Edge 381: Google DeepMind's PrompBreeder Self-Improves Prompts
Was this email forwarded to you? Sign up here Edge 381: Google DeepMind's PrompBreeder Self-Improves PromptsThe method combines chain of thoughts, plan and solve and evolutionary algorithms in a single mthod.
Reasoning and prompt evolution/optimization are being recognized as the next significant frontier for large language models(LLMs). We have all been dazzled by projects like AutoGPT or BabyAGI that constantly evolve prompts to achieve a specific goal in a way that resembles reasoning. Among the various strategies employed to enhance the reasoning capabilities of LLMs, one of the prominent ones is Chain-of-Thought Prompting, often hailed for its effectiveness. However, it’s worth noting that manually crafted prompt strategies tend to fall short of optimal performance. Recently, researchers from Google DeepMind unveiled PROMPTBREEDER , a self-improving prompt algorithm that uses evolutionary techniques to arrive to the best prompts for a given task. PROMPTBREEDER addresses some of the limitations of CoT with a simple and super clever algorithm that improves the prompts in a self-referential manner... Subscribe to TheSequence to read the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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The series will cover memory, action execution, planning, collaboration and many other characteristics of autonomous agents. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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NVIDIA’s GTC in Four Headlines
Sunday, March 24, 2024
Impressive AI hardware innovations and interesting software moves. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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Edge 380: Inside SELF-Discover: Google DeepMind's LLM Reasoning Method for Solving Complex Tasks
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The techniques addresses some of the limitation of prompting methods such as chain-of-thought. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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