A proposal for interoperable attestation objects that connect training data, evaluation labor, and AI-generated outputs across the AI supply chain.
Don’t Let AI Invert The Testing Pyramid
Thierry de Pauw: consulting CTO - IT Delivery Consultant - IT Engineer - Don’t Let AI Invert The Testing Pyramid
AI is a business model stress test
AI commoditizes anything you can specify. It can't commoditize what you have to operate.
Union.ai: Ship fast. Scale big. Orchestrate the future.
The AI development platform to go from experimentation to production faster. Orchestrate, train, and serve AI.
Meet Foundry: An AI Startup that Builds, Evaluates, and Improves AI Agents
AI native industrial data platform for manufacturing | UMH
Standardize industrial data across sites and systems to reduce costs, improve efficiency and accelerate execution. Open-source, deployed at production sites across Europe, live in weeks.
The AI "Evaluation Crisis" Is an Opportunity to Get Data Flow Right
Why the AI evaluation crisis could force a reckoning on dataset provenance, attribution, and consent.
trace-spec/ROADMAP.md at 738358dfac58047eaf689ca824f9e15008aabf36 · agentrust-io/trace-spec
TRACE: Trust Runtime Attestation and Compliance Evidence. Open attestation standard for agentic AI governance. - agentrust-io/trace-spec
Permissive-Washing in the Open AI Supply Chain: A Large-Scale Audit of License Integrity
Permissive licenses like MIT, Apache-2.0, and BSD-3-Clause dominate open-source AI, signaling that artifacts like models, datasets, and code can be freely used, modified, and redistributed. However, these licenses carry mandatory requirements: include the full license text, provide a copyright notice, and preserve upstream attribution, that remain unverified at scale. Failure to meet these conditions can place reuse outside the scope of the license, effectively leaving AI artifacts under default copyright for those uses and exposing downstream users to litigation. We call this phenomenon ``permissive washing'': labeling AI artifacts as free to use, while omitting the legal documentation required to make that label actionable. To assess how widespread permissive washing is in the AI supply chain, we empirically audit 124,278 dataset $\rightarrow$ model $\rightarrow$ application supply chains, spanning 3,338 datasets, 6,664 models, and 28,516 applications across Hugging Face and GitHub. We find that an astonishing 96.5\% of datasets and 95.8\% of models lack the required license text, only 2.3\% of datasets and 3.2\% of models satisfy both license text and copyright requirements, and even when upstream artifacts provide complete licensing evidence, attribution rarely propagates downstream: only 27.59\% of models preserve compliant dataset notices and only 5.75\% of applications preserve compliant model notices (with just 6.38\% preserving any linked upstream notice). Practitioners cannot assume permissive labels confer the rights they claim: license files and notices, not metadata, are the source of legal truth. To support future research, we release our full audit dataset and reproducible pipeline.
Cloudflare Workers AI | Open-source AI inference
Workers AI facilitates the scalable development & deployment of AI applications at the edge.
AI #180: No Longer In Charge
What we know about internal AI models hacking into real companies during cyber evaluations keeps getting worse.
trace-spec/schema/trace-claim.json at 738358dfac58047eaf689ca824f9e15008aabf36 · agentrust-io/trace-spec
TRACE: Trust Runtime Attestation and Compliance Evidence. Open attestation standard for agentic AI governance. - agentrust-io/trace-spec
Third-party cyber evaluations involving OpenAI models
OpenAI explains recent third-party cybersecurity evaluation incidents and outlines new safeguards to strengthen AI model testing and evaluation.
Models.dev — An open-source database of AI models
Models.dev is a comprehensive open-source database of AI model specifications, pricing, and features.
The AI test is now under subpoena - Sensemaker
Alabama is using consumer-protection law to demand OpenAI's internal records after its AI models broke out of a security test and compromised Hugging Face.
Labor market impacts of AI: A new measure and early evidence
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
wharton-generative-ai-labs/AIBO
An open-source tool for running controlled behavioral experiments on AI systems at scale.