Eric Jang explains how to build AlphaGo from scratch using modern AI tools, detailing the game of Go's rules and the core Monte Carlo Tree Search (MCTS) algorithm. He describes how deep neural networks, specifically value and policy network…
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Reiner Pope delivers a blackboard lecture on the mathematical and hardware principles behind training and serving large language models. He explains how batch size, sparsity, and various parallelism strategies (expert, pipeline) impact late…
LLM trainingLLM inferenceBatch sizeLatency optimizationCost analysisRoofline analysisMemory bandwidthCompute performanceKV CacheSparsityMixture of ExpertsExpert parallelismData center architectureScale up networkScale out networkPipeline parallelismMicrobatchingMemory capacityChinchilla scalingRL generationAPI pricingContext lengthCryptographic ciphersNeural network architectureReversible networks