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General Compute Raises 100 Million Dollars to Build an Inference Cloud on Nvidia's Rivals

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  • General Compute Raises 100 Million Dollars to Build an Inference Cloud on Nvidia's Rivals
Photograph of General Compute founders Finn Puklowski and Jason Goodison seated on a rooftop terrace.

General Compute has raised 100 million dollars in Series A funding co-led by Blackbird Ventures and Abstract Ventures, at an 800 million dollar post-money valuation, TechCrunch reported on October 27. The company's own announcement the same day confirms the round, with participation from Fuse Venture Partners, Village Global and others. It is a steep step up from a 60 million dollar valuation after its May seed round, and TechCrunch says a single deal with a large customer worth 100 million dollars in annual recurring revenue paved the way for it.

Where most neoclouds chased Nvidia GPUs for training, General Compute built its niche on specialized inference chips from Nvidia's rivals. It struck a 400 million dollar deal to purchase chips from SambaNova, which TechCrunch describes as the first debt financing of inference chips, and the company says that buildout is backed by a 400 million dollar debt facility from Upper90. It has since added Positron and Cerebras as suppliers. The company sells bare metal - raw servers with no software layer on top - to cloud companies that offer developers high-speed inference, and its announcement promises customers dedicated hardware or a guaranteed tokens-per-second service level without procuring or managing the infrastructure themselves.

The physical strategy is deliberately unglamorous. Instead of building huge data centers from scratch, General Compute rents space in other companies' data centers, taps smaller power sources, and converts former bitcoin-mining sites into places that run AI models. Co-founder and chief executive Finn Puklowski expects the company to deploy 75 megawatts of computing capacity in 2027, with access to about 200 megawatts of power, and the company says its first major deployments go live in the first quarter of 2027, with more than 50 megawatts in the pipeline.

The timing is the test of the thesis. CoreWeave, the publicly traded neocloud, has fallen to a 12-month stock low, and Elon Musk has predicted that more than 200 neoclouds face consolidation. Puklowski called fears of a chip-led collapse massively overstated, said demand for more compute arrives weekly, and pointed to Anthropic's bullish S-1 as settling fears for now. SambaNova chief executive Rodrigo Liang framed the real question plainly: everyone in this market is selling speed, and the question is whether you can make money doing it.

For people building with AI, the significance is distribution. Alternative chips have rarely lacked benchmarks; they have lacked an easy way to rent them at scale. Blackbird principal James Palmer, whose firm also backed inference platform Baseten, told TechCrunch that Cerebras, Positron and SambaNova all need distribution partners who can take them to scale and navigate the physical world. If General Compute makes non-Nvidia inference genuinely easy to buy, open-weight models get cheaper and faster homes, and token prices face real pressure. The caveat is capital: Puklowski admits financing will remain his full-time job, and a valuation built ahead of the first major deployments is a promise, not proof.

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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.

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

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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1Password Lets Agents Log In Without Ever Seeing the Password: The Approval Is the Product

The fastest way to make an AI agent useful is also the fastest way to make it dangerous: give it your passwords. 1Password took direct aim at that bargain on October 22 with 1Password for Agents, a system that lets a supported agent sign in to your accounts without ever seeing, handling, or storing the password itself. Chief executive Aashish Tripathi put the problem plainly in the launch statement: agents are starting to do real work on our behalf, and the old model, where you hand over a credential and hope for the best, does not work.

  • Read more about 1Password Lets Agents Log In Without Ever Seeing the Password: The Approval Is the Product

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