Show HN: Bets on Post-GPU Compute

Vishal V's exploration of post-GPU compute and Extropic AI's bet on sampling as the primitive marks a significant shift in the approach to AI processing. The focus on block Gibbs sampling algorithm and its potential to generalize beyond strictly bipartite models indicates a potential breakthrough in efficient AI computation. This development has significant implications for website owners, particularly those who rely heavily on AI-driven content or services. As post-GPU compute becomes more prevalent, website owners can expect increased efficiency and reduced costs associated with AI processing. This, in turn, may lead to a surge in AI-driven traffic to their sites, making it essential to have robust AI bot tracking and management systems in place. To prepare for this shift, website owners should take the following actionable steps: monitor their llms.txt files for updates related to post-GPU compute and sampling-based AI models, adjust their content policies to accommodate the potential increase in AI-driven traffic, and explore ways to optimize their sites for block Gibbs sampling algorithm-based AI bots to ensure seamless interaction and minimize potential disruptions.