September sponsors-only newsletter
Simon Willison’s Weblog 1 week ago 13
September sponsors-only newsletter editions were sent to existing or new sponsors via a provided access link.
1415 summarised stories about AI Security, each linking back to the original source. Browse all topics →
Simon Willison’s Weblog 1 week ago 13
September sponsors-only newsletter editions were sent to existing or new sponsors via a provided access link.
TechCrunch 1 week ago 35 ● 16 sources
David Robinson resigned from OpenAI after writing an essay in The Atlantic saying the company’s culture is broken. He said he spent 3.5 years at OpenAI and had led the safety reports that accompanied major product launches. OpenAI said it is continuing to improve safety measures, while Robinson’s departure adds pressure for broader culture and alignment changes beyond new rules or laws.
The New Stack 1 week ago 42
Cybersecurity teams are finding that AI-driven software production and faster exploit development are widening the gap between the number of CVEs they can identify and the number they can investigate and fix. The article points to the collapsing time-to-exploit window, making long, sequential manual triage unworkable. Vulnerability management is shifting from counting spreadsheet entries by CVSS severity to continuous, contextual risk prioritization using production scanning, reachability/context, and threat-intel signals.
Fortune 27 ● 18 sources
The author argues that appointing an AI czar is not enough because repeated AI incidents and weakening public/investor trust could trigger a broader pullback that harms the U.S. economy. In 2025, Amazon, Meta, Alphabet, and Microsoft invested $400 billion in data centers alone. The proposed change is to create a fully staffed Department of AI with authority to set pre- and post-deployment risk frameworks, run audits, impose fines, and draft faster legislation to reduce risk and preserve investment confidence.
Product Hunt 1 week ago 28
Linda launched today as a free private AI coworker for Mac that performs tasks in its own browser using your folders and can be supervised step-by-step. It is available with no account and is set up to run local AI on Apple Silicon or use your own key. It lets you control specialist agents and take over actions, with prompts before it performs sensitive actions like sending, buying, deleting, or posting.
Fortune 4 ● 18 sources
AI policy researchers at GovAI said major AI labs can run powerful models with key safeguards turned off and that published safety evaluations may not match real internal usage. They pointed to Sept. 29 as the briefing date and cited that internal safeguards were not deployed, with tools failing to reliably review agent behavior. As a result, they argue for independent auditing and warn that more real-world deployment in development and testing could increase safety problems in models or codebases.
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AI’s center of gravity this week moved toward something less glamorous than headlines about “smarter” models: scaling the stuff models actually learn from. AI4Bharat and NVIDIA released Nemotron-pretraining-Indic-v1, backed by an open, GPU-accelerated synthetic data generation pipeline for 22 Indian languages. The corpus is massive—about 2.8 trillion tokens—split across 2,601.0 billion native-script tokens and 224.6 billion romanized tokens. The practical pitch is even sharper: builders can reuse not just the data, but the full prompt/quality/repair recipe, then continue-pretraining to push results on Nemotron 3.5 Super VL, with the promise that an Indic continued-pretraining stage helps benchmarks.
Read the full briefing →