蜜桃传媒

In this talk, I present our experiments that explore opportunities for synergy between Traditional AI (e.g., SAT solvers), or ML (e.g., fine-tuned models) with large API-based language models such as GPT-4. I describe several scenarios where such combinations are meaningful and helpful, including reasoning tasks like solving Sudoku, knowledge-tasks like QA and dialog, and also routing tasks for cost-quality optimization over LLMs.

Mausam is a Professor of Computer Science and founding head of Yardi School of AI at IIT Delhi, along with being an affiliate professor at 蜜桃传媒 of Washington, Seattle. He has over 100 archival papers, a book, two best paper awards, and a test of time award to his credit. He has been a PC Chair for AAAI, is currently an Editor-in-Chief for ARR, and was recently elected as an AAAI Fellow. He is currently on a sabbatical working as a Visiting NLP Researcher at Bloomberg's AI group in New York.