Professor
Swarat Chaudhuri from the University of Texas at Austin and visiting researcher at Google DeepMind discusses breakthroughs in AI reasoning, theorem proving, and mathematical discovery. Chaudhuri explains his groundbreaking work on COPRA (a GPT-based prover agent), shares insights on neurosymbolic approaches to AI.
Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on ARC and AGI, they just acquired MindsAI - the current winners of the ARC challenge. Are you interested in working on ARC, or getting involved in their events? Goto
https://tufalabs.ai
TOC:
[
00:00:00] 0. Introduction / CentML ad, Tufa ad1. AI Reasoning: From Language Models to Neurosymbolic Approaches
[
00:02:27] 1.1 Defining Reasoning in AI
[
00:09:51] 1.2 Limitations of Current Language Models
[
00:17:22] 1.3 Neuro-symbolic Approaches and Program Synthesis
[
00:24:59] 1.4 COPRA and In-Context Learning for Theorem Proving
[
00:34:39] 1.5 Symbolic Regression and LLM-Guided Abstraction2. AI in Mathematics: Theorem Proving and Concept Discovery
[
00:43:37] 2.1 AI-Assisted Theorem Proving and Proof Verification
[
01:01:37] 2.2 Symbolic Regression and Concept Discovery in Mathematics
[
01:11:57] 2.3 Scaling and Modularizing Mathematical Proofs
[
01:21:53] 2.4 COPRA: In-Context Learning for Formal Theorem-Proving
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01:28:22] 2.5 AI-driven theorem proving and mathematical discovery3. Formal Methods and Challenges in AI Mathematics
[
01:30:42] 3.1 Formal proofs, empirical predicates, and uncertainty in AI mathematics
[
01:34:01] 3.2 Characteristics of good theoretical computer science research
[
01:39:16] 3.3 LLMs in theorem generation and proving
[
01:42:21] 3.4 Addressing contamination and concept learning in AI systems
