Experimental News Clipping Site

Tag: benchmark

  • Hacker News: 400x faster embeddings models using static embeddings

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    Kurt Seifried
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    Source URL: https://huggingface.co/blog/static-embeddings Source: Hacker News Title: 400x faster embeddings models using static embeddings Feedly Summary: Comments AI Summary and Description: Yes **Summary:** This blog post discusses a new method to train static embedding models significantly faster than existing state-of-the-art models. These models are suited for various applications, including on-device and in-browser execution, and edge…

  • Slashdot: ‘Mistral is Peanuts For Us’: Meta Execs Obsessed Over Beating OpenAI’s GPT-4 Internally, Court Filings Reveal

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    Kurt Seifried
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    Source URL: https://tech.slashdot.org/story/25/01/15/1715239/mistral-is-peanuts-for-us-meta-execs-obsessed-over-beating-openais-gpt-4-internally-court-filings-reveal Source: Slashdot Title: ‘Mistral is Peanuts For Us’: Meta Execs Obsessed Over Beating OpenAI’s GPT-4 Internally, Court Filings Reveal Feedly Summary: AI Summary and Description: Yes Summary: The text highlights Meta’s competitive drive to surpass OpenAI’s GPT-4, as revealed in internal communications related to an AI copyright case. Meta’s executives express a…

  • Hacker News: voyage-code-3

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    Kurt Seifried
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    Source URL: https://blog.voyageai.com/2024/12/04/voyage-code-3/ Source: Hacker News Title: voyage-code-3 Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents voyage-code-3, a new embedding model optimized for code retrieval that significantly outperforms existing models in both performance and cost-efficiency. The introduction of Matryoshka learning and advanced quantization techniques allows for reduced storage requirements without compromising…

  • Simon Willison’s Weblog: Codestral 25.01

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Jan/13/codestral-2501/ Source: Simon Willison’s Weblog Title: Codestral 25.01 Feedly Summary: Codestral 25.01 Brand new code-focused model from Mistral. Unlike the first Codestral this one isn’t (yet) available as open weights. The model has a 256k token context – a new record for Mistral. The new model scored an impressive joint first place with…

  • Hacker News: AI Engineer Reading List

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    Kurt Seifried
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    Source URL: https://www.latent.space/p/2025-papers Source: Hacker News Title: AI Engineer Reading List Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text focuses on providing a curated reading list for AI engineers, particularly emphasizing recent advancements in large language models (LLMs) and related AI technologies. It is a practical guide designed to enhance the knowledge…

  • Docker: Meet Gordon: An AI Agent for Docker

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/meet-gordon-an-ai-agent-for-docker/ Source: Docker Title: Meet Gordon: An AI Agent for Docker Feedly Summary: We share our experiments creating a Docker AI Agent, named Gordon, which can help new users learn about our tools and products and help power users get things done faster. AI Summary and Description: Yes Summary: The text discusses a…

  • Hacker News: SOTA on swebench-verified: relearning the bitter lesson

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    Kurt Seifried
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    Source URL: https://aide.dev/blog/sota-bitter-lesson Source: Hacker News Title: SOTA on swebench-verified: relearning the bitter lesson Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses advancements in AI, particularly around leveraging large language models (LLMs) for software engineering challenges through novel approaches such as test-time inference scaling. It emphasizes the key insight that scaling…

  • Simon Willison’s Weblog: microsoft/phi-4

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jan/8/phi-4/ Source: Simon Willison’s Weblog Title: microsoft/phi-4 Feedly Summary: microsoft/phi-4 Here’s the official release of Microsoft’s Phi-4 LLM, now officially under an MIT license. A few weeks ago I covered the earlier unofficial versions, where I talked about how the model used synthetic training data in some really interesting ways. It benchmarks favorably…

  • Slashdot: Nvidia’s Huang Says His AI Chips Are Improving Faster Than Moore’s Law

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    Kurt Seifried
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    Source URL: https://tech.slashdot.org/story/25/01/08/1338245/nvidias-huang-says-his-ai-chips-are-improving-faster-than-moores-law?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Nvidia’s Huang Says His AI Chips Are Improving Faster Than Moore’s Law Feedly Summary: AI Summary and Description: Yes Summary: Nvidia’s advancements in AI chip technology are significantly outpacing Moore’s Law, presenting new opportunities for innovation across the stack of architecture, systems, libraries, and algorithms. This progress will not…