Why AI Quality Assurance Belongs In The Boardroom
www.forbes.com — AI may democratize intelligence, but it will not automatically democratize trust.
Stanford University
Stanford’s AI100 Report Examines The Cost Of AI Progress
Stanford's century-long AI study admits it's already out of date
The Register — Five-year review charts upheaval in work, science, and public life – with little consensus on who's in control
The 4 Dimensions Of Scoring AI Risk
www.forbes.com — Leaders should be able to confirm whether AI passes these four checkpoints before giving the green light on AI implementation.
A Stanford Study Just Explained When to Use AI for Research—and When Not to
[One Million AI Engineer Special] How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco
Latent Space — What do you assign when a coding agent can finish last year’s homework in one prompt? In the second run of Stanford’s CS146S, Mihail Eric brought open-source maintainers into the course. Students have to learn an unfamiliar repo, propose a change, and ...
Your AI Agent May Create a Business Decision Nobody Actually Ordered
AI learns to predict the world without ever seeing it
Tech Xplore — Almost every artificial intelligence system we know begins in the same way: it is exposed to vast amounts of information from the real world—books, websites, images and recordings—and trained to identify patterns within it. A new study involving researchers from Tel Aviv University and Stanford University raises another possibility: Can a system develop general learning capabilities even when all the data it trains on is generated entirely from scratch within the system itself?
A YC startup is putting $1M behind five unsolved materials science problems for AI
TechCrunch — Discovered Materials, a months-old YC startup that uses AI to find chip materials, is offering $200,000 for each solution to five open materials science problems.
Rapid LLM development is outrunning the research meant to explain it, study finds
The Decoder — Stanford researchers tested 50 widely cited claims about LLMs against 20 current models. 44 percent of the findings are already "expired," and another 34 percent have weakened significantly. The average lifespan is just 15.7 months. Claims about what models can't do expire fastest.
What CLOs Need To Know About Defending Decisions With AI Data
Can mathematicians count on AI? A Stanford professor weighs in
The San Francisco Standard — Ravi Vakil advises OpenAI, Anthropic, and Google DeepMind on math. He talks about the promise and the risks of the two worlds colliding.
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