primeintellect

Prime Intellect raises $130M in a Series A funding round

#PrimeIntellect secures $130M in a Series A funding round led by Radical Ventures, with participation from NVIDIA Ventures, Intel Capital, and Dell Technologies Capital. The funding round brings Prime Intellect's total funds raised to $150.5M.

Prime Intellect is a decentralized #AI infrastructure platform building an open superintelligence stack with tools for #AIagent development, compute, reinforcement learning, and deployment.

👉 x.com/PrimeIntellect/status/2074899489190785419

When both Nvidia and Intel Capital place bets on a “decentralized AI training” project, that’s a signal worth pausing to look at twice.

Prime Intellect has just completed a $13 million Series A funding round. In the investor lineup are both NVIDIA and Intel Capital—two powerhouses with the most clout and resources in terms of computing power—yet they chose to back a team that wants to decentralize training capabilities.

What it’s doing is very straightforward: it is connecting cross-cluster distributed training so that researchers, compute providers, and funders can collaborate to train cutting-edge open-source models, while also sharing ownership of the models and the resulting returns. In other words, it’s no longer a few big companies monopolizing closed-source models; instead, the people who contribute GPUs, write the code, and provide the funding collectively hold an open AI.

What I care about most is the motives of the big players. By backing decentralized training, Nvidia—at least to some extent—is endorsing the path of “networked computing power.” In the future, the idle GPUs scattered around the world could genuinely be organized to run trillion-parameter training tasks.

The narrative in the DeAI track—from “issuing tokens to ride on concepts” to “running and validating the training pipeline”—is quietly shifting gears.

#DeAI #去中心化AI #PrimeIntellect

Prime Intellect betting on decentralized AI training: this hard-core path—break computational power, capital, and code out across global nodes to run in coordinated collaboration, so that large models are no longer the exclusive property of a few major giants.

A Series round of $13 million—the lineup of investors speaks volumes: NVIDIA and Intel Capital both stepped in. Two chip leaders co-backed a decentralized training team, which in itself is a statement.

The highlight lies here: if cross-cluster distributed training can truly work for open models, and participants share ownership and returns according to their contributions, then the logic of how AI value is distributed must be rewritten. The remaining challenges are communication overhead and incentive mechanisms—whether engineers can handle mainnet-level pressure is the deciding line between it being mere narrative or real infrastructure.

This decentralized AI track is worth ongoing follow-up.

#DeAI #去中心化算力 #PrimeIntellect

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