Barry Silbert isn’t slowing down. The self-made billionaire, who first gained recognition at just 17 as the youngest person in the U.S. to earn a stockbroker license, has consistently stayed ahead of financial and technological curves. From Wall Street trading to pioneering alternative asset platforms like Second Market—later acquired by NASDAQ—Silbert’s career has been defined by early bets on transformative technologies. His most famous move? Buying Bitcoin in 2012 when it was trading at just $11, and subsequently building Digital Currency Group (DCG), a powerhouse in the crypto ecosystem.
Now, Silbert is turning his attention to the next frontier: decentralized artificial intelligence (AI). In a bold new venture, he’s launched Yuma, a subsidiary dedicated to advancing AI through decentralized networks. Unlike traditional AI giants such as Google and OpenAI, which rely on centralized data centers and proprietary models, Yuma is betting on a distributed model—where intelligence, computing power, and innovation emerge from a global network of independent contributors.
This vision hinges on blockchain-powered infrastructure, specifically a project called Bittensor, launched in 2021. Bittensor incentivizes developers and machine learning engineers to contribute AI models and computing resources by rewarding them with TAO tokens, its native cryptocurrency. Silbert sees this as the foundation for a permissionless, open-source AI future—one that mirrors the early days of the internet, before corporate “walled gardens” dominated online access.
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The Vision: Decentralized Intelligence for the Masses
Silbert draws a direct parallel between the evolution of the internet and what he believes is coming for AI. In the 1990s, closed networks like AOL and CompuServe controlled user access to information. Then came the open web—decentralized, permissionless, and globally accessible. He argues that today’s AI landscape resembles those early walled gardens: dominated by a few well-funded tech giants with exclusive control over data, algorithms, and infrastructure.
“Just like the early days of Bitcoin, which fueled the development of a new form of transparent, borderless money, we’re moving from the digital ownership of assets to the decentralized ownership of intelligence,” Silbert said in a recent interview.
Yuma’s mission is to help build this decentralized alternative—not by replacing existing AI systems, but by creating an open ecosystem where anyone can contribute, innovate, and profit. At the core of this effort are subnets, modular AI services running on the Bittensor network. These subnets function like specialized applications—some handle natural language processing, others focus on image generation or data analysis. Currently, around 60 subnets are active, but Silbert envisions thousands emerging as developer interest grows.
Bittensor: The Engine Behind Decentralized AI
Launched in 2019 by a former Google engineer, Bittensor operates as a blockchain-based protocol designed to democratize AI development. It uses TAO tokens to reward participants who provide valuable machine learning models or computing power to the network. Like Bitcoin, TAO is mined—though instead of solving cryptographic puzzles, miners contribute useful AI computations.
The total supply of TAO is capped at 21 million, mirroring Bitcoin’s scarcity model. As of now, TAO has a market cap of approximately $3.5 billion, ranking it among the top 35 cryptocurrencies globally—still far behind Ethereum but gaining momentum as interest in decentralized AI grows.
One of the key innovations of Bittensor is its incentive mechanism. Developers upload models to subnets; the network evaluates their performance and distributes TAO tokens accordingly. This creates a competitive yet collaborative environment where quality is rewarded automatically.
Silbert acknowledges that crypto terminology can be off-putting to mainstream users and enterprises. That’s why Yuma is intentionally downplaying the blockchain aspect, focusing instead on delivering practical AI services. “Blockchain scares people away,” he admits. “Our focus is on building decentralized intelligence—not selling crypto.”
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Overcoming Challenges in Decentralized AI
Despite its promise, decentralized AI faces significant hurdles. Leading AI companies like Google and OpenAI benefit from vast financial resources, proprietary datasets, and massive data centers optimized for high-speed processing. They invest billions in custom chips (like TPUs and GPUs) and rely on colocation—placing computing hardware close together to minimize latency.
Decentralized networks, by contrast, operate across scattered nodes worldwide. This geographic distribution introduces latency challenges and makes real-time coordination difficult—especially for tasks requiring heavy computational throughput.
Jeff Wilser, host of the AI-Curious podcast, remains cautiously optimistic. “The idea of open, non-corporate-controlled AI is compelling,” he says. “But it’s unclear whether a decentralized model can match the efficiency and scale of centralized giants.”
Still, there are areas where decentralized AI could thrive. For example, data training and model fine-tuning don’t always require instant response times. Idle computing power from personal devices, research labs, or underused cloud servers could be harnessed effectively in these contexts.
Moreover, Michael Casey, chair of the Decentralized AI Society, believes that AI agents themselves may solve usability issues. These autonomous programs could act as intermediaries—interacting with complex decentralized systems behind the scenes so users don’t have to.
“The complexity will fade into the background,” Casey predicts. “Soon, users won’t even realize they’re interacting with a decentralized network.”
FAQs About Decentralized AI and Barry Silbert’s Yuma Initiative
Q: What is decentralized AI?
A: Decentralized AI refers to artificial intelligence systems built on distributed networks rather than centralized servers. Instead of being controlled by a single company, they rely on contributions from independent developers and machines around the world.
Q: How does Bittensor work?
A: Bittensor is a blockchain protocol that rewards participants with TAO tokens for contributing useful AI models or computational power. It uses a proof-of-work-like system where value is determined by utility, not just energy consumption.
Q: Why is Barry Silbert involved in decentralized AI?
A: Known for early investments in Bitcoin and blockchain infrastructure, Silbert sees decentralized AI as the next logical step—a way to extend principles of openness, ownership, and permissionless innovation into artificial intelligence.
Q: Can decentralized AI compete with Google or OpenAI?
A: Not immediately. Centralized firms have massive advantages in funding and infrastructure. However, decentralized AI may excel in niche areas like open research, censorship-resistant applications, and community-driven development.
Q: Is TAO a good investment?
A: As with any cryptocurrency, TAO carries risks. Its value depends on adoption of the Bittensor network and broader market conditions. Investors should conduct thorough research before participating.
Q: Will users notice if they’re using decentralized AI?
A: Eventually, no. The goal is seamless integration—where backend decentralization remains invisible to end users, much like how most people don’t know how DNS works when browsing the web.
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The Road Ahead
While mainstream applications of decentralized AI are still in their infancy, Silbert’s involvement brings credibility and capital to the space. By leveraging lessons from Bitcoin’s rise—gradual adoption, developer momentum, and network effects—he aims to position Yuma at the forefront of a paradigm shift.
The journey won’t be easy. Usability, scalability, and public trust remain major obstacles. But if history is any guide, disruptive ideas often start on the fringes before becoming mainstream.
As Silbert puts it: “We’re not just building another AI company. We’re laying the foundation for a new kind of intelligence—one that belongs to everyone.”
Core Keywords: decentralized AI, Barry Silbert, Bittensor, TAO token, blockchain AI, Yuma, artificial intelligence, crypto incentives