Transformers: The best idea in AI | Andrej Karpathy and Lex Fridman
Tubopedia Mission
[Transformers: The best idea in AI | Andrej Karpathy and Lex Fridman](https://www.youtube.com/watch?v=9uw3F6rndnA) - The [Transformer architecture](/posts/Transformers-Explained-Understand-the-model-behind-GPT-BERT-and-T5) in deep learning is considered a beautiful and surprising idea. - It is a general-purpose neural network architecture that can process various sensory modalities such as vision, audio, text, etc. - The Transformer is a powerful, trainable, and efficient computer that can handle a wide range of tasks. - The architecture was introduced in a paper titled "Attention Is All You Need" in 2016 and has had a significant impact on the field. - The authors may not have fully anticipated the extent of its impact, but they were aware of the motivations and design decisions behind it. - The catchy and memeable title of the paper, though not entirely reflective of its significance, contributed to its popularity. - The Transformer is expressive, optimizable, and efficient, making it suitable for various computations and hardware setups. - It supports the learning of short algorithms and gradually extends them during training through residual connections. - The architecture has remained stable over the years, but there is ongoing exploration to improve it further. - Current trends focus on scaling up datasets, improving evaluation, and keeping the architecture unchanged while making advancements in other areas. see [Lex Fridman](/posts/Lex-Fridman)