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Ai Industry News

Nvidia's Flora Labels Robot Video for 72 Cents an Hour, Not 88 Dollars

Photograph of two humanoid robots, one working alongside a woman in a kitchen and another wearing a white Nvidia hard hat at a work station

Nvidia's GEAR robotics lab has open-sourced Flora, the data engine it uses to train its GR00T humanoid robot models, and the headline number is hard to ignore. Reporting by The Decoder on October 25, drawing on Nvidia's research paper, puts Flora's cost at about 72 cents to label one hour of robot video, compared with roughly 88.49 dollars for OpenAI's GPT-6 Astra. The models are available on Hugging Face, and Nvidia says the system already annotates up to 200,000 hours of video a day across 512 GB300 GPUs in its own training pipeline.

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Apollo Says AI Has Paid Off Nowhere Outside Tech: The S&P 493 Are Still Flat

Photograph of the carved stone facade of the New York Stock Exchange building with its gold Stock Exchange lettering.

Apollo Global Management's chief economist has put a number on the suspicion many finance chiefs have been voicing privately. In a note published October 24, Torsten Slok argued that artificial intelligence has delivered, in his words, zero financial payoff to corporate America outside of tech. TechCrunch reported the note on October 25. His test is deliberately plain: strip the Magnificent Seven out of the S&P 500, and the remaining 493 companies show flat profit margins, flat revenue per worker, and no sign in the productivity data that AI is moving the needle yet.

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Anthropic Says One Agent Beats Many: Fold Your Subagents Back Into the Loop

Photograph of Dario Amodei.

Anthropic is telling enterprise builders to do the unfashionable thing: use fewer agents. In guidance published October 22 from its Applied AI team, and reported widely on October 25, the company said that across several enterprise deployments a single agent that loads skills and tools only when needed frequently beat both a one-prompt-for-everything design and a fleet of specialised subagents on quality, and often cost less and ran faster. In one comparison the single-agent setup ran about twice as fast as the multi-agent version it replaced.

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