AI models fail at robot control without human-designed building blocks but agentic scaffolding closes the gap
A new framework from Nvidia, UC Berkeley, and Stanford systematically tests how well AI models can control robots through code. The findings: without human-designed abstractions, even top models fail, but methods like targeted test-time compute scaling closes the gap.<br /> The article AI models fail at robot control without human-designed building blocks but agentic scaffolding closes the gap appeared first on The Decoder. [...]
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Nvidia's agentic AI stack is the first major platform to ship with security at launch, but governance gaps remain
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An AI agent rewrote a Fortune 50 security policy. Here's how to govern AI agents before one does the same.
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The Agentic Reckoning: Enterprise AI organizations have a runtime problem, not a model problem — and most are building the wrong solution
In Q1 2026, VentureBeat's Pulse Research surfaced the “Governance Mirage”: the gap between the governance org charts enterprises had drawn and the control layers they had actually built. Fort [...]
The robots we saw at CES 2026: The lovable, the creepy and the utterly confusing
CES always has its share of attention-grabbing robots. But this year in particular seemed to be a landmark year for robotics. The advancement in AI technology has not only given robots better “brain [...]
Most enterprises can't stop stage-three AI agent threats, VentureBeat survey finds
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]