Solana's focus on increasing bandwidth and reducing latency is a synergistic cornerstone for Crypto x AI projects on Solana beating Web2 AI labs
SOL latency way down x Decentralized training efficiency way up
Think (FireDancer, @doublezero, AlpenGlow 150ms finality) x (@NousResearch disTro's training efficiency)
We've had 20+ years to optimize co-located GPU datacenters, now we are seeing ridiculous improvements to the core infra (solana) and decentralized training methods to make this a competitive offering
Incredible Crypto x AI thesis by @twillz24 on @Delphi_Digital
TLDR: He's seeing the Web2 AI labs focus on GPU efficiency (Prompt caching, essential changes only) and focus on return on GPU metrics (i.e. ChatGPT 4.5 -> 4.1 demonstrates this)
He argues the opportunity is more pronounced for Crypto x AI since we have a global network of hardware + token yields that can drive down the cost of training/inference (I.e. @NousResearch / @inference_labs / many others in each bucket) to a degree that creates a stronger flywheel. Cheaper costs -> richer app ecosystem, usage and applications.
Incredible Crypto x AI thesis by @twillz24 on @Delphi_Digital
TLDR: He's seeing the Web2 AI labs focus on GPU efficiency (Prompt caching, essential changes only) and focus on return on GPU metrics (i.e. ChatGPT 4.5 -> 4.1 demonstrates this)
He argues the opportunity is more pronounced for Crypto x AI since we have a global network of hardware + token yields that can drive down the cost of training/inference (I.e. @NousResearch / @inference_labs / many others in each bucket) to a degree that creates a stronger flywheel. Cheaper costs -> richer app ecosystem, usage and applications.