AI inference is getting cheaper. But it’s consuming more and more of the AI compute stack.
About SN14 Cacheon
Cacheon@cacheon_aiAI inference is getting cheaper. But it’s consuming more and more of the AI compute stack. McKinsey released a new report yesterday, estimating that by 2030, inference will account for ~60% of AI compute demand, versus ~40% for training. That makes inference optimization increasingly consequential: every gain in throughput and utilization changes how much useful AI the same hardware can serve. McKinsey’s full report ↓ mckinsey.com/industries/semiconductors/our-insi…
Linkmckinsey.commckinsey.com/industries/semiconductors/our-insights/scaling-ai-inferenceSN14 Cacheon at a glance
SN14, Cacheon (α token ㄷ), is one of the independent markets on the Bittensor network, each with its own α token and its own price. Its α currently trades at 0.008730 τ (≈ $2.65), against 24,580 τ of pool liquidity. On-chain, the best-delegated validator on it yields about 58.51% APR (simple) and 79.50% APY (compounded), emissions add 0.001219 τ to the pool each block, epochs run every 360 blocks. It was registered at block #4,848,444.
More from SN14 Cacheon
Taosis indexes announcements, articles, posts and releases about Bittensor subnets from their own channels and keeps a record of each. The text above is the source’s; the figures are read from the chain by Taosis.