Can Crypto Help Solve AI’s Compute Crisis?

Artificial intelligence was supposed to democratize access to knowledge. Instead, it may be creating a new class divide.

As AI models become more powerful, the limiting factor is no longer intelligence. It's compute — the raw processing power required to train, run, and deploy increasingly sophisticated systems. And just like the early days of Bitcoin mining, access to that compute is becoming concentrated in the hands of a few giant players.

"With AI, the biggest issue now is compute," Cysic Head of Marketing Annie Xie told Coinage. "The big players in this space, we all know them. They kind of own everything."

The observation echoes a growing concern. The AI boom has triggered an arms race among hyperscalers including Microsoft, Google, Amazon and Meta, all competing to secure Nvidia chips, build data centers and lock up future computing capacity. Meanwhile, startups and independent developers increasingly find themselves competing for everything else. For Xie, the parallels to crypto are obvious.

"When we think about the development of AI, we have to ask ourselves who's going to get left behind," she said. "It's the regular person."

The comparison is striking because crypto has already lived through a similar evolution. Bitcoin was initially envisioned as a decentralized network anyone could participate in from a personal computer. Over time, mining mostly became dominated by specialized hardware and industrial-scale operations.

That challenge has created a growing category of projects attempting to decentralize access to computing resources. Rather than relying solely on centralized data centers, these networks seek to aggregate unused compute from individuals and smaller operators into distributed marketplaces. Cysic is one of the latest entrants pursuing that vision.

The company began by building infrastructure around zero-knowledge proofs, a cryptographic technique increasingly important for scaling blockchains. But it has since expanded into AI infrastructure, offering agent hosting, inference services, developer tools and hardware products designed to contribute computing power back into its network.

The project recently launched the Cysic DogeBox 1, a compact, consumer-grade node that seeks to leverage the upside of Dogecoin mining combined with Cysic's verifiable compute network.

"The main theme that we're trying to push is that everyone should be able to have access to compute," Xie said. "Whether that's to be in crypto or to use AI or to build something of their own."

That vision extends beyond simply providing hardware. Cysic recently launched CyOps, an AI development environment designed to simplify the process of building applications using natural language commands instead of traditional coding.

For many users, accessibility may prove just as important as raw computing power.

AI tools have become dramatically more capable over the past two years, but they often remain difficult to use effectively. Prompting models, validating outputs and stitching together workflows can quickly become overwhelming for non-technical users.

"If you can't prompt well, if you don't know how to look for quality, if you can't verify anything, AI is not really going to help you," Xie argued.

The challenge is particularly apparent in the emerging market for AI agents. While the concept of autonomous software assistants has attracted enormous attention, deploying and maintaining them often requires technical expertise that most users lack.

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