Best AI Software 2024: 15 Artificial Intelligence Platforms

Quick Summary:

AI software speeds things up, reduces errors, and automates repetitive tasks. In other words, the right software can help boost your productivity and accuracy. So, join us as we review some of the best AI software on the market. Each meets different needs, so choose according to yours.

Navigating the landscape for the best AI software can feel like finding a needle in a haystack. Sure, countless solutions are available, but which one truly aligns with your unique requirements? That’s why we’re here!

We've combed through the vast options, conducted extensive research, and put together a hand-picked selection of the top 15 artificial intelligence platforms for 2024.

Get ready to delve into our carefully selected collection of the best AI technology of the year. Let's dive in!

Best Artificial Intelligence Software Comparison Chart (Top 10 Artificial Intelligence Platforms)

Ready to choose your best AI software? Here's our top 10 AI platforms comparison chart. It shows each tool's price and what it's best for. This way, you can quickly compare them and find the right fit for you. 

What Are the Different Types of AI Software?

When diving into the world of software for AI, you'll notice there are three main types: technology-based, functionality-based, and capability-based AI software. Let's take a closer look at each one.

Technology-Based 

Technology-based AI software is categorized by its specific technologies, like machine learning, natural language processing, or computer vision. These software tools use advanced algorithms to learn from data and make predictions or decisions without being explicitly programmed to do so.

Functionality-Based 

Functionality-based AI software is organized by what it does. For instance, some software focuses on automating tasks, like chatbots for customer service. Others might be designed for data analysis to help businesses make sense of large amounts of data.

Capability-Based 

Capability-based AI software refers to the level of intelligence the software exhibits. It ranges from narrow AI, which is designed to perform a specific task, such as voice recognition, to general AI, which can understand, learn, and apply knowledge across a wide range of tasks similar to a human.

What is the Best AI Software? Here’s Our Top 15 List:

What is the best AI software currently available? It's time to dive deeper into our list of software solutions for artificial intelligence technology. We're going to explore each of the top 15 options in more detail, so you can see that every tool excels in its own unique way.

Let's get started!

1. Google Cloud AI Platform (Best AI Software Overall)

Why We Chose It:

Google Cloud AI, as one of the best AI platform companies, delivers a comprehensive range of machine learning tools for data scientists and developers. Its suite of services significantly enhances efficiency by offering readily available cloud APIs for tasks such as image processing, language translation, and video analysis.

Google Cloud AI is compatible with popular open-source frameworks like PyTorch, TensorFlow, and Scikit-learn. It provides a unified machine learning platform, Vertex AI, which simplifies building, deploying, and scaling AI models.

The platform hosts innovative AI services such as Generative AI, Data Science tools, and Responsible AI, emphasizing model interpretation and understanding.

Additionally, it includes robust tools like AutoML, Cloud Natural Language, Dialogflow, Speech-to-Text, Text-to-Speech, and Video AI.

Pros:

• Works with popular tools like TensorFlow and Scikit-learn

• Comes with its own ways of handling things like pictures, speech, language, and future predictions

• You can easily build, train, and use ML models, and it can handle big tasks

• Lots of guides to help you learn how to use it and make advanced things

Cons:

• The platform might be complex for beginners in machine learning and AI

• The pricing can be hard to understand and predict due to the many variables involved

• The heavy integration with the Google ecosystem can limit your options if you want to use services outside of it

Pricing:

• Check individual tools for pricing 

Visit site 
_{Go to Google Cloud AI’s official website}
 

2. ChatGPT (Best Free AI Software)

Why We Chose It:

ChatGPT, created by OpenAI, is really good at writing text that sounds like a person wrote it. It's handy for writing emails, making chatbots, or creating content quickly. This is great for businesses and writers who need to write a lot, fast.

The best part about ChatGPT is that it writes text that feels real and is easy to understand. Plus, it keeps getting better with regular updates.

ChatGPT has been recently integrated with the search engine Bing for more powerful and accurate answers. Via Zapier, you can connect ChatGPT with thousands of the most popular apps, including Slack, Spotify, Microsoft To-Do, Gmail, and more. 

