Have you ever thought about how unique AI applications and innovations work?
Well, it’s all because of open-source AI platforms, the driving force behind countless innovative projects.
The demand for robust and reliable tools inside AI frameworks has reached new heights in an era of constantly evolving technology. This highlights the crucial role of open-source AI platforms.
And, with so many open-source AI platforms available online, it’s natural to feel confused.
For this reason, we have hand-picked 18 open-source AI platforms capable of advancing your projects.
But first, let’s discuss what open source AI is.
Open Source AI: What is It?
Open Source AI is about openly sharing code so developers can collaborate to invent, improve, and exchange AI technology. This team-based approach facilitates the creation of innovative AI applications more quickly. You can get these projects on sites such as GitHub, and they significantly influence areas such as healthcare, manufacturing, education, and finance.
What’s impressive is that AI frameworks are accessible on various platforms, including Microsoft Windows, Linux, iOS, and Android. This means that developers have the tools to solve complex issues effectively.
Plus, by leveraging existing libraries and technologies, small teams may focus on developing specific solutions rather than beginning from scratch. Open source AI balances differences by enabling everyone access to the latest innovations and helping businesses create practical applications faster.
Main Motives of Using Open Source AI Platforms
Open-source AI platforms have emerged as a powerful force promoting accessibility and innovation in various fields. Their distinctive features benefit researchers, developers, and organizations similarly.
Now, let’s explore the main reasons for using various such AI platforms:
Multiple Use Cases
Numerous valuable applications, such as real-time detection, medical image analysis, tailored recommendations, and customized learning experiences, are possible with open-source AI platforms. Because of their versatility, developers can tackle many problems in many sectors.
Building Strong Developers Networks
Organizations may have access to a varied developer community that consistently improves and advances AI technologies by utilizing open-source AI. Knowledge exchange, creativity, and group problem-solving are encouraged by this cooperative landscape.
Openness and Continuous Development
Open source AI is collaborative, which promotes transparency and allows for continuous progress. Open code review, contribution, and iteration enable developers to create feature-rich, trustworthy, modular solutions that change over time.
Universal Accessibility
Developers, researchers, and organizations may easily access open-source AI tools, which promote their broad acceptance and use. Because of their accessibility, cutting-edge AI technologies are now more widely available, leveling the playing field for innovation.
Top 18 Open Source AI Platforms to Elevate Your Projects
After learning about what an open source AI platform is and its benefits, you better understand how it can be helpful to you.
So, it’s time to unwrap the list of the top 18 open-source AI platforms that can elevate your initiatives.
Whether you’re new to micro AI or exploring open-source AI initiatives, we have you covered. We have discussed all the free and paid open-source AI platforms here.
Excited to know?
Then, keep scrolling to discover the list!
1.TensorFlow
TensorFlow is a top-notch open-source AI platform that enables programmers to collaborate and exploit current models while generating new ones. This open-source AI platform allows you to harness the power of data in your business.
And you can do it by creating complex predictive modeling applications. It uses data flow graphs to develop models and is also helpful for perception, comprehension, prediction, creation, and categorization.
Standout Features
- Compatible with a wide range of systems and programming languages.
- Offers tutorials and training videos to support learners
- Javascript and Python interact with this AI platform without any issues.
- Enables developing and deploying machine learning models on various platforms and devices.
- Takes advantage of a strong community providing resources and help.
Area of Expertise
- Mathematical computation and scalable machine learning
Industry Partners
- Airbnb
- Airbus
- Carousell
- GE Healthcare
- Coca Cola
Platform Compatibility
- Linux
- Windows
- Android
- iPhone/ iPad
Pricing
- Free
2. Pytorch
Like TensorFlow, Pytorch is a complete framework for converting ideas into practical applications. It’s a comprehensive framework with many tools and datasets to facilitate all aspects of developing open-source AI projects.
