Experimental News Clipping Site

Tag: Outputs

  • Hacker News: Doing data labelling in-house

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    Kurt Seifried
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    Source URL: https://www.ericbutton.co/p/data-labelling Source: Hacker News Title: Doing data labelling in-house Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the development of Yeager, a state-of-the-art AI model for air traffic control audio, and the significant effort put into in-house data labeling. It emphasizes the unique challenges of working with highly specialized…

  • Hacker News: Hallucinations in code are the least dangerous form of LLM mistakes

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Mar/2/hallucinations-in-code/ Source: Hacker News Title: Hallucinations in code are the least dangerous form of LLM mistakes Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the phenomenon of “hallucinations” in code generated by large language models (LLMs), highlighting that while such hallucinations can initially undermine developers’ confidence, they are relatively…

  • Simon Willison’s Weblog: Quoting Kellan Elliott-McCrea

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Mar/2/kellan-elliott-mccrea/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Kellan Elliott-McCrea Feedly Summary: Regarding the recent blog post, I think a simpler explanation is that hallucinating a non-existent library is a such an inhuman error it throws people. A human making such an error would be almost unforgivably careless. — Kellan Elliott-McCrea Tags: ai-assisted-programming, generative-ai,…

  • Simon Willison’s Weblog: Hallucinations in code are the least dangerous form of LLM mistakes

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Mar/2/hallucinations-in-code/#atom-everything Source: Simon Willison’s Weblog Title: Hallucinations in code are the least dangerous form of LLM mistakes Feedly Summary: A surprisingly common complaint I see from developers who have tried using LLMs for code is that they encountered a hallucination – usually the LLM inventing a method or even a full software library…

  • Simon Willison’s Weblog: llm-anthropic #24: Use new URL parameter to send attachments

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Mar/1/llm-anthropic/#atom-everything Source: Simon Willison’s Weblog Title: llm-anthropic #24: Use new URL parameter to send attachments Feedly Summary: llm-anthropic #24: Use new URL parameter to send attachments Anthropic released a neat quality of life improvement today. Alex Albert: We’ve added the ability to specify a public facing URL as the source for an image…

  • Simon Willison’s Weblog: Structured data extraction from unstructured content using LLM schemas

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Feb/28/llm-schemas/#atom-everything Source: Simon Willison’s Weblog Title: Structured data extraction from unstructured content using LLM schemas Feedly Summary: LLM 0.23 is out today, and the signature feature is support for schemas – a new way of providing structured output from a model that matches a specification provided by the user. I’ve also upgraded both…

  • Cloud Blog: Evaluate gen AI models with Vertex AI evaluation service and LLM comparator

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/evaluate-ai-models-with-vertex-ai–llm-comparator/ Source: Cloud Blog Title: Evaluate gen AI models with Vertex AI evaluation service and LLM comparator Feedly Summary: It’s a persistent question: How do you know which generative AI model is the best choice for your needs? It all comes down to smart evaluation. In this post, we’ll share how to perform…

  • Slashdot: OpenAI Rolls Out GPT-4.5

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    Kurt Seifried
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    Source URL: https://slashdot.org/story/25/02/27/2022254/openai-rolls-out-gpt-45?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: OpenAI Rolls Out GPT-4.5 Feedly Summary: AI Summary and Description: Yes Summary: OpenAI’s release of the GPT-4.5 model represents a significant enhancement in AI capabilities, particularly in natural language processing and coding efficiency. This model addresses prior issues with accuracy, aiming to reduce fabricated responses, which holds great relevance…

  • OpenAI : Introducing GPT-4.5

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    Kurt Seifried
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    Source URL: https://openai.com/index/introducing-gpt-4-5 Source: OpenAI Title: Introducing GPT-4.5 Feedly Summary: We’re releasing a research preview of GPT‑4.5—our largest and best model for chat yet. GPT‑4.5 is a step forward in scaling up pretraining and post-training. AI Summary and Description: Yes Summary: The text announces the release of a research preview for GPT-4.5, highlighting advancements in…

  • Schneier on Security: “Emergent Misalignment” in LLMs

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    Kurt Seifried
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    Source URL: https://www.schneier.com/blog/archives/2025/02/emergent-misalignment-in-llms.html Source: Schneier on Security Title: “Emergent Misalignment” in LLMs Feedly Summary: Interesting research: “Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs“: Abstract: We present a surprising result regarding LLMs and alignment. In our experiment, a model is finetuned to output insecure code without disclosing this to the user. The resulting model…