OpenAI's new prototype, SearchGPT, promises to combine AI smarts with real-time web information to make search easier.
AI has achieved silver-medal standards at the International Mathematical Olympiad, raising questions about the future of mathematics and the role of AI in solving complex problems.
The reliability of AI existential risk probabilities is called into question in a thought-provoking article, challenging the authority we often assign to these forecasts and calling for more scrutiny.
Three fascinating papers from UNC Chapel Hill, Google DeepMind, and a collaboration between Caltech and NVIDIA explore advancements in theorem proving, balancing fast and slow planning, and aligning large language models with Best-of-N distillation. These papers could transform the way we approach complex problems with language models and streamline the development of LLMs.
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Timestamps:
00:34 Introduction
01:54 OpenAI Announces SearchGPT
03:15 AI achieves silver-medal standard solving International Mathematical Olympiad problems
04:55 AI existential risk probabilities are too unreliable to inform policy
06:25 Fake sponsor
08:21 LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
10:10 System-1.x: Learning to Balance Fast and Slow Planning with Language Models
12:01 BOND: Aligning LLMs with Best-of-N Distillation
13:43 Outro