EfficientML.ai Lecture 17: Distributed Training (Part I) (MIT 6.5940, Fall 2023)
EfficientML.ai Lecture 17: Distributed Training (Part I) (MIT 6.5940, Fall 2023) Instructor: Prof. Song Han Slides: https://efficientml.ai
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EfficientML.ai Lecture 17: Distributed Training (Part I) (MIT 6.5940, Fall 2023, Zoom)
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Stanford CS230 | Autumn 2025 | Lecture 8: Agents, Prompts, and RAG
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M. Perarnau-Llobet -Thermodynamic Networks: Harnessing Non-Equilibrium Steady States for Computation
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EfficientML.ai Lecture 18: Distributed Training (Part II) (MIT 6.5940, Fall 2023)
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Chip design from the bottom up – Reiner Pope
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Computer Architecture - Lecture 27: Systolic Arrays (ETH Zürich, Fall 2020)
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EfficientML.ai Lecture 9 - Knowledge Distillation (MIT 6.5940, Fall 2023)
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Distributed ML Talk @ UC Berkeley
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Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM | Jared Casper
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Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
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LLM inference optimization: Architecture, KV cache and Flash attention
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Visualizing transformers and attention | Talk for TNG Big Tech Day '24
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EfficientML.ai Lecture 16 - Diffusion Model (MIT 6.5940, Fall 2023)
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EfficientML.ai Lecture 14 - Vision Transformer (MIT 6.5940, Fall 2023)
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Harnesses in AI: A Deep Dive — Tejas Kumar, IBM
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EfficientML.ai Lecture 12 - Transformer and LLM (Part I) (MIT 6.5940, Fall 2023)
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Exploring the Latency/Throughput & Cost Space for LLM Inference // Timothée Lacroix // CTO Mistral
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Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker
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"A.I. and Our Economic Future," Professor Chad Jones
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