIaaS

With several key trends and developments, the future of AIaaS is promising. Here are some potential directions for the future of AIaaS:

• Increased adoption: As AI technologies continue to mature and demonstrate their value across various industries, the adoption of AIaaS is likely to increase in areas like healthcare, finance, retail, and manufacturing.
• Advanced AI models: AIaaS providers will continue to develop and deploy more advanced and specialized AI models to tackle complex problems.
• Edge AI and IoT Integration: With the proliferation of the Internet of Things (IoT) devices, AIaaS will integrate with edge computing capabilities to bring AI processing and inference closer to the data source, reducing latency, improving response time, and enhancing privacy and security.
• Democratization of AI: As AIaaS becomes more accessible and user-friendly, it will empower non-experts to leverage AI technologies effectively. This democratization will enable a broader range of users and businesses to harness AI for various applications.

How to Choose the Best AI as a Service Company

Choosing the best AIaaS company requires careful consideration. Before selecting a company, assess the breadth and depth of AI services offered by the company. Consider whether their offerings align with your specific needs. As a general rule of thumb, it is best to consider a provider that offers a wide range of AI capabilities, such as natural language processing, computer vision, machine learning, or deep learning, depending on your requirements.

Evaluate the pricing model and cost structure of the AIaaS provider. Consider factors such as subscription fees, usage-based pricing, or any additional costs for customization, training, or ongoing support. Also, be sure to research the reputation of the AIaaS company by exploring reviews, testimonials, and industry feedback.

Bottom Line: AI as a Service Companies

AI as a service companies offer businesses access to cloud-based artificial intelligence technologies, a feat that is otherwise nearly impossible for most companies to achieve on their own due to limited or lack of resources, limited experts or internal skill sets. AIaaS companies are democratizing access to artificial intelligence and helping businesses discover new insights, track trends, automate digital processes, and study customer behavior quickly in near-real time, all without worrying about infrastructure or hardware investments.

The 11 AIaaS companies reviewed in this guide rank the highest in the AI sector and offer their customers the best-of-breed AIaaS solutions driving the highest customer satisfaction. These companies are helping to advance the industry’s technology and lowering the entry barriers to AI for a wide swath of businesses.

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