Show notes
Link to Youtube: https://youtu.be/w8S8sSPHqLwFormula 1 recap (0:00)State of AI: a year since gpt3 (9:30)Origins of Deep learning and Generative AI (12:30)Intelligence is compute power and model size (19:00)Gemini, and how to define AGI (29:00)How ChatGPT thinks (34:30)Multimodality (40:20)AI based robotics (46:30)Impacts on society: Separating Alignment and Safety (49:40)What we should train deep learning models for (55:50)LinksShoutout to rockerpoweredmohawk (F1 related content): https://www.youtube.com/@RocketpoweredmohawkThe Gemini Lie: https://www.youtube.com/watch?v=90CYYfl9ntM&pp=ygUbZmlyZXNoaXAgY29kZSByZXBvcnQgZ2ltaW5pPower of Multimodal AI (hints towards AGI)https://youtu.be/ex1GeX0IhJQ?si=hrYWTE7BREbCszUnHinton's whitepaper (backpropagation applied on multi-layer perceptron in 1986): https://www.nature.com/articles/323533a0LeNet whitepaper (mathematical proof of CNNs in 1990): https://direct.mit.edu/neco/article-abstract/1/4/541/5515/Backpropagation-Applied-to-Handwritten-Zip-Code?redirectedFrom=fulltextAlexNet whitepaper (first popular practical application of CNNs in 2011): https://dl.acm.org/doi/10.1145/3065386The paper that "transformed" the natural language processing world: https://dl.acm.org/doi/10.5555/3295222.3295349OpenAI being inconsistent with model architecture transparency: https://en.wikipedia.org/wiki/GPT-4#Criticisms_of_transparencyAndrej Karpathy OpenAI pipeline talk - https://youtu.be/bZQun8Y4L2A?si=Im-cCSfGXhG87YvzAlpha fold (Predicting protein structure from sequence) - https://alphafold.ebi.ac.uk/GNoME (Material Science AI) - https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/