Why open source artificial intelligence platforms help enterprise business transformation

As advancements in artificial intelligence and machine learning (AI/ML) rise, business leaders are now embracing open source culture and technologies. There are several reasons for this, including collaboration across organizations, accelerated innovation, and social responsibility. A software-maker culture inspires established companies to experiment with AI and create platforms that align with their business needs. While AI/ML initiatives can deliver significant benefits, they are not without challenges and risks. Among the challenges are cost, lack of tools for machine learning operations, and lack of responsible AI tools. Downloading open source software may introduce the risk of lack of governance and security or lead to shadow IT and drive associated risks. When embraced appropriately with the right security and management layers, AI/ML can deliver effective business capabilities, including flexibility, agility, portability, and overall time to value. In this episode, Ritu Jyoti, Group Vice President, Worldwide Artificial Intelligence Research Practice, describes AI/ML adoption trends and challenges, how open source MLOps platforms may help, synergies with a hybrid cloud approach, and best practices and recommendations. Ritu will also briefly describe a couple of customer scenarios resulting from interviews that IDC conducted with multiple Red Hat® customers who have been successfully using Red Hat OpenShift® AI for accelerating the AI/ML life cycle.