• The Unreasonable Effectiveness of Recurrent Neural Networks

  • Nov 2 2024
  • Length: 15 mins
  • Podcast

The Unreasonable Effectiveness of Recurrent Neural Networks

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  • Summary

  • In this episode we break down the blog post by Andrej Karpathy: The Unreasonable Effectiveness of Recurrent Neural Networks, which explores the capabilities of recurrent neural networks (RNNs), highlighting their surprising effectiveness in generating human-like text. Karpathy begins by explaining the concept of RNNs and their ability to process sequences, demonstrating their power by training them on various datasets, including Paul Graham's essays, Shakespeare's works, Wikipedia articles, LaTeX code, and even Linux source code. The author then investigates the inner workings of RNNs through visualisations of character prediction and neuron activation patterns, revealing how they learn complex structures and patterns within data. The post concludes with a discussion on the latest research directions in RNNs, focusing on areas such as inductive reasoning, memory, and attention, emphasising their potential to become a fundamental component of intelligent systems.

    Audio : (Spotify) https://open.spotify.com/episode/5dZwu5ShR3seT9b3BV7G9F?si=6xZwXWXsRRGKhU3L1zRo3w

    Paper: https://karpathy.github.io/2015/05/21/rnn-effectiveness/
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