Great example of the importance of few shot examples How do you get these examples? One way is to have a proper logging + feedback collection service set up You can even automate the "feedback" -> "few shot example" loop – see "self learning GPTs" https://
youtube.com/watch?v=OnQQeW
Ewzyw
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AGENTS
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Few-Shot Learning: Logging, Feedback, and Self-Learning GPTs
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Cohere Transforms Insurance with AI Summarization and Knowledge Assistants
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Cohere is transforming the insurance sector, offering time-saving solutions like large context summarization and knowledge assistants that automate operations and customer interactions. Learn more:
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Current Approaches to AGI: Reasoning and Advanced Methods Discussion
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Lets’s meet for a @e180labs braindate at #GTC2024: Are current approaches sufficient to get us to AGI? Lets discuss reasoning, NCAs, Q*… @
@NVIDIA https://
a.e180.co/l/CmUyiD/ #braindate # (03/21, 1pm L1) -
Anthropic Claude Prepares Hypnodrones Release
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Anthropic’s Claude is preparing to release the hypnodrones https://t.co/7suEGvdUJ3
— Joscha Bach (@Plinz) 21 mars 2024Anthropic’s Claude is preparing to release the hypnodrones
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Self-Learning GPTs: Improving Applications Through Feedback
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YouTube Video: Self Learning GPTs Using Feedback to Improve Your Application Concrete example: easily build a chatbot to generate tweets in a particular style without direct prompting!
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Making Individual Prompt Development Accessible and Measurable
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Not exactly haha. I just want to make the development of individual prompts more accessible and measurable. The real work is stringing these prompts together to make a system like this one.
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LangGraph Quickstarts: Easier Multi-Agent App Development
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New LangGraph Quickstarts We've made it easier to get started building multi-agent apps with LangGraph and LangGraph.js with revamped quickstarts! Try them out, and let us know what you think! And stay tuned – we have a lot of exciting things coming around LangGraph.
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claude-prompt-engineer: AI Agent Creates Optimal Claude Prompts
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Introducing `claude-prompt-engineer` ✍️
— Matt Shumer (@mattshumer_) 20 mars 2024
An agent that creates optimal Claude 3 prompts.
Just describe a task, and a chain of AIs will:
– Generate many possible prompts
– Test them in a ranked tournament
– Return the best one
And it's open-source: https://t.co/nrivU2BWmn pic.twitter.com/ruxDCrq1DLIntroducing `claude-prompt-engineer` An agent that creates optimal Claude 3 prompts. Just describe a task, and a chain of AIs will:
– Generate many possible prompts
– Test them in a ranked tournament
– Return the best one And it's open-source: https://
github.com/mshumer/gpt-pr
ompt-engineer
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Claude Constrained Agent Chains Calls for Optimal Prompts
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`claude-prompt-engineer` is a constrained agent — meaning its behavior is highly-controlled, leading to better results than open-ended agents. It chains together lots of Claude 3 calls that work together to find the best possible prompt.
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Learning LLM Skills with AI Tutor Cosmo
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2. Engineering Output Size with LLMs
— Rowan Cheung (@rowancheung) 20 mars 2024
Being able to run prompts and get feedback directly from Cosmo (the AI tutor Corgi) makes learning really fun.
You have an LLM helping you learn how to work better with LLMs! 🤯 pic.twitter.com/KYUOnlklS02. Engineering Output Size with LLMs Being able to run prompts and get feedback directly from Cosmo (the AI tutor Corgi) makes learning really fun. You have an LLM helping you learn how to work better with LLMs!