Now on Poe: Command R and Command R+ from Cohere! These bots excel at understanding complex questions and long conversations, providing detailed answers in over 10 languages. They can also search the web for the latest information to enhance their responses. (1/2)
PROMPT ENGINEERING
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LLMs Intelligence: Argument Evaluation and Personalized Appeal Prediction
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LLMs are already pretty intelligent; they can distinguish between strong and weak arguments, predict stances based on beliefs and demographic characteristics, and determine the appeal of an argument to an individual based on their traits. The paper below shows that LLMs perform
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AI Writing Excellence and Software Operating Agent Development
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Two main things: 1. We are the best AI for writing and writing-related tasks. Our models write naturally, have access to up-to-date info, can research + cite sources. + lots more. 2. We’ve been developing an AI agent that can operate software to get tasks done for you.
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ChatGPT keyboard shortcut extension for writing, coding, and blog posts
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9. CMJ
— God of Prompt (@godofprompt) 24 avril 2024
Improve your writing, get answers to coding questions & generate blog posts with ChatGPT keyboard shortcut.
Install this Chrome extension and press Cmd/Alt + J!https://t.co/REDEeFm4pg pic.twitter.com/QHCFTtpwmB9. CMJ Improve your writing, get answers to coding questions & generate blog posts with ChatGPT keyboard shortcut. Install this Chrome extension and press Cmd/Alt + J! https://
cmdj.app -
Files-to-Prompt tool for LLM context processing
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I built my own tool for that: files-to-prompt to chuck all of the files in a directory into a single stream, then I pipe that to my LLM tool and send it to a large context model like Claude 3 Opus to ask questions about it
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GPT-3 and Copilot Examples for URL Guessing and Testing
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I have a few examples in https://t.co/aymMPeMsdG and https://t.co/n38dNNX8Vw pic.twitter.com/jPEzopNALi
— Simon Willison (@simonw) 23 avril 2024I have a few examples in https://
til.simonwillison.net/gpt3/guessing-
amazon-urls
… and https://
til.simonwillison.net/gpt3/writing-t
est-with-copilot
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Detecting Dangerous Behavior in Sleeper Agent Models
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This simple approach works here because prompts that induce dangerous behavior are salient in the internal state of these sleeper agent models. This is likely due to the way they were fine-tuned. How effective the probing techniques will be in practice remains an open question.
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Fine-tuning Primer: Guide to Timing, Budget, Data, and Tools
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Check out this informative primer on all things #finetuning from Daniel Porras Reyes at @flybridge
. Topics: When's the right time to fine-tune Budget / resource considerations Prepping data for fine-tuning Choosing the right tool Check it out: https://
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AI Model Context Mechanism with Debug Tool Visibility
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Yeah, it has a very neat mechanism where it includes likely snippets from nearby files in the context when it completes – you can run debug tools to see exactly what it's doing
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Building Intuition for Better Copilot Results
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This is exactly my experience – there's so much depth to getting good results out of Copilot, and like so many things LLM it comes down to building up a weird, almost subconscious intuition about how best to use it