Tianyi Chen pushes the limits of artificial intelligence by asking an urgent question: what if AI could be designed not only to optimize for a single result, but to make more intelligent and more balanced decisions – a bit like humans?
Chen, a new associate professor of electrical and computer engineering at Cornell Tech and Cornell Engineering, uses deep mathematical information to design algorithms which help to juggle the AI of several priorities at the same time – precision, equity, efficiency and reliability – rather than optimizing for one.
This balanced approach could make generative AI tools more reliable, strengthen large -scale IT systems and improve the energy efficiency of new AI chips that feed them. His work has already led to patented innovations thanks to collaborations with IBM.
