When people think about artificial intelligence (AI), they picture the result, whether it’s the recipe the large-language model (LLM) provided or the email it was able to rephrase. These concrete outputs are easy to appreciate, yet few take the time to consider the infrastructure and processes that need to occur to produce the end product.
Even though AI’s results might seem instant, a considerable amount of computation and data analysis occurs behind the scenes. As projects and industries increasingly adopt AI solutions into their tech stack, the infrastructure needed to support these systems is becoming increasingly centralized and expensive.
However, one company believes that AI computing should be accessible to all instead of being a privilege confined to a small group who can take advantage of this technology.
Exabits has recognized the growing demand for computational power, converting raw GPU resources from top manufacturers like NVIDIA into enterprise-level computing services. By democratizing access, Exabits ensures that developers avoid steep delays caused by infrastructure shortages.
In a written interview with MSN, Mark Fidelman, Exabit’s CSO, shared his insight into the company’s mission and the future of AI. “AI is devouring compute power at a rate that traditional cloud providers cannot keep up with,” said Fidelman. “While Amazon, Google, and Microsoft struggle with supply chain bottlenecks, we’re scaling faster, cheaper, and without vendor lock-in.”
As AI, particularly AI agents, grow more essential across different sectors from healthcare to finance, Fidelman observes that their ongoing engagement will drive demand to unprecedented levels. Fidelman notes that their constant activity will drive demand to unprecedented levels. He explains, “Exabits is already preparing for this with H200 GPUs, next-gen networking, and a scalable architecture that can handle billions of AI interactions daily.”
Developers and founders face the challenge of Big Tech increasingly monopolizing the resources required to operate these models. Businesses depend on a shortlist of industry players, which controls availability and determines the prices for use, leaving firms with limited control over the architecture essential for projects to run.
Fidelman addresses how Exabits contributes to the vision of decentralized AI, saying “Exabits is decentralizing AI compute by removing the middlemen, creating an open market for compute, giving developers complete control over their infrastructure. Now, AI projects will be able to scale without fear of being shut down, censored, or priced out.”
In response to the growing demand for compute, it has evolved into an asset class, gaining more recognition of its worth and limited availability. Like capital, retail investors are starting to see compute as an essential asset to invest in.
“Compute is the new oil. The companies that control compute will control the AI economy, and Exabits ensures that access to compute is tokenized and tradable. Our tokenized compute model means companies can own, stake, and monetize compute power instead of just renting it,” says Fidelman.
Now, with AI reaching new heights, regulation is coming ahead quickly. Fidelman shares that AI companies need to remain one step ahead. This requires focusing on data security, compliance-friendly infrastructure, and transparent auditing. “At Exabits, we’re implementing trusted execution environments (TEEs) to ensure AI computations remain secure and compliant while still being decentralized,” Fidelman explained.
Expanding on these developments, he concludes by sharing: “The biggest development on Exabit’s horizon? The launch of our tokenized compute marketplace which will redefine how AI companies access and pay for compute. If you think AI is big now, wait until Exabits unlocks decentralized compute globally.”
With its unique vision and commitment to equal entry points to AI infrastructure, Exabits is reshaping the AI industry. It allows projects worldwide and across different sectors to harness AI’s full potential without the constraints of traditional tech players.