Pros:

• It writes text that sounds like a human wrote it

• You can use it for many different things

• It keeps getting better with updates

• Integrates with thousands of the most popular apps via Zapier 

Cons:

• Sometimes it might not fully understand complex conversations

• It doesn't always know if the information is true or false

• It only knows information up to when it was last trained

Pricing:

• Free version

• Plus, $20/month 

Visit site 
_{Go to Chat GPT’s official website}
 

3. NVIDIA AI (Top On Premise AI Platform for Creating Complex AI Models)

Why We Chose It:

NVIDIA AI is a suite of tools focused on machine learning and artificial intelligence. It's ideal for individuals or businesses who handle large volumes of data or create complex AI models, such as data scientists or researchers.

The platform is known for its speed and capacity to manage challenging, resource-intensive tasks. Its compatibility with popular AI frameworks, like TensorFlow, adds to its appeal.

What sets NVIDIA AI apart as one of the top AI software is its potent processing capabilities, combined with a user-friendly approach, making complex AI tasks more accessible.

Pros:

• NVIDIA AI is known for its rapid processing capabilities

• It can handle complex, resource-intensive tasks

• It works well with popular AI frameworks like TensorFlow

Cons:

• While powerful, it can be challenging for beginners

• To get the most from NVIDIA AI, you need high-end NVIDIA GPUs, which may increase the cost

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to NVIDIA AI’s official website}
 

4. Azure Machine Learning (Great Cloud AI Platform for Novices)

Why We Chose It:

Azure Machine Learning is an AI tool by Microsoft, great for crafting AI models to predict outcomes from data. It's user-friendly, making it ideal for AI novices and experts alike. With Azure, you can create, train, and deploy AI models all in the cloud.

The highlight of Azure is its easy-to-use interface combined with effective problem-solving capabilities. Plus, it integrates seamlessly with other Microsoft tools. This blend of simplicity, power, and compatibility puts Azure Machine Learning among the best AI software on the market.

Pros:

• Has an intuitive interface that makes it easy to use

• It seamlessly integrates with other Microsoft tools

• It’s flexible and scalable 

Cons:

• Might not be a good choice for those not in the Microsoft ecosystem

Pricing:

• Refer to this page for pricing

Visit site 
_{Go to Azure Machine Learning’s official website}
 

5. IBM Watson (AI Development Software for Creating Natural Language and Visual Data Applications)

Why We Chose It:

IBM Watson is an AI development platform packed with ready-to-use apps and tools. You can build, manage, and monitor your AI while it learns from your data to predict future results. This means you can focus on creative work and leave the boring data entry to Watson.

IBM Watson is great for data scientists, making AI easier to understand and develop.

This AI has a user-friendly interface, a comprehensive model operation, and can be accessed through any cloud. Plus, because IBM makes it, you'll get access to other cool IBM features and open-source tools, similar to Google Cloud Learning.

Some tools you’ll find include Watson Orchestrate, Watson Virtual Assistant, and Watson Discovery. 

Pros:

• Can be used across various industries, from healthcare to finance, for a range of tasks like data analysis, prediction, and natural language understanding

• Provides sophisticated AI capabilities like machine learning, natural language processing, and image and speech recognition

• Can handle large amounts of data and can be scaled up or down based on the needs of the business

• Integrates well with other IBM products and external platforms

Cons:

• Despite its user-friendly interface, it may still take some time to fully understand all features

• While it offers many IBM features, it may not integrate as well with non-IBM tools

Pricing:

• Check individual tools for pricing

Visit site 
_{Go to IBM Watson’s official website}
 

6. TensorFlow (Best AI Platform for Versatility and Customization)

Why We Chose It:

TensorFlow is a free, open-source platform for machine learning that offers tools, libraries, and resources for developers and data scientists. This software lets you create big, complex models with layers of neural networks.

It's easy to use for beginners thanks to the high-level Keras API, but it's also customizable, which makes it good for all sizes of projects.

TensorFlow works everywhere - in the cloud, on your computer, on your phone, and even in your web browser. You can use it for things like recognizing images, analyzing videos, recognizing voices, and more.

It's one of the top AI software because it's popular, versatile, and backed by a great community.

Pros:

• Can run on multiple platforms like desktops, servers, and even mobile devices (iOS and Android)

• Designed to work with big data sets

• Vast community for support and continuous improvements to the platform

• Well-suited for developing deep learning models

• Robust support for neural networks and various tools for creating complex network architectures

• Integrates with Google's Cloud Platform

Cons:

• It has a steep learning curve 

• Can be slower for small scale and single-machine applications than some other libraries

Pricing:

• Free 

Visit site 
_{Go to TensorFlow’s official website}
 

7. Observe.AI (One of the Best Artificial Intelligence Tools for Contact Center Analytics and QA)

Why We Chose It:

Observe.AI, a call-analysis platform, harnesses automated speech recognition to improve business performance in real time. Primarily targeting English and Spanish-speaking markets, it allows organizations to effectively analyze calls using advanced speech and natural language processing technologies.

