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Last week, researchers from Google #Deepmind and Princeton University released a paper titled: “Tree of Thoughts: Deliberate Problem Solving with Large Language Models”, introducing a new way to overclock Large Language Models and make them solve problems like humans. In this video, I cover the key takeaways from the paper, briefly explaining what Tree of Thought promoting is and other prompting techniques like Chain of Thought, Input-Output and Chain of Thought with Self Reflection as used in Google’s PaLM 2 Technical Report, and the experiments done by research to show just how much smarter Tree of Thought is. Relevant Links and References: Tree of Thought Paper: https://arxiv.org/pdf/2305.10601.pdf Google PaLM 2 Technical Report: https://ai.google/static/documents/palm2techreport.pdf @WesRoth Explainer: https://youtu.be/BrjAt-wvEXI Google Deepmind: https://www.deepmind.com Chatpters: Intro - 0:00 What Is Tree of Thought - 0:27 What is Input-Output Prompting - 0:56 What is Chain of Thought Prompting - 1:10 What is Chain of Thought with Self Reflection - 1:37 How Does Tree of Thought Work - 2:16 Tree of Thought Experiments - 3:25 Conclusion - 5:54 Thanks for watching, have a great weekend. #AI #Trending #AIResearch #LLM #Google