PyTorch has an easy-to-use interface and was created with Python developers in mind. Its object-oriented design makes it easier to package modular code fragments performing a particular function.
These clearly defined “objects” may be easily included in more extensive workflows, simplifying intricate processes and encouraging programmer cooperation.
Moreover, while Python-savvy developers will find PyTorch especially useful, it also provides a C++ interface for those who are not proficient in Python.
Standout Features
- Well-supported on all major cloud platforms, allowing for easy development and scaling.
- The PyTorch ecosystem includes various tools for computer vision, natural language processing, and other tasks.
- Improve performance by utilizing native async operations and peer-to-peer connectivity.
- The torch. the distributed backend allows for scalable training and optimization.
Area of Expertise
- Deep learning and AI
Industry Partners
- Meta
- Microsoft
- IBM
- Intel
Platform Compatibility
- Windows
- Linux
- Mac
Pricing
- Free
3. Keras
Keras, created by François Chollet, is an application programming interface (API) that lets you rapidly share the front end of your deep learning models. It is billed as being created with people in mind.
One of its most noteworthy features is its high-level API, which is decisive for expert users and intuitive for newcomers alike, making it an excellent option for complex deep-learning jobs and instructional reasons.
Your code is easier to read and understand when you use Keras. XLA compilation with JAX and TensorFlow makes models run quicker, while tools like TF Serving, TorchServe, TF Lite, and TF.js make it easier to publish models across several platforms.
Standout Features
- Accessible and user-friendly API, particularly for novices.
- Runs flexibly on top of several backends like PyTorch, TensorFlow, and JAX.
- Effective implementation for quicker training and inference using XLA compilation.
- Allows deployment in various settings, including browsers, mobile devices, and servers.
- Prioritizes debugging speed, maintainability, deployability, and elegant and concise code.
Area of Expertise
- Simplifies deep learning tasks
Platform Compatibility
- Linux
- MacOS
- Windows
Industry Partners
- NVIDIA
- Amazon Web Services
Pricing
- Free
4. Open AI
OpenAI is a well-known research company committed to advancing artificial intelligence while prioritizing human safety. Their ground-breaking work in natural language processing (NLP) has sparked worldwide interest.
One of their noteworthy contributions is Codex. It is a methodology for converting natural language into code in various computer languages.
Furthermore, in keeping with the idea of open-source AI efforts, OpenAI provides access to their models, allowing customers to tweak the code to meet their needs.
Standout Features
- OpenAI leads the way in AI research by putting ethics and safety first.
- Provide free access to sophisticated AI models for development, such as GPT and Codex.
- OpenAI works with businesses and organizations to promote innovation.
- Promote AI learning via seminars and documentation.
- It guarantees that advances in AI are equitable and beneficial to society.
- GPT and Codex cover NLP, computer vision, and robotics.
Area of Expertise
- Machine learning research, Natural language processing, fraud detection, and computer vision
Platform Compatibility
- Windows
- MacOS
- Linux
Pricing
- A free three-month trial period with a $18 credit. Reimburse only for services provided.
5. RASA
RASA is another one of the best open-source AI platforms. It is best for generating and implementing a conversational AI framework via the cloud. This best open-source AI platform uses machine learning to interpret and create natural language replies, enabling sophisticated conversation engagements.
This open-source AI platform is described as “future-proof” and versatile. Any NLP or ML model can be integrated into it to enhance the accuracy of results as technology advances.
Businesses should use targeted conversational AI with integrated social messaging interfaces, such as Slack and Facebook. Rasa now offers Docker images for deployments that are built, which makes installation easier and guarantees consistency between various environments.
Standout Features
- Pre-built modules for popular chatbot functionality.
- A simple layout allows for customization and integration.
- Community support and engaged growth.
Area of Expertise
- Development and deployment of conversational AI solutions such as chatbots and virtual assistants.