The tool can be seamlessly integrated with other business intelligence software.

Key functionalities include highly accurate transcription, sentiment analysis, silence detection, and automated redaction to ensure compliance and privacy. It also offers real-time AI solutions like Agent Assist and Supervisor Assist for in-call guidance and coaching.

With Observe.AI, businesses gain comprehensive insights from every customer interaction, which can be harnessed to optimize performance, boost sales, and enhance compliance. 

Pros:

• Offers highly precise transcription services using advanced AI

• Its real-time AI solutions like Agent Assist and Supervisor Assist provide valuable in-call coaching

• Analyzes 100% of customer interactions, providing extensive insights for business improvements

• Can be integrated with other business intelligence software

• Features like automated redaction ensure data privacy and compliance

Cons:

• Unlike some competitors, Observe.AI doesn't offer a free trial, which may deter some potential users

• The platform may have a steep learning curve for some users, especially those new to call-analysis software

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to Observe.AI’s official website}
 

8. Infosys XtractEdge (for Businesses with Heavy Reliance on Document Processing)

Why We Chose It:

Infosys XtractEdge (formerly Infosys Nia) is an AI tool that uses machine learning, deep learning, and natural language processing to automate complex tasks, boost productivity, and draw insights from documents. It digs into data hidden in documents and changes images into text through optical character recognition (OCR).

This tool can handle a wide range of documents like contracts, insurance papers, emails, PDFs, handwritten notes, and images. It helps businesses uncover insights from unstructured data and provide measurable value. With impressive client results, it's an ideal tool for businesses that process a lot of documents. 

Pros:

• Great for businesses that have to deal with different types of documents like emails, contracts, PDFs, and more

• Can take care of difficult tasks and help your team be more productive

• Doesn't just process documents, it can also draw useful insights from them

Cons:

• It could be a bit hard to use, especially for beginners

• If your business doesn't deal with a lot of documents, it might not be as useful

• While its OCR feature is generally accurate, there might be instances when it could make mistakes especially with very complex or poor quality documents

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to Infosys XtractEdge's official website}

9. H2O.AI (Best Open-Source AI Platform)

Why We Chose It:

H2O.AI provides an open-source platform that simplifies the development and deployment of AI models. Equipped with pre-trained, open-source models and algorithms, it’s designed to help developers of all skill levels create scalable AI solutions. The platform provides deployment flexibility, catering to on-premise or cloud-based preferences.

Its flagship offerings include h2oGPT, an open-source generative AI, and H2O LLM Studio, a no-code interface for fine-tuning large language models.

With the H2O AI Cloud, even non-data scientists can develop world-class AI models in minutes. This platform not only supports the creation and operation of machine learning models and applications with transparency and speed, but it also facilitates performance monitoring and the innovation of user-friendly business solutions. 

Pros:

• Enables users to modify and optimize as per their requirements

• Flexibility to choose the best fit for a particular problem

• Supports on-premise or cloud-based deployments

• Offers a no-code interface for fine-tuning models, making it accessible to non-data scientists

Cons:

• Some functionalities may require a good understanding of machine learning concepts

• Being open-source, users might have to rely on community support for resolving some issues

• While it's capable of handling large datasets, performance can vary depending on the specific use case and deployment scenario

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to H2O.AI’s official website}
 

10. Chorus.AI (Great Artificial Intelligence Platform As a Service for Conversation Analytics in Sales)

Why We Chose It:

Chorus.ai is an AI platform as a service conversation intelligence tool aimed at high-growth sales teams. Its primary purpose is to record, manage, and transcribe calls, providing real-time insights.

The AI-powered software allows teams to tag significant action items and subjects during calls, enhancing their organization and communication processes.

Additionally, Chorus.ai employs machine learning to analyze data and uncover valuable insights, guiding sales strategy and follow-ups. Key features include call recording, sales coaching, and sales management.

Chorus.ai integrates with ZoomInfo to bring in-depth contact and company intelligence to the teams, making it a powerful tool for managing customer relationships and maximizing revenue. 

