The inaugural class of the LIA-AI Growth Academy celebrate its graduation at Stony Brook’s Center of Excellence in Wireless and Information Technology.
A Stony Brook PhD student and assistant professor explored human supervision shaping large language models and how can models take part in their improvement.
Lav Varshney, Director of Stony Brook University's AI Innovation Institute, discussed the puzzles, pitfalls and possibilities of a more AI-reliant world.
Stony Brook's Yi Liu is leading a project rebuilding generative AI to create new molecules, and one exploring design and optimization of battery electrolytes.
Undergraduate student research was featured in the AI Innovation Institute’s AI Innovation and Diffusion Research Experience for Undergraduates (REU) program.
Through the LIA-AI Growth Academy, 50 local ventures are in an intensive training program designed to turn AI daunting concept into a toolkit for success.
Stony Brook University has partnered with the Long Island Association (LIA) and its philanthropic arm, the LIA Foundation, to launch the LIA-AI Growth Academy.
Researchers from leading institutions across the country gathered at Stony Brook University for an invite-only Embodied AI Workshop, a day-long event exploring how artificial intelligence is beginning to move beyond...
Edward Reiner is a Stony Brook ‘77 alumnus whose career has followed healthcare’s shift from paper charts to terabytes of data and now, to large language models
Stony Brook's Jeffrey Heinz is trying to answer a deceptively simple question: How well, exactly, can today’s neural networks learn, and where do they fail?
When Ankita Nagpal boarded a flight from India to the United States, she brought a passion for writing and a sense that she needed time to grow as a writer.
The symposium ‘Unsettling Intelligences: The Politics of Reason through AI and Art’ marked a partnership that blurred the line between research and exhibition.
The AI Innovation Institute will present a seminar titled, "Information-Theoretic Framework for Understanding Modern Machine-Learning," on November 10.