Read this amazing masterpiece by google research to deepen your understanding on the chain of thoughts prompting – https://
ai.googleblog.com/2022/05/langua
ge-models-perform-reasoning-via.html
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LLMS
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Google Research on Chain of Thought Prompting Explained
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Chain of Thought Frameworks for Advanced AI Solutions
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Here are some innovative frameworks leveraging Chain of thoughts prompting to enable advanced AI solutions: 1. @langchain 2. @dust4ai Feel free to add more if you come across any and share your experience!
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Chain of Thought Prompting Advances Language Model Reasoning
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With Chain of Thought prompting, language models of sufficient scale can solve complex reasoning problems that are not solvable with standard prompting methods. It is a huge step forward in AI, making LLMs more interpretable and better equipped to tackle complex problems.
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Multi-step reasoning without model weight modification
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It mimics an intuitive thought process like humans when working through multi-step reasoning problems, and can be achieved without modifying the language model's weights or using a large training dataset.
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Chain of Thought Prompting Improves Language Model Problem Solving
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Chain of Thought prompting helps language models break down complex problems and generate more structured, organized responses. It makes problem-solving more interpretable and increases the chances of finding the correct answer.
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Chain of Thought vs Standard Prompting for Language Models
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With standard prompting, language models are given input-output pairs before predicting the answer. With Chain of Thought prompting, they are prompted to produce intermediate reasoning steps before giving the final answer.
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Chain of Thought Prompting: Teaching AI to Show Its Work
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Just like your 4th-grade math teacher made you 'show your work', the new Chain of Thought Prompting is teaching AI to break down complex problems and think more like humans! (A thread)
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ChatGPT Writing Columns: Scaling Generative AI and Data Quality
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Will #ChatGPT write @andykessler
's @WSJ column any time soon? Like all tech, it's all about how well #GenerativeAI can scale (and the quality of the #data.) #machinelearning #AI -
ChatGPT’s Vapid Responses Beyond Factual Errors
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Even when not wrong, ChatGPT can be simply vapid or banal. // @OpenAI // #AI #machinelearning #deeplearning #ChatGPT
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Track Token Usage Throughout Chain and Agent Calls
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Track token usage throughout chain/agent calls This was one of the more requested features! Very useful to be able to know how many tokens your agent/chain is using. See below thread for more information