Tag: large language models

  • Cloud Blog: What’s new with BigQuery AI and ML?

    Source URL: https://cloud.google.com/blog/products/data-analytics/bigquery-adds-new-ai-capabilities/ Source: Cloud Blog Title: What’s new with BigQuery AI and ML? Feedly Summary: At Next ’25, we introduced several new innovations within BigQuery, the autonomous data to AI platform. BigQuery ML provides a full range of AI and ML capabilities, enabling you to easily build generative AI and predictive ML applications with…

  • Cloud Blog: The dawn of agentic AI in security operations

    Source URL: https://cloud.google.com/blog/products/identity-security/the-dawn-of-agentic-ai-in-security-operations-at-rsac-2025/ Source: Cloud Blog Title: The dawn of agentic AI in security operations Feedly Summary: The daily grind of sifting through endless alerts and repetitive tasks is burdening security teams. Too often, defenders struggle to keep up with evolving threats, but the rapid pace of AI advancement means it doesn’t have to be…

  • Slashdot: Could a ‘Math Genius’ AI Co-author Proofs Within Three Years?

    Source URL: https://science.slashdot.org/story/25/04/28/0255248/could-a-math-genius-ai-co-author-proofs-within-three-years?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Could a ‘Math Genius’ AI Co-author Proofs Within Three Years? Feedly Summary: AI Summary and Description: Yes Summary: The text discusses DARPA’s new project, expMath, which aims to accelerate mathematical research through AI innovation. It highlights the challenges of current AI capabilities in complex mathematical tasks and emphasizes the…

  • Simon Willison’s Weblog: Quoting Eliot Higgins, Bellingcat

    Source URL: https://simonwillison.net/2025/Apr/26/elliot-higgins/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Eliot Higgins, Bellingcat Feedly Summary: We’ve been seeing if the latest versions of LLMs are any better at geolocating and chronolocating images, and they’ve improved dramatically since we last tested them in 2023. […] Before anyone worries about it taking our job, I see it more…

  • Simon Willison’s Weblog: Exploring Promptfoo via Dave Guarino’s SNAP evals

    Source URL: https://simonwillison.net/2025/Apr/24/exploring-promptfoo/#atom-everything Source: Simon Willison’s Weblog Title: Exploring Promptfoo via Dave Guarino’s SNAP evals Feedly Summary: I used part three (here’s parts one and two) of Dave Guarino’s series on evaluating how well LLMs can answer questions about SNAP (aka food stamps) as an excuse to explore Promptfoo, an LLM eval tool. SNAP (Supplemental…

  • Slashdot: Google AI Fabricates Explanations For Nonexistent Idioms

    Source URL: https://tech.slashdot.org/story/25/04/24/1853256/google-ai-fabricates-explanations-for-nonexistent-idioms?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google AI Fabricates Explanations For Nonexistent Idioms Feedly Summary: AI Summary and Description: Yes Summary: The text discusses flaws in large language models (LLMs) as demonstrated by Google’s search AI generating plausible explanations for nonexistent idioms. This highlights the risks associated with AI-generated content and the tendency of LLMs…

  • The Register: AI training license will allow LLM builders to pay for content they consume

    Source URL: https://www.theregister.com/2025/04/24/uk_publishing_body_launches_ai/ Source: The Register Title: AI training license will allow LLM builders to pay for content they consume Feedly Summary: UK org backing it promises ‘legal certainty’ for devs, money for creators… but is it too late? A UK non-profit is planning to introduce a new licensing model which will allow developers of…

  • Simon Willison’s Weblog: llm-fragment-symbex

    Source URL: https://simonwillison.net/2025/Apr/23/llm-fragment-symbex/#atom-everything Source: Simon Willison’s Weblog Title: llm-fragment-symbex Feedly Summary: llm-fragment-symbex I released a new LLM fragment loader plugin that builds on top of my Symbex project. Symbex is a CLI tool I wrote that can run against a folder full of Python code and output functions, classes, methods or just their docstrings and…