FILE 00118KIn the same month, Jack Clark and Chamath Palihapitiya independently flagged the same thing: a 72-billion-parameter model trained across 160 GPUs by anonymous participants coordinating through a blockchain. Neither is a Bittensor insider. Both recognized what it means when the ability to create foundation models stops being a privilege of five organizations.
FILE 00217KSomeone on X pointed out that Covenant-72b can't count the R's in strawberry. They're right. But so were the people who laughed at GPT-4 for the same mistake two years before it started passing the bar exam. The interesting question was never whether the model fails. It's why, what that reveals about intelligence, and what happens next.
FILE 00321KTony Hawk spent thirteen years trying to land a trick the world said was impossible. Within a decade, teenagers were doing it on YouTube. Steven Kotler calls this the 'seeing it done' effect. Covenant72B, the largest model ever trained on a fully decentralized network, is that same moment for AI. The impossible just became the starting line.
FILE 00429KPre-training gives AI knowledge. Post-training teaches it judgment: what to refuse, how to reason, what to value. This is the phase where alignment happens, and while decentralized efforts existed, weight sync over public internet made them impractically slow. This week, a research paper from Grail demonstrated that the bandwidth barrier keeping RL post-training centralized was 99% redundant, an artifact of how we were moving data rather than a physical constraint. The implications extend far beyond compression ratios.
FILE 00529KFor eighty years, the most powerful technologies have required concentration: co-located machines in fortress datacenters, tightly controlled by those who could afford the infrastructure. This week's research breakthrough from Templar marks something different, a technical path toward intelligence as genuinely distributed public infrastructure, where your home GPU can train frontier models alongside Google's datacenters.
FILE 00618KThree years ago, I wouldn't have believed I'd be training for a half marathon while helping coordinate a decentralized AI protocol. But both journeys, the solo morning miles and the collective effort to democratize artificial intelligence, follow the same philosophy.