Industry Partners
- Ergo
- American Express
- Lemonade
- Tia
- Adobe
Platform Compatibility
- Windows
- MacOS
- Linux
Pricing
- Free
- For businesses, there are also premium alternatives.
6. OpenCV
The next best open-source AI platform on our list is OpenCV. It is a leading option for businesses developing innovative solutions, analyzing visual data, and automating processes.
This open-source AI platform is well-known for computer vision. TensorFlow could have an undergraduate background in broad artificial intelligence, but OpenCV is superior in AI vision—it’s like having a master’s degree in the subject.
Because much of its library is written in C, it runs on various platforms, demonstrating its adaptability. OpenCV claims to work with multiple platforms, from “PowerPC Macs to robotic dogs.”
Furthermore, it facilitates smooth cross-language development with its contemporary C++ interface and support for wrappers for Python, Java, and other languages.
Standout Features
- Extensive capabilities for object identification, video analysis, and picture modification.
- Excellent performance and instantaneous capabilities.
- Support for several programming languages and cross-platform compatibility.
Area of Expertise
- Computer vision library for processing images and videos in real time.
Industry Partners
- Huawei
- Intel
- Dronecode Foundation
- Microsoft Azure
Platform Compatibility
- Windows
- Linux
- Android
- iPhone/iPad
Pricing:
- Free, even when used for business purposes.
7. Amazon Sagemaker
Next on the list of 18 best open-source AI platforms is Amazon Sagemaker. AWS’s cloud-based solution, Amazon SageMaker, simplifies the development, testing, and implementation of machine learning models on a broad scale.
This completely managed platform offers tools for data labeling, model training, and deployment, catering to developers, data scientists, and machine learning specialists.
With the help of a full suite of tools integrated into a fully managed service, this open-source AI platform makes high-performance, reasonably priced machine learning (ML) possible for any application.
Standout Features
- Numerous pre-built tools and algorithms for a range of activities.
- Smooth interaction with other AWS services
- Infrastructure that can be scaled up to manage big AI projects.
Area of Expertise
- Development, training, and deployment of cloud-based machine learning models
Industry Partners
- Accenture
- Intel
- GE Healthcare
Platform Compatibility
- Windows
- MacOS
- Linux
- Cloud Platform- Amazon Web Services
Pricing:
- $0.05/month
8. Amazon Web Services (AWS)
Amazon Web Services (AWS) now comes on our list of the best open-source AI platforms.
If you need a reliable platform to get your platform started or if you have code to run, AWS offers a free choice. The platform also neatly saves your applications’ output and results.
AWS also provides an abundance of value-added capabilities for corporate marketing. This includes managing task coordination for your various cloud apps and modifying your code for their content delivery network—all for free.
Standout Features
- Offers high availability and fault tolerance, reducing downtime, with many data centers worldwide.
- Supports a thriving user and developer community by offering a wealth of documentation, tutorials, forums, and support alternatives.
- Offers a full range of services to meet various business requirements, including computation, storage, databases, machine learning, analytics, and more.
- With AWS’s capacity to scale resources up or down in response to demand, optimizing performance and minimizing costs is possible.
Area of Expertise
- Offers a full range of cloud computing services, such as software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS).
Industry Partners
- Databricks
- Broadridge
- Radis LABS
- Hashicorp
Platform Compatibility
- Windows
- Linux
- MacOS
Pricing
- Its Prices vary.
- There are always free alternatives, 12-month free offerings, and limited-time deals.
9. IBM Watson
IBM Watson is a machine learning platform with NLP and other AI capabilities. It enables companies to create artificial intelligence-powered apps, improve decision-making procedures, and glean meaningful insights from data.
Watson’s versatility makes it a leader in AI and applies to various areas, including healthcare, finance, and customer service. It can access external and internal data sources since it integrates with many databases.
Standout Features
- Leverages advanced natural language processing (NLP) to understand human language, allowing accessible text or voice communication.
