Terrent Tao's video description:
In this experiment, I took a statement in universal algebra that a collaborator of mine (Bruno Le Floch) on the Equational Theories Project had written a one-page human proof of, and set the task of formalizing the proof in a very low-level, "line by line" fashion, with heavy reliance on both the large language model-powered code completion tool "Github Copilot" and the dependent type matching tactic "canonical". The proof was formalized in about 33 minutes.
The demo looks really appealing. I have a real-world use case in mind: analyzing an Excel file and asking questions about its contents. The current approach (https://github.com/pydantic/pydantic-ai/blob/main/mcp-run-py...) seems limited to running standalone scripts—it doesn't support reading and processing files. Is there an extension or workaround to enable file input and processing?
Could you also elaborate on how companies can reach out to you and Eric? What are the key criteria or 'table stakes' you look for in a project or team?
Jeremy, you've taken a bold, open initiative. Thank you for calling on all the small, innovative teams. To better understand the types of projects or applications that excite you and Eric most, could you share examples of companies or applications that Answer.AI currently supports or plants to invest in? Additionally, if yo u have any published articles detailing these ventures please share the link. Best wishes with your venture.