Experimental News Clipping Site

Tag: llm

  • Cloud Blog: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/introducing-vertex-ai-rag-engine/ Source: Cloud Blog Title: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence Feedly Summary: Closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI for enterprise. Despite the incredible capabilities of generative AI for enterprise, this perceived gap may be…

  • Hacker News: Why aren’t we all serverless yet?

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    Kurt Seifried
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    Source URL: https://varoa.net/2025/01/09/serverless.html Source: Hacker News Title: Why aren’t we all serverless yet? Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides an in-depth analysis of the current state and challenges of serverless computing in cloud applications, highlighting the industry’s apprehension to fully adopt this model despite its potential benefits. The discussion…

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

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    Kurt Seifried
    in

    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…

  • Wired: AI Social Media Users Are Not Always a Totally Dumb Idea

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    Kurt Seifried
    in

    Source URL: https://www.wired.com/story/ai-social-media-users-are-not-always-a-totally-dumb-idea/ Source: Wired Title: AI Social Media Users Are Not Always a Totally Dumb Idea Feedly Summary: Meta’s AI characters users might seem useless, but fake social media users can sometimes offer valuable insights into real human behavior. AI Summary and Description: Yes Summary: Meta’s plan to introduce a significant number of artificial…

  • The Register: Additional Microprocessors Decoded: Quick guide to what AMD is flinging out next for AI PCs, gamers, business

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    Kurt Seifried
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    Source URL: https://www.theregister.com/2025/01/08/amd_ai_nvidia/ Source: The Register Title: Additional Microprocessors Decoded: Quick guide to what AMD is flinging out next for AI PCs, gamers, business Feedly Summary: Plus: A peek at Nvidia’s latest hype CES AMD unleashed a flood of CPUs at the annual CES super-conference this week in Las Vegas – chips that span the…

  • Hacker News: OmniAI (YC W24) Hiring Engineers to Build Open Source Document Extraction

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    Kurt Seifried
    in

    Source URL: https://www.ycombinator.com/companies/omniai/jobs/LG5jeP2-full-stack-engineer Source: Hacker News Title: OmniAI (YC W24) Hiring Engineers to Build Open Source Document Extraction Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the engineering roles at Omni, focused on building advanced OCR and document extraction technologies, highlighting the challenges of working with LLMs and integrating various tech…

  • Simon Willison’s Weblog: Quoting David Crawshaw

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jan/7/david-crawshaw/ Source: Simon Willison’s Weblog Title: Quoting David Crawshaw Feedly Summary: I followed this curiosity, to see if a tool that can generate something mostly not wrong most of the time could be a net benefit in my daily work. The answer appears to be yes, generative models are useful for me when…

  • Cloud Blog: Supervised Fine Tuning for Gemini: A best practices guide

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/master-gemini-sft/ Source: Cloud Blog Title: Supervised Fine Tuning for Gemini: A best practices guide Feedly Summary: Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning…

  • The Register: AI can improve on code it writes, but you have to know how to ask

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    Kurt Seifried
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    Source URL: https://www.theregister.com/2025/01/07/ai_can_write_improved_code_research/ Source: The Register Title: AI can improve on code it writes, but you have to know how to ask Feedly Summary: LLMs do more for developers who already know what they’re doing Large language models (LLMs) will write better code if you ask them, though it takes some software development experience to…