What if AI could not only think but also question its own thoughts? In this captivating episode, we unveil how cutting-edge techniques are teaching large language models to self-reflect, dramatically reducing those frustrating AI hallucinations where machines confidently get things wrong.Dive into the fascinating world of AI introspection with groundbreaking studies like "Chain-of-Verification Reduces Hallucination in Large Language Models" and "SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning." Discover how these advancements are making AI more accurate, reliable, and even more human-like in their reasoning.We'll journey through the innovative concepts of "ReAct: Synergizing Reasoning and Acting in Language Models" and "Reflexion: Language Agents with Verbal Reinforcement Learning," exploring how AI is learning to think, act, and evolve independently.This isn't just tech—it's the dawn of a new era where AI could transform industries, revolutionize science, and reshape our everyday lives. If you want to be at the forefront of this AI revolution, this episode is your gateway.Don't miss out on unlocking the secrets of AI's inner voice. Tune in now and be part of the future!References for main topic: [2407.01603] A Review of Large Language Models and Autonomous Agents in Chemistry [2309.11495] Chain-of-Verification Reduces Hallucination in Large Language Models [2305.11694] QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations [2308.00436] SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation [2212.01349] Nonparametric Masked Language Modeling [2208.07339] LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale [2303.17651] Self-Refine: Iterative Refinement with Self-Feedback [2210.03629] ReAct: Synergizing Reasoning and Acting in Language Models GitHub - ysymyth/ReAct: [ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models [2303.11366] Reflexion: Language Agents with Verbal Reinforcement Learning [2304.01904] REFINER: Reasoning Feedback on Intermediate Representations

Ver todos los episodios