Tag: large language models
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Hacker News: Show HN: Llama 3.2 Interpretability with Sparse Autoencoders
Source URL: https://github.com/PaulPauls/llama3_interpretability_sae Source: Hacker News Title: Show HN: Llama 3.2 Interpretability with Sparse Autoencoders Feedly Summary: Comments AI Summary and Description: Yes Summary: The provided text outlines a research project focused on the interpretability of the Llama 3 language model using Sparse Autoencoders (SAEs). This project aims to extract more clearly interpretable features from…
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Hacker News: Comparison of Claude Sonnet 3.5, GPT-4o, o1, and Gemini 1.5 Pro for coding
Source URL: https://www.qodo.ai/blog/comparison-of-claude-sonnet-3-5-gpt-4o-o1-and-gemini-1-5-pro-for-coding/ Source: Hacker News Title: Comparison of Claude Sonnet 3.5, GPT-4o, o1, and Gemini 1.5 Pro for coding Feedly Summary: Comments AI Summary and Description: Yes **Summary:** This text provides a comprehensive analysis of various AI models, particularly focusing on recent advancements in LLMs (Large Language Models) for coding tasks. It assesses the…
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Simon Willison’s Weblog: OK, I can partly explain the LLM chess weirdness now
Source URL: https://simonwillison.net/2024/Nov/21/llm-chess/#atom-everything Source: Simon Willison’s Weblog Title: OK, I can partly explain the LLM chess weirdness now Feedly Summary: OK, I can partly explain the LLM chess weirdness now Last week Dynomight published Something weird is happening with LLMs and chess pointing out that most LLMs are terrible chess players with the exception of…
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Hacker News: OK, I can partly explain the LLM chess weirdness now
Source URL: https://dynomight.net/more-chess/ Source: Hacker News Title: OK, I can partly explain the LLM chess weirdness now Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text explores the unexpected performance of the GPT-3.5-turbo-instruct model in playing chess compared to other large language models (LLMs), primarily focusing on the effectiveness of prompting techniques, instruction…
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Cloud Blog: Don’t let resource exhaustion leave your users hanging: A guide to handling 429 errors
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/learn-how-to-handle-429-resource-exhaustion-errors-in-your-llms/ Source: Cloud Blog Title: Don’t let resource exhaustion leave your users hanging: A guide to handling 429 errors Feedly Summary: Large language models (LLMs) give developers immense power and scalability, but managing resource consumption is key to delivering a smooth user experience. LLMs demand significant computational resources, which means it’s essential to…
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Hacker News: From ClickOps to GitOps: The Evolution of AI App Development
Source URL: https://blog.helix.ml/p/from-clickops-to-gitops-the-evolution Source: Hacker News Title: From ClickOps to GitOps: The Evolution of AI App Development Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the evolving landscape of AI engineering, emphasizing the transition from rapid prototyping to production-ready AI applications. It highlights the growing acceptance of GPTs in business solutions…
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Simon Willison’s Weblog: TextSynth Server
Source URL: https://simonwillison.net/2024/Nov/21/textsynth-server/ Source: Simon Willison’s Weblog Title: TextSynth Server Feedly Summary: TextSynth Server I’d missed this: Fabrice Bellard (yes, that Fabrice Bellard) has a project called TextSynth Server which he describes like this: ts_server is a web server proposing a REST API to large language models. They can be used for example for text…
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Simon Willison’s Weblog: Quoting Steven Johnson
Source URL: https://simonwillison.net/2024/Nov/21/steven-johnson/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Steven Johnson Feedly Summary: When we started working on what became NotebookLM in the summer of 2022, we could fit about 1,500 words in the context window. Now we can fit up to 1.5 million words. (And using various other tricks, effectively fit 25 million words.)…
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Hacker News: Niantic announces "Large Geospatial Model" trained on Pokémon Go player data
Source URL: https://nianticlabs.com/news/largegeospatialmodel/ Source: Hacker News Title: Niantic announces "Large Geospatial Model" trained on Pokémon Go player data Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the development of a Large Geospatial Model (LGM) by Niantic, which aims to enhance spatial intelligence through machine learning. It highlights the challenges faced by…