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How might LLMs store facts | Deep Learning Chapter 7 How might LLMs store facts | Deep Learning Chapter 7 23 λεπ iPhone Duo Hands On! iPhone Duo Hands On! 2 λεπ 13 most EXPENSIVE Tech Fails of all time 13 most EXPENSIVE Tech Fails of all time 24 λεπ I bought the most CURSED TECH on the internet ft. KSI I bought the most CURSED TECH on the internet ft. KSI 25 λεπ Toxic ABANDONED Shopping Mall - Exploration Toxic ABANDONED Shopping Mall - Exploration 14 λεπ They Left The Tourist Trail: Kris Kremers and Lisanne Froon | Fascinating Horror They Left The Tourist Trail: Kris Kremers and Lisanne Froon | Fascinating Horror 11 λεπ The Prisoner of Bogan The Prisoner of Bogan 32 λεπ SUICIDE NOTE SUICIDE NOTE 4 λεπ The Lost Divers They Refused To Rescue: The Paria Accident | Fascinating Horror The Lost Divers They Refused To Rescue: The Paria Accident | Fascinating Horror 12 λεπ Disney Channel's Theme: A History Mystery Disney Channel's Theme: A History Mystery 92 λεπ Crashed By A Crocodile? 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How might LLMs store facts | Deep Learning Chapter 7

2024 23 λεπ

Unpacking the multilayer perceptrons in a transformer, and how they may store facts Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support An equally valuable form of support is to share the videos. AI Alignment forum post from the Deepmind researchers referenced at the video's start: https://www.alignmentforum.org/posts/iGuwZTHWb6DFY3sKB/fact-finding-attempting-to-reverse-engineer-factual-recall Anthropic posts about superposition referenced near the end: https://transformer-circuits.pub/2022/toy_model/index.html https://transformer-circuits.pub/2023/monosemantic-features Some added resources for those interested in learning more about mechanistic interpretability, offered by Neel Nanda Mechanistic interpretability paper reading list https://www.alignmentforum.org/posts/NfFST5Mio7BCAQHPA/an-extremely-opinionated-annotated-list-of-my-favourite Getting started in mechanistic interpretability https://www.neelnanda.io/mechanistic-interpretability/getting-started An interactive demo of sparse autoencoders (made by Neuronpedia) https://www.neuronpedia.org/gemma-scope#main Coding tutorials for mechanistic interpretability (made by ARENA) https://arena3-chapter1-transformer-interp.streamlit.app/ Звуковая дорожка на русском языке: Влад Бурмистров. Sections: 0:00 - Where facts in LLMs live 2:15 - Quick refresher on transformers 4:39 - Assumptions for our toy example 6:07 - Inside a multilayer perceptron 15:38 - Counting parameters 17:04 - Superposition 21:37 - Up next ------------------ These animations are largely made using a custom Python library, manim. See the FAQ comments here: https://3b1b.co/faq#manim https://github.com/3b1b/manim https://github.com/ManimCommunity/manim/ All code for specific videos is visible here: https://github.com/3b1b/videos/ The music is by Vincent Rubinetti. https://www.vincentrubinetti.com https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. If you're reading the bottom of a video description, I'm guessing you're more interested than the average viewer in lessons here. It would mean a lot to me if you chose to stay up to date on new ones, either by subscribing here on YouTube or otherwise following on whichever platform below you check most regularly. Mailing list: https://3blue1brown.substack.com Twitter: https://twitter.com/3blue1brown Instagram: https://www.instagram.com/3blue1brown Reddit: https://www.reddit.com/r/3blue1brown Facebook: https://www.facebook.com/3blue1brown Patreon: https://patreon.com/3blue1brown Website: https://www.3blue1brown.com

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