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Tag: reasoning

  • Tomasz Tunguz: EvoBlog: Building an Evolutionary AI Content Generation System

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    Kurt Seifried
    in

    Source URL: https://www.tomtunguz.com/evoblog-evolutionary-ai-content-generation/ Source: Tomasz Tunguz Title: EvoBlog: Building an Evolutionary AI Content Generation System Feedly Summary: One of the hardest method models to break is how disposable AI generated content is. When asking me to generate one blog post, why not just ask it to generate three, pick the best, use that as a…

  • Docker: The GPT-5 Launch Broke the AI Internet (And Not in a Good Way)

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/gpt5-api-deprecation-ai-app-failure/ Source: Docker Title: The GPT-5 Launch Broke the AI Internet (And Not in a Good Way) Feedly Summary: What That Means for Devs and AI App Companies When GPT-5 dropped, OpenAI killed off a bunch of older APIs without much warning. A whole lot of apps face-planted overnight. If your app hard-codes…

  • Slashdot: China’s Lead in Open-Source AI Jolts Washington and Silicon Valley

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    Kurt Seifried
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    Source URL: https://news.slashdot.org/story/25/08/13/1536215/chinas-lead-in-open-source-ai-jolts-washington-and-silicon-valley?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: China’s Lead in Open-Source AI Jolts Washington and Silicon Valley Feedly Summary: AI Summary and Description: Yes Summary: The text highlights China’s advancements in open-source AI, particularly how their leading model surpasses that of OpenAI, raising significant concerns among U.S. policymakers and the tech industry. This shift emphasizes the…

  • Docker: Building AI agents made easy with Goose and Docker

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/building-ai-agents-with-goose-and-docker/ Source: Docker Title: Building AI agents made easy with Goose and Docker Feedly Summary: Building AI agents can be a complex task. But it also can be a fairly simple combination of answers to the following questions:  What is the AI backend that powers my intelligent fuzzy computation? What tools do you…

  • Slashdot: LLMs’ ‘Simulated Reasoning’ Abilities Are a ‘Brittle Mirage,’ Researchers Find

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    Kurt Seifried
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    Source URL: https://slashdot.org/story/25/08/11/2253229/llms-simulated-reasoning-abilities-are-a-brittle-mirage-researchers-find?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: LLMs’ ‘Simulated Reasoning’ Abilities Are a ‘Brittle Mirage,’ Researchers Find Feedly Summary: AI Summary and Description: Yes Summary: Recent investigations into chain-of-thought reasoning models in AI reveal limitations in their logical reasoning capabilities, suggesting they operate more as pattern-matchers than true reasoners. The findings raise crucial concerns for industries…

  • Simon Willison’s Weblog: LLM 0.27, the annotated release notes: GPT-5 and improved tool calling

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/11/llm-027/ Source: Simon Willison’s Weblog Title: LLM 0.27, the annotated release notes: GPT-5 and improved tool calling Feedly Summary: I shipped LLM 0.27 today, adding support for the new GPT-5 family of models from OpenAI plus a flurry of improvements to the tool calling features introduced in LLM 0.26. Here are the annotated…

  • Simon Willison’s Weblog: Qwen3-4B-Thinking: "This is art – pelicans don’t ride bikes!"

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/10/qwen3-4b/#atom-everything Source: Simon Willison’s Weblog Title: Qwen3-4B-Thinking: "This is art – pelicans don’t ride bikes!" Feedly Summary: I’ve fallen a few days behind keeping up with Qwen. They released two new 4B models last week: Qwen3-4B-Instruct-2507 and its thinking equivalent Qwen3-4B-Thinking-2507. These are relatively tiny models that punch way above their weight. I’ve…

  • Simon Willison’s Weblog: Quoting Sam Altman

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/10/sam-altman/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Sam Altman Feedly Summary: the percentage of users using reasoning models each day is significantly increasing; for example, for free users we went from