Posts tagged with #PULSE
PULSEDecentralized AIReinforcement LearningGrailBittensorCovenant AIWeight CompressionBF16Machine LearningAI Alignment
Who Teaches the Machine: How Grail is Decentralizing the Most Consequential Phase of AI Development
Pre-training gives AI knowledge. Post-training teaches it judgment: what to refuse, how to reason, what to value. This is the phase where alignment happens, and while decentralized efforts existed, weight sync over public internet made them impractically slow. This week, a research paper from Grail demonstrated that the bandwidth barrier keeping RL post-training centralized was 99% redundant, an artifact of how we were moving data rather than a physical constraint. The implications extend far beyond compression ratios.
Derek Barnes
