The development of artificial intelligence faces decentralization challenges. Crypto projects offer solutions, competing with big tech companies.
AI, Crypto, and the Decentralization Dilemma
One of the core tenets driving crypto enthusiasts is decentralization. It opposes the U.S. Securities and Exchange Commission’s Howey test, which defines investment contracts as relying on a 'common enterprise' and the 'efforts of others' for profit. While most securities are tied to centralized corporations, Bitcoin, Ethereum, and other sufficiently decentralized networks are designed to function without a central authority. As AI becomes more mainstream, the same ethos of decentralization is extending to it, especially given the growing dominance of Google, Microsoft, and OpenAI.
Crypto's Push for Decentralized AI
Blockchain-based AI projects, such as Tao, Virtuals on Base, and AI16Z on Solana, are launching decentralized AI models. One of their primary challenges is access to vast amounts of high-quality data. In contrast to corporate giants, decentralized teams are at a disadvantage that limits progress and adoption.
The Cost Factor and DeepSeek
The issue of cost also looms. Major companies may create a 'pay-to-play' environment where developers are charged for using AI infrastructure. Meanwhile, startups like DeepSeek offer more cost-effective AI models that could shift the market dynamics.
DeepSeek demonstrates that alternatives exist but may create new dependencies. For the future of crypto AI, decentralization remains a significant challenge.
