Jake Brukhman argues distributed GPU networks can challenge Big Tech's grip on artificial intelligence, and he's putting serious capital behind the thesis
The AI arms race has a concentration problem. A handful of tech giants control the most powerful models, the largest GPU clusters, and the data pipelines feeding them. Jake Brukhman, founder and CEO of CoinFund, thinks decentralized networks built on distributed GPU resources can serve as a meaningful counterbalance.
CoinFund has raised $158 million to back crypto and AI startups, with a portfolio that reads like a who’s who of decentralized compute projects.
The case for distributed GPUs #
Brukhman’s argument is that consumer and data-center GPUs sitting idle around the world can be aggregated into networks powerful enough to train advanced AI models collaboratively. At the Theta Capital Legends4Legends conference, Brukhman presented this vision in detail, emphasizing technological advances that have moved decentralized model training from a speculative concept to an emerging reality. His prediction: a full-blown race in decentralized AI training is coming, and it will happen sooner than most people expect.
Where CoinFund is placing its bets #
Prime Intellect, a project focused on building an open-source decentralized AI stack, secured $5.5 million in seed funding co-led by CoinFund in April 2024. The company later raised an additional $15 million.
Pluralis Research raised $7.6 million in a seed round co-led by CoinFund and Union Square Ventures in 2025.
Then there’s Gensyn, a decentralized training network that operates with an ERC-20 token called $AI. The token serves multiple functions within the network: verification, staking, payments, and governance. It has a total supply of 10 billion tokens.
Why this matters for the crypto market #
For crypto investors specifically, decentralized AI projects introduce a new category of token utility. Rather than tokens that derive value primarily from speculation or DeFi mechanics, AI-related tokens are tied to real compute workloads. A token used to pay for GPU time on a decentralized network has demand driven by actual resource consumption, not just trading volume. Brukhman founded CoinFund in 2015, originally as a Slack group for early decentralization advocates.
For investors watching this space, the key metric to track isn’t token prices. It’s actual compute utilization on these decentralized networks. If projects like Prime Intellect and Gensyn can demonstrate that distributed GPU clusters are training models at scale, the investment thesis moves from speculative to structural. Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our