【講者】 Dr. Irina Rish, Full Professor, Université de Montréal | Mila – Quebec AI Institute | CERC in autonomous AI
【講題】Towards Genuinely Open AI: the Role of High-Performance Compute
【摘要】 The rapidly expanding field of large-scale self-supervised models (a.k.a. “foundation models”) continues to make significant advances towards solving long-standing AI challenges such as a broad generalization and transfer, bringing the AI field closer to its “holy grail’ of achieving the Artificial General Intelligence (AGI), and impacting a wide range of scientific and societal applications. However, this type of research requires the amount of compute currently unavailable to academic and nonprofit organizations, thus widening the “compute gap” with industry and leading to concentration of AI power in a few leading companies. This motivated us – a rapidly growing international collaboration across several Universities and non-profit organizations – to join forces and initiate an effort towards developing common objectives and tools for advancing the field of large-scale foundation models. Our long-term, overarching goal is to develop a wide international collaboration united by the objective of building foundation models that are increasingly more powerful, while at the same time are safe, robust and aligned with human values. Such models aim to serve as the foundation for numerous AI applications, from industry to healthcare to scientific discovery – i.e., AI-powered applications of great societal value. We aim to avoid accumulation of the most advanced AI technology in a small set of large companies, while jointly advancing the field of AI and keeping it open (“democratization” of AI). Obtaining an access to large-scale computational resources would greatly facilitate the development of open AI research world-wide, and ensure a collaborative, collective solution to the challenge of making AI systems of the future not only highly advanced but maximally beneficial for the whole of humanity.