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Today on IMPULSE: Anthropic signs a reported $200 billion deal with Google Cloud for roughly five gigawatts of capacity, and Larry Fink tells investors compute is heading toward futures markets. Coinbase cuts 14% of its workforce and hands the press an AI rationale, even though revenue and crypto cycle math tell a more familiar story. Elon Musk's xAI rents the entire Colossus 1 cluster — about 220,000 GPUs — to Anthropic, the same company Musk spent the year suing.
Then we move offstage. California posts the first implementation roles for SB 53, and the job descriptions tell you what frontier-AI regulation will actually look like. The FDA rolls out Elsa 4.0 across reviewer workflows and starts consolidating decades of inspection and adverse-event data into a single AI-ready repository. A new benchmark from Mount Sinai puts frontier models at 46% on real-world EHR physician tasks. Chinese labs Kimi and DeepSeek raise at $20-plus and $45 billion valuations with state capital in the mix. And a new paper from a Stanford-affiliated team documents what they call the Compliance Trap — measurable metacognitive degradation in models pushed under adversarial pressure.
One throughline: capacity, money, and oversight are arriving from very different directions, on very different clocks.
By Marcus VorwallerToday on IMPULSE: Anthropic signs a reported $200 billion deal with Google Cloud for roughly five gigawatts of capacity, and Larry Fink tells investors compute is heading toward futures markets. Coinbase cuts 14% of its workforce and hands the press an AI rationale, even though revenue and crypto cycle math tell a more familiar story. Elon Musk's xAI rents the entire Colossus 1 cluster — about 220,000 GPUs — to Anthropic, the same company Musk spent the year suing.
Then we move offstage. California posts the first implementation roles for SB 53, and the job descriptions tell you what frontier-AI regulation will actually look like. The FDA rolls out Elsa 4.0 across reviewer workflows and starts consolidating decades of inspection and adverse-event data into a single AI-ready repository. A new benchmark from Mount Sinai puts frontier models at 46% on real-world EHR physician tasks. Chinese labs Kimi and DeepSeek raise at $20-plus and $45 billion valuations with state capital in the mix. And a new paper from a Stanford-affiliated team documents what they call the Compliance Trap — measurable metacognitive degradation in models pushed under adversarial pressure.
One throughline: capacity, money, and oversight are arriving from very different directions, on very different clocks.