- With IBM Watson’s automated predictive analytics, you may create predictive models without requiring high data science knowledge.
- Robust data visualization features from IBM Watson make creating dynamic dashboards and visualizations possible.
- Cognitive analytics is a tool that IBM Watson uses to analyze data, find trends, and make wise suggestions.
Area of Expertise
- Top open-source AI platform for advanced data analysis and assessment.
Industry Partners
- Telefonica
- American Airlines
Platform Compatibility
- Windows
- Linux
- MacOS
- Cloud Platforms ( AWS, Azure, and IBM Cloud)
Pricing:
- $140/month
10. H20.ai
As an open-source solution, H2O.ai facilitates the creation and implementation of AI and machine learning models. The platform provides various automated tools and algorithms for specific tasks, including feature engineering, data preparation, and model selection.
This open-source AI platform offers easy interaction with popular data science tools and enterprise-grade support. The AI Cloud Platform from H2O.ai commits to moral AI practices and bills itself as the “fastest, most accurate” AI platform.
Their goal is to enable everyone to access this technology and democratize and humanize the use of AI, enabling everyone to use it to improve society.
Standout Features
- Large-scale model development and deployment using scalable infrastructure.
- Optimization of hyperparameters and automatic model adjustment.
- API access combined with a user-friendly UI and visual processes.
Area of Expertise
- Offer innovative machine learning and artificial intelligence solutions, specifically in data science and model building.
Industry Partners
- Snowflake
- Microsoft
- Capgemini
- Databricks
Platform Compatibility
- Windows
- Linux
- MacOS
- Cloud-based platforms (AWS, Azure, and Google Cloud)
Pricing
- Using H20 Wave API and creating open-source apps is free.
11. Microsoft Azure
Microsoft Azure is the fastest-growing cloud service platform in the world since it offers various AI-related services. Azure’s AI features include bot frameworks, machine learning, and cognitive services.
It is essential to AI systems for enterprises utilizing cloud computing since it provides substantial infrastructure for the scalability and deployment of machine learning models.
Standout Features
- Customize the software to fit each user’s needs and tastes.
- Pay as you go or get a 30-day free trial of Azure. You can cancel at any time; there is no upfront commitment.
- Get easily accessible support and direction that is built into the platform.
- Make use of virtualized computing systems to distribute resources in a flexible and scalable manner.
- Centralized interface for resource and service management across Azure.
- Kubernetes-based containerized application deployment and administration made more accessible on the Azure platform.
Area of Expertise
- Provide cloud computing services for developing, implementing, and administrating services and applications.
Industry Partners
- Visma
- Terragon
- Icertis
- Global EY Organization
Platform Compatibility
- Windows
- Linux
- MacOS
Pricing:
- $29
12. Apache MXNet
The next best open-source AI platform is Apache MXNet. The Apache Software Foundation created this adaptable and practical deep learning framework.
Apache MxNet offers a range of high-level APIs for more efficient model development and supports several programming languages. The automated parallelization and dynamic dependency scheduler of MXNet maximizes the use of computing resources.
Because of its speed and scalability, you may use it for production and research applications.
Standout Features
- Support Scala, Julia, Clojure, Java, C++, R, and Perl, as well as deep integration with Python.
- Combines imperative and symbolic programming paradigms for maximum speed and versatility.
- In addition to enabling use cases in machine vision, NLP, time series, and other fields, a robust ecosystem of tools and libraries expands MXNet.
Area of Expertise
- Open-source deep learning framework that is versatile and efficient for various purposes.
Industry Partners
- Ciao
- Cluster one
- Eagle View
- Wolfram
Platform Compatibility
- Windows
- Linux
- MacOS
Pricing
- Free
13. SciKit-Learn
Scikit-learn is a powerful Python package for predictive data analysis and machine learning. It plays a vital role in the AI frameworks of companies like J.P. Morgan and Spotify by providing scalable supervised and unsupervised learning algorithms.