Pros:

• Helps identify successful strategies and trends

• Instant capturing of important points and follow-up actions during calls

• Comes with Sales Coaching that helps identify winning behaviors

• Automatically syncs data to your CRM, giving complete visibility into relationships that drive revenue

• Helps you understand why you win or lose deals

Cons:

• It may offer limited utility for teams outside sales and customer relations

• If the call or meeting recordings are of low quality, the transcriptions and subsequent analytics might be affected

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to Chorus.AI’s official website}
 

11. Run.ai (Best AI ML Platform for Automated Machine Learning Tasks)

Why We Chose It:

Run artificial intelligence software is an AI software that helps you manage and make the most of your GPU cluster for AI development. It bridges the gap between MLOps and AI computing, scheduling, integrating, and managing your AI cluster. With features like GPU Scheduler and friendly UI, it lets you assign resources easily and provides on-demand access to GPUs.

You can also connect to any ML tool of your choice. As one of the best AI ML platforms, it's perfect for data scientists, MLOps, and engineers who want to streamline their development process, lower AI infrastructure costs, and efficiently provision compute and data pipelines.

Pros:

• Makes the most out of your GPU resources

• Easily connects to any ML tool of your choice

• Simplifies environment provisioning and eliminates concerns over remote connection security or complex command-line interfaces

Cons:

• There may be a learning curve for those new to AI development or MLOps

• Organizations without extensive GPU resources may not reap the full benefits

Pricing:

• Free demo

• Pricing details are custom and available upon request

Visit site 
_{Go to Run.AI’s official website}
 

12. Amazon SageMaker (One of the Best Artificial Intelligence Data Products for ML Innovation at Scale)

Why We Chose It:

Amazon SageMaker is an AI tool that streamlines the creation, training, and deployment of machine learning models. Its feature-rich platform caters to data scientists and business analysts, supporting various data types and ML frameworks.

SageMaker boosts productivity through reduced training times and standardized machine learning operations (MLOps) practices. It also introduces Geospatial ML for building models using geospatial data.

Backed by Amazon's extensive ML expertise, SageMaker enables over a trillion predictions per month and substantially decreases training times and costs, making it an excellent choice for ML innovation at scale.

Pros:

• Offers a complete set of tools for building, training, and deploying machine learning models

• Provides interfaces for both data scientists and business analysts, making machine learning more accessible

• Handles large-scale projects efficiently with robust infrastructure and support for leading ML frameworks

• Efficient use of GPUs enables faster model training

Cons:

• There can be a learning curve, particularly for those unfamiliar with AWS

• Depending on the scale and complexity of the project, costs can escalate quickly

• Compared to other platforms, the free tier offerings are limited

• Integration with non-AWS services can be challenging

Pricing:

• Free Tier usage per month for the first 2 months

• Calculate your cost here

Visit site 
_{Go to Amazon SageMaker’s official website}
 

13. Scikit-learn (Best AI Program for PC)

Why We Chose It:

Scikit-learn, an open-source Python library, is a great AI software for PC. It’s widely utilized for predictive analytics, offering algorithms for classification, regression, and clustering.

Built to interoperate with Python's numerical libraries, NumPy and SciPy, it facilitates efficient data analysis. Some core algorithms use Cython for improved performance, while integration with Python libraries like Matplotlib and plotly broadens its applications.

It's highly popular, cited as one of GitHub's most used machine learning libraries. Its commercial usability due to its BSD license, combined with its accessibility and efficiency, makes scikit-learn an ideal choice for data scientists and researchers.

Pros:

• Free to use and commercially viable under a BSD license

• Offers a range of machine learning algorithms

• Works well with other Python libraries like NumPy, SciPy, and Matplotlib

• Widely used and well-documented, providing an extensive community for support

Cons:

• Lacks comprehensive support for deep learning tasks

• Might be less efficient for very large datasets compared to some other libraries

• Core algorithms written in Python may be slower than those in lower-level languages like C++

Pricing:

• Free 

Visit site 
_{Go to Scikit-Learn’s official website}
 

14. Datarobot (Great AI Tool for Data Scientists, Developers, and Business Analysts)

Why We Chose It:

DataRobot is an automated machine-learning platform designed to expedite the development and deployment of predictive models.

Suitable for data scientists, developers, and business analysts, this tool is ideal for extracting valuable insights from data rapidly and efficiently. Its state-of-the-art AI features encourage collaboration and experimentation, with both code-first and no-code options.

