Tag: model

Source URL: https://simonwillison.net/2025/Sep/7/is-the-llm-response-wrong-or-have-you-just-failed-to-iterate-it/#atom-everything Source: Simon Willison’s Weblog Title: Is the LLM response wrong, or have you just failed to iterate it? Feedly Summary: Is the LLM response wrong, or have you just failed to iterate it? More from Mike Caulfield (see also the SIFT method). He starts with a fantastic example of Google’s AI mode…

Wired: Psychological Tricks Can Get AI to Break the Rules

Sep 7, 2025

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Source URL: https://arstechnica.com/science/2025/09/these-psychological-tricks-can-get-llms-to-respond-to-forbidden-prompts/ Source: Wired Title: Psychological Tricks Can Get AI to Break the Rules Feedly Summary: Researchers convinced large language model chatbots to comply with “forbidden” requests using a variety of conversational tactics. AI Summary and Description: Yes Summary: The text discusses researchers’ exploration of conversational tactics used to manipulate large language model (LLM)…

Simon Willison’s Weblog: Quoting Jason Liu

Sep 6, 2025

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Source URL: https://simonwillison.net/2025/Sep/6/jason-liu/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Jason Liu Feedly Summary: I am once again shocked at how much better image retrieval performance you can get if you embed highly opinionated summaries of an image, a summary that came out of a visual language model, than using CLIP embeddings themselves. If you tell…

Simon Willison’s Weblog: Kimi-K2-Instruct-0905

Sep 6, 2025

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Source URL: https://simonwillison.net/2025/Sep/6/kimi-k2-instruct-0905/#atom-everything Source: Simon Willison’s Weblog Title: Kimi-K2-Instruct-0905 Feedly Summary: Kimi-K2-Instruct-0905 New not-quite-MIT licensed model from Chinese Moonshot AI, a follow-up to the highly regarded Kimi-K2 model they released in July. This one is an incremental improvement – I’ve seen it referred to online as “Kimi K-2.1". It scores a little higher on a…

Simon Willison’s Weblog: Why I think the $1.5 billion Anthropic class action settlement may count as a win for Anthropic

Sep 6, 2025

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Source URL: https://simonwillison.net/2025/Sep/6/anthropic-settlement/#atom-everything Source: Simon Willison’s Weblog Title: Why I think the $1.5 billion Anthropic class action settlement may count as a win for Anthropic Feedly Summary: Anthropic to pay $1.5 billion to authors in landmark AI settlement I wrote about the details of this case when it was found that Anthropic’s training on book…

The Register: If Broadcom is helping OpenAI build AI chips, here’s what they might look like

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Source URL: https://www.theregister.com/2025/09/05/openai_broadcom_ai_chips/ Source: The Register Title: If Broadcom is helping OpenAI build AI chips, here’s what they might look like Feedly Summary: Whatever happened to that Baltra thing Tan and crew were helping Apple cook up? Analysis OpenAI is allegedly developing a custom AI accelerator with the help of Broadcom in an apparent bid…

OpenAI : Why language models hallucinate

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Source URL: https://openai.com/index/why-language-models-hallucinate Source: OpenAI Title: Why language models hallucinate Feedly Summary: OpenAI’s new research explains why language models hallucinate. The findings show how improved evaluations can enhance AI reliability, honesty, and safety. AI Summary and Description: Yes Summary: The text discusses OpenAI’s research on the phenomenon of hallucination in language models, offering insights into…

Cloud Blog: Calling all devs: Join the GKE Turns 10 Hackathon and build with agentic AI

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Source URL: https://cloud.google.com/blog/topics/training-certifications/join-the-gke-turns-10-hackathon/ Source: Cloud Blog Title: Calling all devs: Join the GKE Turns 10 Hackathon and build with agentic AI Feedly Summary: For ten years, Google Kubernetes Engine (GKE) has been at the forefront of innovation, powering everything from microservices to cloud-native AI and edge computing. To honor this special birthday, we’re challenging you…

Cloud Blog: Investigate fast with AI: Gemini Cloud Assist for Dataproc & Serverless for Apache Spark

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