Bell Curve The Intersection of AI and Crypto: What Worked, What Didn’t, and What’s Next | Roundup
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Jan 23, 2026 The discussion dives into the early hype surrounding the intersection of AI and crypto, highlighting speculation and early disappointments. Insights reveal how decentralized models struggle against centralized labs' advantages. Key topics include the value crypto can add to AI, especially in coordinating inputs, and the challenges of decentralized compute marketplaces. The hosts also explore how AI might disrupt SaaS pricing models. Ultimately, they identify where long-term value is likely to emerge in applications and data relevance.
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Hype Outpaced Product
- Initial crypto×AI hype relied more on speculation and token interest than real product-market fit.
- Teams underestimated how fast centralized AI labs would outpace decentralized efforts.
Agents Need Real Demand
- Agents on chain remain constrained by complexity and low day-to-day adoption.
- Crypto should focus where agentic apps and application layers add unique value.
Centralized Labs' Acceleration
- Decentralized AI infrastructure lags because centralized labs scale faster and improve models quicker.
- Crypto's strength is coordination, but not necessarily competing at compute or model creation.