#73- Transformers.

<p>Hey guys, in this episode I explain most of what I know about Transformers. I talk about the architecture, the attention formula, encoder, decoder, self-supervised learning, positional encoding, tokenization, inductive bias, Vision-Transformers, receptive fields...</p> <p><br></p> <p>It was the most technical episode I&#39;ve recorded so far, and I hope you like it! By the way, it worth listening to this episode with the Transformers paper.</p> <p><br></p> <p>Paper Transformers: <a href="https://arxiv.org/pdf/1706.03762.pdf">⁠https://arxiv.org/pdf/1706.03762.pdf⁠</a></p> <p>Link of OpenAI explaining Next Token Prediction: https://www.linkedin.com/posts/zainhas_the-most-clearest-and-crisp-explanation-ugcPost-7132561633280692224-63AX?utm_source=share&amp;utm_medium=member_desktop</p> <p>Instagram: https://www.instagram.com/podcast.lifewithai/  </p> <p>Linkedin: https://www.linkedin.com/company/life-with-ai</p>