At IBM we created an AI Roadmap for the next few years. Folks... check what is coming: 𝟮𝟬𝟮𝟯: 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹𝘀 𝗲𝘅𝘁𝗲𝗻𝗱𝘀 𝗯𝗲𝘆𝗼𝗻𝗱 𝗻𝗮𝘁𝘂𝗿𝗮𝗹 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴. In 2023, it will expand enterprise foundation model use cases beyond natural language processing (NLP). 100B+ parameter models will be operationalized for bespoke, targeted use cases, opening the door to broader enterprise adoption. 𝟮𝟬𝟮𝟰: 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝘁𝗿𝘂𝘀𝘁 𝗽𝗲𝗿𝗺𝗲𝗮𝘁𝗲 𝗔𝗜 In 2024, we will integrate trust guardrails throughout the AI foundation models lifecycle and AI governance at the organizational level. Data representations will optimize across privacy, fairness, explainability, robustness, etc. 𝟮𝟬𝟮𝟱: 𝗔𝗜 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗺𝗼𝗿𝗲 𝗲𝗻𝗲𝗿𝗴𝘆 𝗮𝗻𝗱 𝗰𝗼𝘀𝘁 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 In 2025, we will improve the energy and cost efficiency of foundation model training and inference by 5x and bring 200B+ parameter foundation models to enterprises. It’s all about making them more powerful, useful, and practical. 𝟮𝟬𝟮𝟳: 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹𝘀 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗯𝗲𝗰𝗼𝗺𝗲 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 By 2027, we will be routinely doubling the number of foundation model parameters in production for the same energy envelope every 18 months. Training and inference will be 4x more energy efficient vs. 2025. 𝟮𝟬𝟮𝟵: 𝗧𝗿𝘂𝘀𝘁𝘄𝗼𝗿𝘁𝗵𝘆 𝗮𝗻𝗱 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗔𝗜 𝘀𝘁𝗮𝗿𝘁𝘀 𝘁𝗼 𝗿𝗲𝗮𝘀𝗼𝗻 2029 will be an inflection point. AI will support diverse forms of reasoning with explainability and trust. Energy efficiency will increase 4x more and scalable, operationalized AI models will be routine in enterprises. Large-scale self-supervised neural networks, i.e., foundation models, multiply the productivity and the multi-modal capabilities of AI. More general forms of AI emerge to support reasoning and common-sense knowledge. Get ready, we are just getting started!