Critical machine learning capabilities and automation functionalities facilitate scalable value production. In addition, DataRobot promotes model governance and compliance by automating performance tests and model documentation.

Its broad enterprise ecosystem integrates with existing technologies, data platforms, AI frameworks, and DevOps tools. 

Pros:

• Simplifies the development and deployment of ML models

• Supports both code-first and no-code options, catering to a variety of user expertise levels

• Provides the capabilities necessary for large-scale ML deployment

• Automated performance tests and model documentation aid in adhering to regulations

Cons:

• As with all ML tools, the quality of insights depends on the quality of input data

• While automation is convenient, it may limit the degree of customizability some advanced users might want

Pricing:

• Pricing details are custom and available upon request

Visit site 
_{Go to DataRobot’s official website}
 

15. Google Dialogflow (Top AI Software for Creating Conversational Interfaces)

Why We Chose It:

Google Dialogflow, part of Google Cloud AI, is an advanced tool for creating conversational interfaces using Natural Language Processing (NLP).

This software is ideal for developers wanting to design chatbots or voicebots that can seamlessly integrate with messaging platforms and voice assistants. Dialogflow helps design agents capable of multi-turn conversations, creating a more natural and intuitive customer experience.

The tool boasts a visual builder that significantly reduces development time and supports deployment across different digital channels.

The platform also allows for easier management with continuous integration and delivery (CI/CD) mechanisms, as well as advanced AI capabilities, including BERT-based natural language understanding models.

Pros:

• Uses advanced NLP to provide natural, multi-turn conversations

• Integrates with various messaging platforms and voice assistants, making it versatile

• The visual builder and prebuilt agents significantly cut down on development time

• Equipped to handle large-scale implementations thanks to its flow-based modules

• Can handle complex use cases

Cons:

• May require some time for users to get completely familiar with all its features

• Costs can add up quickly for larger, more complex deployments

• Some users might find it limiting if they require highly specific customizations outside of its built-in features

Pricing:

• Dialogflow is priced monthly based on the edition and the requests made during the month. Find out more here. 

Visit site
_{Go to Google Dialogflow’s official website}

What is AI Software & What Does it Do?

AI software, or artificial intelligence in software, refers to computer AI programs that simulate human intelligence processes like learning, problem-solving, and decision-making. They perform tasks such as data analysis, prediction, and automation, often with minimal human intervention. 

By integrating AI in software applications, complex tasks can be executed efficiently, enhancing productivity and driving innovation in various sectors such as healthcare, finance, marketing, and more.

Which of These AI Programs is Best for Me? Our Conclusion

In our exploration of the best artificial intelligence tools, we've identified the Google Cloud AI Platform as our top pick overall, closely followed by ChatGPT. Both platforms offer a range of robust features that can address various AI needs. 

However, remember that the best AI computer program for you ultimately depends on your unique needs, budget, and personal preferences.

DataRobot, Chorus.AI, Run.ai, and Azure Machine Learning also stood out as strong contenders, each offering unique functionalities that could align with your objectives. We encourage you to explore these tools, as well as others, to find the right fit. 

Fortunately, most AI software providers offer free trials or demos, allowing you to test out their platforms before making a decision. 

Your ideal AI solution is out there; it's just a matter of finding it!

FAQs

What is the Most Advanced Artificial Intelligence Software?

OpenAI's GPT-3 stands out as one of the most advanced artificial intelligence software options available at this time. Other powerful AI software includes Google Cloud AI, Azure Machine Learning by Microsoft, IBM Watson, and various other cutting-edge platforms developed by companies and research institutions worldwide.

When Was the First AI Learning Platform Created?

The first AI learning platform was developed in 1984 by Douglas Lenat. It is named "Cybernetics and Cognition" (CYC). CYC aimed to simulate human common sense and knowledge in a computer-readable format. It laid the foundation for subsequent AI learning platforms and knowledge representation systems of today.

What Happens if AI Software Learns to Make AI Software?

If AI software learns to make AI software, it could lead to an exponential advancement in AI capabilities. This concept, known as "recursive self-improvement," has been theorized by experts to potentially result in a rapid evolution of AI systems, leading to the emergence of highly sophisticated artificial intelligence platform companies. 

However, the full implications and consequences of this scenario remain uncertain and speculative.