Major new emerging technological workloads are increasingly using enterprise open source, with 80% of companies expecting to do so in fields including artificial intelligence (AI), machine learning (ML), edge computing, and the Internet of Things (IoT), as per the latest Red Hat report 2022. Artificial intelligence (AI) that is publicly accessible for business and non-commercial use under different open source licences is known as open source AI. Open source AI can consist of datasets, prebuilt algorithms, and ready-to-use interfaces to help develop AI app development. 

But how does the open-source help? To be precise, it enables developers to collaborate and share code, data, and ideas; the open source model has proved effective in the AI field. Any technological advancement requires cooperation, so in the years to come, this may have the potential to be more remarkable developments emerge from the AI community. In the end, working together helps innovate and execute tasks faster.

Let's have a look at the top five (in no particular order) open-source AI software in 2022. 

OpenCV 

Open Source Computer Vision Library (OpenCV) is an open-source computer vision and machine learning software library. An extensive collection of AI algorithms was created to solve real-time computer vision tasks. It was introduced in 1999 as a part of an Intel research effort at the infancy of AI development. A non-profit foundation took over management of the community, user support, and developer help in 2012. More than 2500 optimised algorithms are available in the collection, including a wide range of both classic and cutting-edge computer vision and ML techniques. These techniques may be used to identify items, detect and recognise faces, categorise human behaviours in films, follow camera movements, follow moving objects, extract 3D models of objects, detect and recognise faces in images, and many more.

One can make the best out of it here.

Acumos AI

Acumos AI is an open-source framework that makes it easy to build, share, and deploy AI apps. Acumos is supported by two major players in the space: AT&T and TechMahindra. It enables seamless connectivity between applications like TensorFlow and SciKit Learn by encasing models and tools in a single API. It is linguistically independent and supports models and tools created in many widely used programming languages. Acumos is made to take advantage of contemporary microservices. By making AI available for commercial deployments, the two businesses hoped to buck the trend of tech behemoths like Microsoft, Google, and Apple driving open source innovations.

One can check out this open-source framework here. 

ClearML

Allegro AI, a supplier of open source tools for data scientists and machine learning labs, underwent a makeover, and the outcome is ClearML. To be precise, it is an open source company that provides ML developers, data scientist-practitioners and engineering managers the tools to explore more with their machine and deep learning projects. With only two lines of code needed for implementation, ClearML can be used as an MLOps solution. One of the key associated features is that the framework provides the ability to run Bayesian hyperparameter optimisation with zero integration. Even if one chooses ClearML Free, one can still get 100GB of free storage, a workspace for three collaborators, low integration development, and support for on-premise deployment.

Explore the open-source framework here.

H2O.ai

H2O, an organisation founded in 2012, has spent nearly ten years at the forefront of open source AI innovation. To advance large-scale AI and ML solutions, the company collaborates with tech behemoths like NVIDIA, Intel, IBM, and Google, among others. A distributed in-memory ML platform with linear scalability, H2O is completely open source. The most popular statistical and machine learning methods, such as deep learning, gradient boosted machines, and generalised linear models, are supported by H2O. Over 18,000 businesses worldwide use the H2O platform, which is also very well-liked in the R and Python communities.

One can explore the platform here.

PyTorch

In 2016, PyTorch, a Python-based interface for creating AI/ML apps, was released by Facebook's AI research division under an open source licence. Additionally, PyTorch has a C++ interface that is accessible. Today, PyTorch has grown into a robust ecosystem with all the tools required to speed up the development of AI from research to production. Moreover, a rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. 

One can explore the platform here.