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How “reverse game theory” could keep AI agents in check

A new approach known as “reverse game theory” aims to control powerful AI models by designing systems that incentivize them to stick to the rules.

MIT Technology ReviewNov 3, 2026

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AI
MIT Technology ReviewSep 25, 2026
The Pentagon wants $30 million to build an AI-powered lie detector
A polygraph tracks body signals such as heart rate and breathing, on the theory that lying changes them. The Pentagon's proposed Polygraph+ program would score those signals with machine learning and add standoff sensing, which reads those signals without touching the person. Experts are skeptical, since a racing pulse can signal nerves as easily as a lie, and tech-based lie detection has a long record of failure.
Read original at MIT Technology Review (opens in a new tab)
AI
TechCrunchNov 3, 2026
Anthropic is working on a system to prove AI models’ identity
Called FlashProve, the system would let anyone check that an AI response really came from the model it claims to be from. Anthropic is working on an open source system to verify which AI model produced a given output, according to a blog post published Tuesday.
Read original at TechCrunch (opens in a new tab)
AI
arXivNov 3, 2026
The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer
This book provides a compact, derivation-oriented introduction to the mathematical foundations of modern generative artificial intelligence.
Read original at arXiv (opens in a new tab)
Cloud
Ars TechnicaNov 3, 2026
Ukraine’s drone strikes spur hasty Russian plans for underground data centers
Russia tries to fix exposed digital infrastructure as data center war backfires. Russian tech companies are scrambling to harden and hide their data centers underground after Ukrainian drone strikes damaged facilities housing AI supercomputers and disrupted cloud services for millions of Russian users.
Read original at Ars Technica (opens in a new tab)
AI
The DecoderNov 3, 2026
Rapid LLM development is outrunning the research meant to explain it, study finds
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.
Read original at The Decoder (opens in a new tab)

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