SciKit-Learn provides a range of supervised and unsupervised learning techniques for applications, including feature extraction, dimensionality reduction, clustering, regression, and classification.
Standout Features
- Easy-to-use and effective instruments for analyzing predictive data.
- Universally accessible and adaptable to different situations.
Area of Expertise
- Provide a comprehensive machine learning library for data science and classical methods.
Industry Partners
- NVIDIA
- Data iku
- AWeber Communications
Platform Compatibility
- Windows
- Linux
- MacOS
Pricing
- Free
14. GitHub
Whichever platform you decide on, the GitHub platform maintains organization in collaborative work. When many people work on the same code, the platform keeps track of notes, Wikis, and version history to manage projects.
It facilitates project management when several people work on the same code. GitHub is, therefore, necessary for people or teams to collaborate effectively on a project.
Standout Features
- Promotes smooth teamwork using pull requests, code reviews, and problem tracking.
- Supports software project construction, testing, and deployment automation using GitHub Actions.
- Creates a thriving developer community by utilizing social tools, wikis, and discussion forums.
- Protects code and repositories by putting security features like two-factor authentication, code scanning, and vulnerability warnings into practice.
- Improves efficiency and workflow by integrating with a range of third-party products and services.
Area of Expertise
- Offer software development teams a complete platform for version control, teamwork, project management, and workflow automation.
Industry Partners
- Shopify
- Stripe
- Indeed
- AWS
Platform Compatibility
- Web Browsers
- Windows
- Linux
- MacOS
- Android
- iOS
Pricing
- Price: Basic $0
- Team $44
- Enterprise $231
15. GitHub AI Projects: Instagram Spam Protection & Fake Product Review Identification
We’re integrating these open-source AI platforms into our GitHub development because, once content is live, social network management becomes an essential part of marketing.
With the help of these initiatives, we can train our programming models more thoroughly using pre-existing datasets, which improves brand protection and guarantees a consistent flow of leads.
Standout Features
- Promotes smooth teamwork using pull requests, code reviews, and problem tracking.
- Supports software project construction, testing, and deployment automation using GitHub Actions.
- Creates a thriving developer community by utilizing social tools, wikis, and discussion forums.
- Protects code and repositories by putting security features like two-factor authentication, code scanning, and vulnerability warnings into practice.
- Improves efficiency and workflow by integrating with a range of third-party products and services.
Area of Expertise
- Offer software development teams a complete platform for version control, teamwork, project management, and workflow automation.
Industry Partners
- Shopify
- Indeed
- AWS
Platform Compatibility
- Web Browsers
- Windows
- Linux
- MacOS
- Android
- iOS
Pricing:
- Free
16. OpenNN
OpenNN is another of the best open-source AI platforms available. It is an open-source AI software package that implements ML and neural networks. Known for its groundbreaking work in big data and artificial intelligence, Artelnics is the firm that created and manages OpenNN.
Unlike some of the other open-source AI tools on this list, OpenNN does not focus on computer vision or natural language processing. Customer intelligence and industry-specific analytics, particularly their predictive applications, are among its prominent use cases.
Standout Features
- Regression analysis for ML output modeling
- Classifying data to identify particular patterns
- Use historical datasets for forecasting.
- Mapping the associations between two correlated variables
- A neural designer tool to make the process of creating neural networks more
Area of Expertise
- Create apps for early healthcare diagnosis, equipment predictive maintenance, consumer segmentation, and many other uses.
Industry Partners
- Airbus
- Philips
- Thales
Platform Compatibility
- Web Browsers
- Windows
- Linux
- MacOS
Pricing:
- Free
17. Acumos AI
Acumos AI ranks second to last among the top 18 open-source AI platforms. Acumos is a relatively young player in the open-source AI software space, but industry heavyweights TechMahindra and AT&T support it.
