10 ChatGPT prompts that'll make you rich: Don't forget to bookmark
LLMS
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LMSYS Arena: Anonymous Model Testing Platform Documentation
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Apparently the LMSYS arena is used for this kind of anonymous model testing quite often, they have documentation about that here:
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LLM Slop Datasets and Evaluation Secrets Newsletter
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It's been a couple of weeks since my last newsletter (which is more-or-less copied and pasted from my blog), turns out I've been writing longer bookmark descriptions recently so the newsletter ended up huge, even though I didn't think I had much content https://
simonw.substack.com/p/llm-slop-dat
asette-secrets-llm-evals
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Running LLMs locally on MacBook M1 Pro with LMStudio
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Running on Macbook M1 pro (16GB RAM) using the @LMStudioAI. If you find this useful, RT to share it with your friends. Don't forget to follow me @Saboo_Shubham_ for more such LLMs tips and tutorials. https://
x.com/Saboo_Shubham_
/status/1787308176813298128
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Deterministic Quoting: Preventing LLM Text Alterations
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I saw an interesting proposal today for avoiding those kinds of minor alterations to direct quotes: https://
mattyyeung.github.io/deterministic-
quoting
… "That’s the only way to guarantee that an LLM has not transformed text: don’t send it through the LLM in the first place." -
AI Companies Struggle with Model Selection Criteria and Feature Prioritization
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I assume the GPT2 head-to-head is literally a head-to-head for production selection. My guess is large AI companies (like OpenAI, Anthropic, Cohere, AWS, GCP, MSFT) still don’t have a sense of how important certain features (latency, hallucinations, concision, etc) are to the
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Switching AI Models: Opus vs ChatGPT Code Interpreter
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I think you misunderstood why I switched models – it wasn't because I got a bad result out of Opus, it was because I knew ChatGPT Code Interpreter could tackle the problem using tools that Opus doesn't have access to
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Premise Order Significantly Impacts LLM Reasoning Accuracy
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Featuring our first paper of the week, "Premise Order Matters in Reasoning With LLMs": https://
alphaxiv.org/abs/2402.08939
v2
…. Premise reordering can lead to accuracy dropoffs of 30% in LLMs! The authors @ryanandrewchi @xinyun_chen_ will be on alphaXiv to respond to your questions! -
OpenAI’s GPT2-Chatbot Revealed Through Rate Limit Error
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Here's confirmation that gpt2-chatbot (now renamed to "im-also-a-good-gpt-chatbot") is from OpenAI, thanks to a revealing 429 rate limit error message
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Understanding LLM Flaws: A Practical Guide to Tool Usage
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The key with all of this is to treat LLMs as flawed tools If a tool is flawed it doesn't mean it's completely useless, it means you have to understand those flaws and how to work around them LLMs have almost no documentation about how to do that, which is why I write about them