Experimental News Clipping Site

Tag: user feedback

  • Scott Logic: The Feature Fallacy

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    Kurt Seifried
    in

    Source URL: https://blog.scottlogic.com/2025/05/22/the-feature-fallacy.html Source: Scott Logic Title: The Feature Fallacy Feedly Summary: Features or Foundations. Where do you start. What are the pros and cons of building fast or building the blocks to build on. AI Summary and Description: Yes **Summary:** The text delves into the strategic tension between prioritizing feature development and investing in…

  • The Register: Stargate to land its first offshore datacenters in the United Arab Emirates

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    Kurt Seifried
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    Source URL: https://www.theregister.com/2025/05/23/stargate_uae/ Source: The Register Title: Stargate to land its first offshore datacenters in the United Arab Emirates Feedly Summary: Says it will serve half of humanity but testing that claim produced a hilarious ChatGPT fail Stargate, the Open AI led consortium that aims to build giant AI datacenters, has picked the United Arab…

  • Simon Willison’s Weblog: Expanding on what we missed with sycophancy

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/May/2/what-we-missed-with-sycophancy/ Source: Simon Willison’s Weblog Title: Expanding on what we missed with sycophancy Feedly Summary: Expanding on what we missed with sycophancy I criticized OpenAI’s initial post about their recent ChatGPT sycophancy rollback as being “relatively thin" so I’m delighted that they have followed it with a much more in-depth explanation of what…

  • Simon Willison’s Weblog: Quoting Mark Zuckerberg

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/May/1/mark-zuckerberg/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Mark Zuckerberg Feedly Summary: You also mentioned the whole Chatbot Arena thing, which I think is interesting and points to the challenge around how you do benchmarking. How do you know what models are good for which things? One of the things we’ve generally tried to…

  • Simon Willison’s Weblog: Quoting Ted Sanders, OpenAI

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Apr/17/ted-sanders/ Source: Simon Willison’s Weblog Title: Quoting Ted Sanders, OpenAI Feedly Summary: Our hypothesis is that o4-mini is a much better model, but we’ll wait to hear feedback from developers. Evals only tell part of the story, and we wouldn’t want to prematurely deprecate a model that developers continue to find value in.…

  • The Cloudflare Blog: Sequential consistency without borders: how D1 implements global read replication

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    Kurt Seifried
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    Source URL: https://blog.cloudflare.com/d1-read-replication-beta/ Source: The Cloudflare Blog Title: Sequential consistency without borders: how D1 implements global read replication Feedly Summary: D1, Cloudflare’s managed SQL database, announces read replication beta. Here’s a deep dive of the read replication implementation and how your queries can remain consistent across all regions. AI Summary and Description: Yes Summary: The…

  • Docker: Run Gemma 3 with Docker Model Runner: Fully Local GenAI Developer Experience

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    Kurt Seifried
    in

    Source URL: https://www.docker.com/blog/run-gemma-3-locally-with-docker-model-runner/ Source: Docker Title: Run Gemma 3 with Docker Model Runner: Fully Local GenAI Developer Experience Feedly Summary: Explore how to run Gemma 3 models locally using Docker Model Runner, alongside a Comment Processing System as a practical case study. AI Summary and Description: Yes Summary: The text discusses the growing importance of…

  • Simon Willison’s Weblog: Pydantic Evals

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Apr/1/pydantic-evals/#atom-everything Source: Simon Willison’s Weblog Title: Pydantic Evals Feedly Summary: Pydantic Evals Brand new package from the Pydantic AI team which directly tackles what I consider to be the single hardest problem in AI engineering: building evals to determine if your LLM-based system is working correctly and getting better over time. The feature…

  • Slashdot: Bloomberg’s AI-Generated News Summaries Had At Least 36 Errors Since January

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    Kurt Seifried
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    Source URL: https://news.slashdot.org/story/25/03/30/1946224/bloombergs-ai-generated-news-summaries-had-at-least-36-errors-since-january?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Bloomberg’s AI-Generated News Summaries Had At Least 36 Errors Since January Feedly Summary: AI Summary and Description: Yes Summary: The text discusses Bloomberg’s experimentation with AI-generated summaries for journalism, highlighting both the potential benefits and challenges faced by the implementation of such technology. This case illustrates the growing trend…