FILE 00119KOn June 4, two days into a seventy-day training competition, the crown landed on a checkpoint that was more than half bit-identical to a model that already existed. A public audit has now shown what that means: the season's flagship from-scratch claim in crypto AI descends, weight by weight, from Alibaba's Qwen. The scandal is real. So is the inversion inside it: only open weights could have been caught this way, and the honor system for training claims ended the moment anyone could check.
FILE 00219KIn 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 00317KSomeone 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 00421KTony 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 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.
FILE 00710KWhy a technical breakthrough in gradient compression could reshape who controls the future of artificial intelligence
FILE 0087KMeet the cryptopunk miners of Templar training AI models on their gaming rigs, challenging the assumption that only trillion-dollar companies can build artificial intelligence.
