Member-only story
AI Meets Crypto: Hype or Hope? A Professor’s View
As a professor, I’m often skeptical when two trending topics are mashed together and labeled revolutionary. Too frequently, this leads to solutions in search of problems. The intersection of AI and crypto might seem to suffer from this hype, with the crypto world sometimes advocating “decentralization for decentralization’s sake” without delivering real utility.
However, if we strip away the noise and focus on first principles, there are clear, impactful ways in which these two technologies can complement one another. This post outlines how AI can benefit from crypto, how crypto can be enhanced by AI, and key pitfalls to avoid.
How Can We Make AI Better With Crypto?
1. Decentralized Data Collection and Valuation
Large foundation models like OpenAI’s GPT-4 rely on massive datasets scraped from the internet — often with dubious legality. A decentralized system could compensate data contributors fairly, creating an economy around high-quality data contributions. Think of it as a decentralized version of Scale AI.
For example, individuals could contribute anonymized images, audio, or text from their devices, feeding it into a training pipeline using algorithms like Federated Learning. Using techniques like Data Shapley, contributors could be paid based on the marginal value their data adds to the final model. Each dataset could even be tokenized as NFTs to transparently track ownership and value.
2. Decentralized Training and Inference
As someone who has spent over $400,000 on Nvidia GPUs for my lab, I often see these expensive resources idle outside of major paper deadlines. A decentralized network could allow labs, companies, and individuals to monetize unused GPUs as a source of passive income.
Imagine downloading models from Hugging Face and serving them as APIs, similar to OpenAI’s GPT-4, but at a cheaper price. Users would pay in fiat currency for model outputs, and GPU operators would earn crypto tokens. The value of these tokens could grow as the network gains adoption, tying them to real-world demand.
