Transformer
machine-learning model architecture first developed by Google Brain
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Videos Mentioning Transformer
Yann LeCun: Deep Learning, ConvNets, and Self-Supervised Learning | Lex Fridman Podcast #36
Lex Fridman
A type of neural network architecture mentioned in the context of reasoning and working memory, with limitations related to recurrence and fixed layers.
Oriol Vinyals: DeepMind AlphaStar, StarCraft, and Language | Lex Fridman Podcast #20
Lex Fridman
A neural network architecture, very popular in natural language processing since 2017, and also used in AlphaStar to integrate past observations and actions.
Deep Learning State of the Art (2019)
Lex Fridman
A model architecture that utilizes self-attention in the encoder and attention in the decoder to capture rich context from the input sequence for output generation.
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge
Stanford Online
A novel neural network architecture that enabled scaling of language model training through self-attention, leading to improved performance on GPUs.
Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 7 - Evaluation
Stanford Online
A type of neural network architecture that transforms text to text, mentioned as a known model that cannot be directly reused for multimodal image-to-text evaluation.