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Explore The moment we stopped understanding AI [AlexNet] with 2,517,190 views, 90,402 likes, and 2,189 comments. Experience the impact of this video content that has captured audience attention.

Thanks to KiwiCo for sponsoring today's video! Go to https://www.kiwico.com/welchlabs and use code WELCHLABS for 50% off your first month of monthly lines and/or for 20% off your first Panda Crate. Activation Atlas Posters! https://www.welchlabs.com/resources/5gtnaauv6nb9lrhoz9cp604padxp5o https://www.welchlabs.com/resources/activation-atlas-poster-mixed5b-13x19 https://www.welchlabs.com/resources/large-activation-atlas-poster-mixed4c-24x36 https://www.welchlabs.com/resources/activation-atlas-poster-mixed4c-13x19 Special thanks to the Patrons: Juan Benet, Ross Hanson, Yan Babitski, AJ Englehardt, Alvin Khaled, Eduardo Barraza, Hitoshi Yamauchi, Jaewon Jung, Mrgoodlight, Shinichi Hayashi, Sid Sarasvati, Dominic Beaumont, Shannon Prater, Ubiquity Ventures, Matias Forti Welch Labs Ad free videos and exclusive perks: https://www.patreon.com/welchlabs Watch on TikTok: https://www.tiktok.com/@welchlabs Learn More or Contact: https://www.welchlabs.com/ Instagram: https://www.instagram.com/welchlabs X: https://twitter.com/welchlabs References AlexNet Paper https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf Original Activation Atlas Article- explore here - Great interactive Atlas! https://distill.pub/2019/activation-atlas/ Carter, et al., "Activation Atlas", Distill, 2019. Feature Visualization Article: https://distill.pub/2017/feature-visualization/ `Olah, et al., "Feature Visualization", Distill, 2017.` Great LLM Explainability work: https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html Templeton, et al., "Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet", Transformer Circuits Thread, 2024. “Deep Visualization Toolbox" by Jason Yosinski video inspired many visuals: https://www.youtube.com/watch?v=AgkfIQ4IGaM Great LLM/GPT Intro paper https://arxiv.org/pdf/2304.10557 3B1Bs GPT Videos are excellent, as always: https://www.youtube.com/watch?v=eMlx5fFNoYc https://www.youtube.com/watch?v=wjZofJX0v4M Andrej Kerpathy's walkthrough is amazing: https://www.youtube.com/watch?v=kCc8FmEb1nY Goodfellow’s Deep Learning Book https://www.deeplearningbook.org/ OpenAI’s 10,000 V100 GPU cluster (1+ exaflop) https://news.microsoft.com/source/features/innovation/openai-azure-supercomputer/ GPT-3 size, etc: Language Models are Few-Shot Learners, Brown et al, 2020. Unique token count for ChatGPT: https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken GPT-4 training size etc, speculative: https://patmcguinness.substack.com/p/gpt-4-details-revealed https://www.semianalysis.com/p/gpt-4-architecture-infrastructure Historical Neural Network Videos https://www.youtube.com/watch?v=FwFduRA_L6Q https://www.youtube.com/watch?v=cNxadbrN_aI Errata 1:40 should be: "word fragment is appended to the end of the original input". Thanks for Chris A for finding this one. CFAQJOTYQHT7JYIT

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