The two businesses aimed to make AI available for commercial use, defying the tendency of computer behemoths like Microsoft, Google, and Apple to spearhead open-source advancements.
For this reason, they launched Acumos AI, a Linux-based design studio that aids in developing cloud-based AI applications and integrating other frameworks.
Standout Features
- The Acumos marketplace allows you to find and use different AI libraries.
- Support for onboarding to facilitate interoperability.
- An interface for managing AI models graphically in advance of a runtime environment.
- A group to provide solutions for the market.
- AI operates within a container with Dockerization support.
- Microservices tools and connection through APIs.
Area of Expertise
- Simplifies the process of developing AI and visual programming making it more approachable and accessible to grasp.
Industry Partners
- Airbus
- Philips
- Thales
Platform Compatibility
- Linux
- Dockers
- Kubernetes
Pricing
- Free
18. ClearML
Allegro AI, a developer of open-source tools for data scientists and machine learning laboratories, rebranded itself as ClearML. Along with the rebranding, ClearML unveiled a free hosted option that allows data scientists to manage AI/ML experiments and organize workloads without incurring additional costs.
ClearML may be used as an MLOps solution, with implementation as simple as two lines of code. It is one of the few open source AI platforms that offer optional paid add-ons, including managed services, well-defined SLAs, and priority support.
ClearML is an excellent option if you want the advantages of open sources—such as cross-ecosystem interoperability and lack of vendor dependency—but still have access to a commercial vendor partner.
Standout Features
- A setting for managing experiments that requires no integration work.
- Job scheduling using resource allocation and priority queues.
- Workspace for collaboration with optional authorization control.
Area of Expertise
- Offer tools to track and control ML experiments.
Industry Partners
- Sony
- Shutterfly
- Outbrain
Platform Compatibility
- Windows
- Linux
- MacOS
Pricing
- Free for up to 3 users
- Pro: $15
- Scale: Custom
- Enterprise: Custom
Tips for the Responsible Implementation of Open Source AI Platforms
It is essential to understand that progress frequently necessitates effort. So, we must also quickly recognize the critical human components of even the most advanced technology developments.
Similarly, you should always approach any open-source AI platform with a dedication to morality and security. Here we are giving you some tips that you need to keep in mind to ensure the efficient and safe use of open-source AI platforms:
- Establishing clear, quantifiable goals before starting custom AI development is essential. This will prevent mismatched results, resource waste, and project failure, ensuring alignment with business needs and intended results.
- Biased algorithms in AI solutions can lead to inaccurate findings and negative preconceptions. To reduce bias, use various data sources, conduct bias audits, implement fairness-aware algorithms, and regularly assess model performance for equality.
- The availability of open-source AI platforms poses security risks, as malicious actors may use them to manipulate results or create harmful content. Implement robust security measures to safeguard AI systems against vulnerabilities and threats.
Conclusion
That’s it! We’ve uncovered the best 18 open-source AI platforms to empower your projects.
These platforms, from TensorFlow to ClearML, provide a wide range of tools and capabilities to help you enhance your innovation in all your endeavors.
So, what’s your next move?
Which one of these open-source AI platforms are you going to implement?
Let us know in the comment section below. We would love to hear from you 🙂
And, if you’re interested in AI tools, explore the world of AI by clicking here.
FAQs
What is an open-source AI platform?
Open-source AI platforms allow everyone to use, edit, and share the source code without restriction.
Are there any free, open-source AI platforms?
Indeed, there are several free, open-source AI platforms accessible. For example:
- RASA
- OpenCV
- PyTorch
- TensorFlow
Which open-source AI platforms are the most advantageous for developers and companies?
Open-source AI platforms have several benefits, such as openness, cooperation for ongoing development, and access to a varied developer community of continuing enhancement.
Which factors should be considered most when choosing the best open source AI platform for a project?
Establishing clear project goals is essential when selecting an open source AI platform to prevent resource waste and inconsistent results.
