Open Source Business Intelligence Tools Advancing Policy Management – Benefit from the collective intelligence of a global community of developers and the world’s best research labs for your next AI project.
Open source AI is defined as artificial intelligence technology that is publicly available for commercial and non-commercial use under various open source licenses. Open source AI includes datasets, pre-built algorithms, and ready-to-use interfaces to help you get started developing AI applications. It is expected that, up from 48% in 2021, 65% of enterprises will begin using open source AI technology in the next two years. This article briefly lists the top 10 open source software you should consider for your next AI project.
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Open source AI is an artificial intelligence technology that can be used for commercial and non-commercial purposes under a variety of open source licenses. Open source AI can include a variety of technologies useful to product teams, individual application developers, and enterprises.
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Open source AI differs from free AI applications in that the underlying code is open to users and open to modifications and implementations other than those originally intended. Open source comes with an active community where developers can contribute and ask for help.
Today, open source AI is a growing segment that benefits developers and businesses alike. According to Open a new window research, 48% of enterprises use open source technologies for AI/ML and this percentage will increase to 65% by 2023.
As mentioned above, AI software can come in many different shapes and sizes, covering datasets, algorithms, user interface, or any combination of the three. In this review (in alphabetical order), we look at common AI use cases such as computer vision, object recognition, character recognition, and speech synthesis, and focus on the ten best open source AI algorithm libraries that can be used to create software applications, and others.
Disclaimer: This is a list based on publicly available information and may include websites intended for medium to large businesses. Readers are encouraged to do their own final research to ensure the best solution for their specific organizational needs.
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Overview: Founded in 2019, Acumos is a relatively new entrant in the open source segment of AI software, but is backed by industry leaders AT&T and TechMahindra. The two companies wanted to buck the trend of tech giants Microsoft, Google and Apple, leaders of open source innovation, and make artificial intelligence commercially viable. In doing so, they introduced Acumos AI, a Linux-based design studio, to help integrate other frameworks and develop cloud-based AI applications.
USP: One of the major USPs of Acumos AI is its GUI design studio functionality. It simplifies the development process and makes it more accessible by simplifying visual programming and artificial intelligence. You can also use the installer to enable functionality with other frameworks, such as TensorFlow and H2O.
Editor’s Note: Acumos is an open source alternative for those interested in more accessible AI. It standardizes your infrastructure stack so you can develop and deploy AI applications faster and is compatible with most major languages, including Java, Python, and R. The Acumos AI Platform manages the end-to-end lifecycle of AI/ML applications. create templates for market deployment, enrichment, and publishing.
Overview: ClearML is the result of a recent rebranding of Allegro AI, a provider of open source tools for data scientists and machine learning labs. Along with the rebranding, ClearML announced a free hosting plan that gives data scientists the freedom to run AI/ML experiments and manage workloads without investing in additional resources. ClearML can be used as an MLOps solution and is ready to deploy via just two lines of code.
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USP: ClearML is one of the few open source AI software with priority support, well-defined SLAs, and optional commercial add-ons such as managed services. If you want the benefits of open source (vendor independence, cross-ecosystem compatibility, etc.) while having a commercial vendor partner, ClearML is a great choice.
Editor’s Note: ClearML has many great features that are rarely seen in the open source segment. For example, even if you choose ClearML Free, you’ll get 100GB of free storage, 3 collaboration areas, low-integration development, and on-premise deployment support. At the opposite end of the spectrum, there is also the pipeline of opportunities for more advanced development. In other words, ClearML perfectly balances the simplicity of open source with the features of traditional commercial platforms.
Overview: Founded in 2012, H2O has been at the forefront of open source AI innovation for nearly a decade. The company partners with tech giants like NVIDIA, IBM, Intel, and Google to advance leading AI and ML products. The company was recently accredited by Singapore’s Infocomm Media Development Authority (IMDA), further strengthening its global presence and enabling Singapore government agencies to benefit from H2O.
USP: H2O’s biggest USP is its AI hybrid cloud capabilities. It means an end-to-end platform that allows you to train, model, operate, develop and use AI (in collaboration with others) in a centralized environment. It is integrated into Kubernetes, so you can run it on any cloud infrastructure or even on-premise.
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Editor’s note: H2O is great for companies just getting started with AI, because you can get started with an open source platform that trains on your business data. As more applications evolve, H2O can support your organization’s journey through training, enhancement requests, automated ML, and more.
Overview: Mycroft is an open source voice assistant that can work in any ecosystem. The company has won numerous awards over the years and is supported by strategic investments from major companies such as Jaguar Landrover. Essentially, Mycroft uses open source AI technology to power various elements of the voice stack. There are many users, developers and translators who are constantly improving AI algorithms.
USP: Mycroft’s biggest USP is that it’s relatively easy to get started. In addition to commercial implementations like Alexa or Siri, it also offers an AI-based personal voice that will extract data at a certain level. That’s why I cover public sector and philanthropy that values data privacy.
Editor’s Note: Unlike most open source AI software, Mycroft focuses heavily on usability. However, if you need a voice assistant and want to go open source, Mycroft is one of the most powerful options.
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Overview: The Open Source Computer Vision Library, or OpenCV, is a rich library of artificial intelligence algorithms designed to solve computer vision tasks in real time. It was launched in 1999 as part of an Intel research project in the early days of artificial intelligence development. In 2012 it was acquired by a non-profit foundation and now manages the community, user support and developer assistance. In 2020, the OpenCV AI Kit campaign was launched to raise funds for new hardware modules.
USP: OpenCV is one of the longest-running and most tested open-source AI software libraries in the industry. Since its inception, Intel has developed C++ from a computer vision library into a widely accessible, deployment-ready platform.
Editorial note: Companies looking to use AI-powered computer vision to develop facial recognition systems, augmented reality apps, and more should consider OpenCV. A rich algorithm library combined with training support and complementary hardware creates a 360-degree solution.
Overview: OpenNN is an open source AI software library for implementing neural networks and ML. Its primary use cases include customer intelligence and industry-specific analytics, including predictive applications. The company that develops and maintains OpenNN is called Artelnics, known for its research into artificial intelligence and big data. Importantly, unlike the other open source software on this list, OpenNN does not specialize in computer vision or natural language processing.
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USP: The most important USP of OpenNN is its ability to provide predictive insights. You can use this open-source AI software to build apps for customer segmentation, early healthcare diagnostics, predictive equipment maintenance, and much more.
Editorial Note: Companies, teams, and individual developers looking for a pure open source AI software library (no commercial frills) should consider OpenNN. You can find its rich documentation, which provides a useful guide to get started.
Overview: PyTorch is an enhancement to the core ML Torch that uses the Lua programming language. In 2016, Facebook’s AI Research Lab launched PyTorch as a Python-based interface for developing AI/ML applications under an open source license. There is also a C++ interface for PyTorch. Today, PyTorch has evolved into a rich ecosystem that gives you all the tools you need to accelerate AI development, from research to production.
USP: Python’s biggest USP is probably its ready availability in the cloud on Alibaba Cloud, Amazon Web Services, Google Cloud Platform, and Microsoft Azure. This allows you to quickly download software libraries from relevant app marketplaces and get started without leaving your current cloud-based development environment.
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Editorial note: PyTorch has the most extensive use cases among the top open source AI software. Not only can you use it for computer vision, but you can also use PyTorch for audio processing, NLP, language translation, and more.
Overview: Rasa is the most popular open source AI
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