Aethir’s Mark Rydon On The DePIN Boom, Enterprise‑Grade GPUs, And Why Decentralized Compute Is Poised To Surge
In Brief
Decentralized GPU networks like Aethir are emerging as cost-effective, globally distributed alternatives to meet surging AI compute demand and support enterprise-grade, blockchain-compatible infrastructure.
The global AI compute landscape is experiencing unprecedented demand. According to Bridgewater Associates, major US tech companies are projected to invest about $650 billion in AI infrastructure in 2026. Market forecasts show the data center GPU market expanding fast, with projections that the global GPU segment — valued at over $125 billion in 2025 — could grow at a 20%+ CAGR through the decade as AI models grow more complex and pervasive.
Within this compute boom, decentralized physical infrastructure networks (DePINs) — particularly in GPU compute — are emerging as cost‑effective alternatives. Recent sector analysis suggests DePIN projects can offer GPU hours at a fraction of centralized cloud pricing, while addressing regional latency and supply bottlenecks.
In an interview with MPost, Mark Rydon, co-founder of Aethir, shared the company’s journey to a leading provider of enterprise-grade, decentralized GPU compute. He described how Aethir has built a globally distributed, low-latency network capable of supporting the surging demand for AI training and inference, and unveiled insights on operating a permissionless, enterprise-ready infrastructure.
Beyond Aethir’s own evolution the expert provided an outlook on the broader DePIN and AI compute markets, highlighting the unprecedented growth in global GPU demand, the emerging role of agentic AI, and how blockchain-based payment rails could reshape autonomous compute adoption.
What is Aethir’s origin story, and what drove the shift from cloud gaming to AI compute?
The original focus of Aethir, the first problem we chose to tackle, was that there are billions of gamers worldwide, and the vast majority play on mobile devices. In Western markets, we think of console and PC gaming, but globally most gamers use low-end phones, meaning much of today’s high-end gaming content is inaccessible due to hardware limits. Cloud gaming pioneered by Google could offload all game processing to the cloud, letting any device run any game and enabling studios to reach billions more players.
We realized that if we could reduce the cost of scaling this solution to a point where it made sense for gaming companies to pay for the infrastructure, it would be a compelling model. Our solution was to decentralize access to compute, aggregating GPUs provided by others. In practice, this meant building massive GPU capacity to support both gaming and AI while ensuring flawless, low-latency service, since gamers—and gaming companies—demand near-perfect performance.
We had to build an enterprise-focused GPU solution that had never existed before, creating a network of enterprise-ready GPUs at a time when few others had done so. Then ChatGPT was released, AI companies quickly hit GPU limits, and we started receiving emails asking, “You have GPUs, right? Can we pay you for them?” Just a few inquiries were enough to make us explore the business model.
Long story short, we developed solutions for these companies, which resulted in enterprise compute contracts and led us to expand our product suite for this type of customer. Today, the vast majority of Aethir’s clients are large AI companies using our infrastructure for training and inference.
Why does decentralized GPU infrastructure matter for the next wave of AI, Web3?
There are a couple of reasons why decentralized infrastructure is important. First, Aethir has a presence in over 93 countries with nearly 300 data centers housing our GPUs. This geographic distribution exceeds anything even the hyperscalers have, meaning builders in places like South Korea, Vietnam, or Norway can access local compute. Hyperscalers not only charge two to ten times more, but their infrastructure may also be located far from users, reducing performance. There’s a clear distribution advantage that decentralized infrastructure allows.
Second, with the rise of agentic infrastructure, agents will transact primarily on the blockchain and are likely to purchase compute the same way. Networks like Aethir are inherently aligned with these blockchain payment rails, giving us a potential advantage over hyperscalers by enabling direct compute ownership for agents, not just companies.
When competing with Amazon Web Services, Google Cloud, and Microsoft Azure, where will hyperscalers remain dominant?
There will always be advantages for market leaders and incumbents—they are massive companies with significant legacy trust. I don’t view Aethir as a decentralized competitor to hyperscalers; we’re a startup, a mid-market competitor. However, we’re more agile, adapt faster, have better unit economics, and offer friendlier terms to startups.
What are the challenges to building a permissionless, enterprise-grade GPU network?
There are technical and economic challenges. The biggest technical challenge in a network like Aethir’s is building an enterprise-grade system on hardware you don’t own. Enterprise customers expect strict SLAs—like 99.99% uptime, guaranteed bandwidth, and other requirements—but if a hardware provider exits the network, it can cause downtime and breach contracts. Managing this is extremely challenging.
Decentralized networks often mitigate this through staking: hardware providers pay a deposit when joining, which they forfeit if they leave early. Running a network on hardware you don’t own is both a major advantage and one of the hardest aspects of this type of ecosystem.
How can decentralized compute networks meet enterprise expectations around compliance, verification, and reliable service levels?
Enterprise companies have very high expectations, and historically, crypto companies haven’t met them. Many crypto projects build solutions for low-quality participants—whether hardware or users—which don’t translate to enterprise needs. You can’t take a product designed for crypto users and show it to a bank or large Web2 company; they won’t accept the limitations.
From day one, we designed Aethir to be enterprise-ready, understanding exactly what these customers require. As a result, working with us feels like working with a major Web2 company: the crypto element is fully abstracted, and the focus is on reliably meeting the basic enterprise requirements necessary to be considered a credible partner.
What early indicators show real demand for decentralized GPU compute?
Within Aethir, we track revenue closely, and we generate more than all other DePIN projects combined. In fact, we likely have the highest revenue of any crypto project that doesn’t earn from gas or fees, making revenue a key metric of our progress. Beyond that, macro indicators of compute demand are clear—anyone following AI trends can see that demand for GPUs is only growing.
How would you describe today’s market and its main growth drivers?
The overall market is in a downturn, but from a sector perspective—looking at AI rather than crypto—there is an insatiable appetite for compute. Demand for infrastructure has never been higher and consistently outpaces supply. Just when the market thinks it’s caught up, new developments—like better video models or agentic AI—create fresh compute needs. From that perspective, the AI compute market is a “rocket ship,” with new opportunities for inference emerging every few weeks and increasingly capable models being released monthly. The sector is driven by relentless demand, creating an almost “up-only” trajectory.
What single inflection point could accelerate more the enterprise adoption of DePIN compute?
I think the market hasn’t fully realized it yet, but an inflection point happened about a month ago with an open-source technology called OpenClaw. It’s an agent-based system where you can plug in OpenAI or Anthropic API keys, creating independent agents that can interact with the world—manage files, send emails, basically act like a digital assistant.
The challenge is hidden in payments: you can’t give these agents bank accounts or credit cards, and existing payment systems often block bot activity. That’s where blockchain and crypto rails become important—they’re programmatic and easy for agents to use. This creates a “hockey stick” moment for agentic use cases, letting agents manage subscriptions, costs, and even pay for themselves. As a result, providers like Aethir, which support crypto-native payments, are uniquely positioned to benefit from this surge in autonomous agent demand.
How do you see Aethir’s role evolving within the DePIN ecosystem over the next few years?
Aethir recently launched a NASDAQ-listed entity called Axes Compute (ticker: GPU), representing Aethir’s interests and operating on our infrastructure. It functions as a digital asset treasury for Aethir. We see our public market presence as critical to growth: we are no longer just a crypto company, but a publicly listed entity. This next phase positions us with one foot in the DePIN ecosystem and one in broader capital markets, allowing us to leverage public market scale while creating outsized value in the decentralized and crypto space.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
