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ai
1026 postsLicense Laundering Exposed Across AI Dataset-to-App Supply Chains
Study of 232,270 AI supply chains reveals systematic license laundering, with obligation-bearing licenses vanishing while permissive ones persist.
Why AI Models Perform Worse Outside English
Why do LLMs underperform outside English? Training data, tokenizer inefficiency, and instruction-tuning gaps explain the cost and accuracy divide.
One ChatGPT link could plant a rogue AI agent inside your company
OpenAI's ChatGPT agent builder had an AgentForger flaw letting a single link spawn a rogue AI agent with an employee's full access.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comSoftware Factories: Loops, Harnesses, and the Cost of Going Dark
Loops, harnesses, and factories: why dark automation in software pipelines quietly builds comprehension debt behind green tests.
Clustering Two Dell Pro Max GB10 Systems for Local AI Compute
Two Dell Pro Max GB10 systems clustered via RDMA/RoCE for 256GB of local AI memory, revealing setup quirks and firmware pitfalls.
Over 30% of new arXiv papers now read as AI-written
A 12,750-paper arXiv study finds ~32% of new submissions score as AI-written, using a false-positive-calibrated detector and detailed field breakdowns.
AI Agents for Mathematicians: Beyond Chat-Based Prompting
Why agentic harnesses like Codex outperform chat prompting for tackling open math conjectures, with durable state and strict verification labels.
Favur Evals: a public benchmark for which AI model codes best
Favur Evals is a public, vendor-independent leaderboard comparing AI models on real software engineering tasks across eight measurable dimensions.
How to Build a 3-Tier On-Device AI Concierge
Learn to set up a 3-tier AI chat widget running on the visitor's browser at zero cost.
Engineering notes: making an AI system tell the truth
How NicheIQ rebuilt its AI idea-evaluation pipeline to fix self-scoring bias, failed self-refinement loops, and reach an honest No-Go verdict.