Cacheon

The energy around @Bittensor at @proofoftalk was exceptional. We had great conversations with old friends and made plenty of new ones across the ecosystem. People are no longer asking whether Bittensor can attract builders. They're asking how subnets will take market share, generate revenue, and build sustainable advantages over centralized AI firms. The ecosystem feels materially different than it did a year ago: more serious teams, stronger infrastructure, more capital, and significantly higher conviction. Came away more bullish than ever on SN14 Cacheon and the broader Bittensor space. Still a long road ahead, but the momentum is undeniable. Hopefully more good news in the coming weeks.

Cacheon mainnet is live. 13 inference servers queued, each racing to beat our baseline on a dedicated 8x H200 pod. The winner earns up to $10,000/day. Inference optimization starts today on @Bittensor. Follow along: cacheon.ai/dashboard

The TurboQuant paper (ICLR 2026) contains serious issues in how it describes RaBitQ, including incorrect technical claims and misleading theory/experiment comparisons. We flagged these issues to the authors before submission. They acknowledged them, but chose not to fix them. The paper was later accepted and widely promoted by Google, reaching tens of millions of views. We’re speaking up now because once a misleading narrative spreads, it becomes much harder to correct. We’ve written a public comment on openreview (openreview.net/forum?id=tO3AS…). We would greatly appreciate your attention and help in sharing it.

🔥 Subnet Summer AMA X @cacheon_ai (Subnet 14) 🔥 @xavi3rlu is building a decentralised inference competition network for open-source AI models, Cacheon is Subnet 14 on Bittensor, creating a permissionless benchmarking system to power the next generation of fast, accurate, and trustless AI inference infrastructure. In this episode, we sit down with the team behind Cacheon, a decentralised inference performance subnet built on Bittensor. We cover: - What Cacheon is building and why containerised inference competition matters for the future of open-source AI - How miners compete by submitting Docker-packaged inference servers optimised for speed and correctness when serving open-source models - Decentralised validation: how validators benchmark and score miner submissions in real time to ensure outputs meet quality and performance standards - Cacheon vs centralised inference providers and why the future of model serving should be open, permissionless, and economically incentivised - The role of token incentives in driving continuous performance improvements and attracting world-class inference engineers to the network - How Cacheon is pushing the boundaries of what decentralised compute can deliver for AI applications at scale - Early progress, current network stats, and what's coming next - Roadmap toward becoming the go-to decentralised inference layer for open-source model deployment - Live community Q&A If you're interested in decentralised AI, open-source model serving, GPU compute, or the future of inference infrastructure - this one's for you. youtu.be/noKx3ZHvUlI?si…