The Unreasonable Effectiveness of Recurrent Neural Networks

Musings of a Computer Scientist.

There’s something magical about Recurrent Neural Networks (RNNs). I still remember when I trained my first recurrent network for Image Captioning . Within a few dozen minutes of training my first baby model (with rather arbitrarily-chosen hyperparameters) started to generate very nice looking descriptions of images that were on the edge of making sense. Sometimes the ratio of how simple your model is to the quality of the results you get out of it blows past your expectations, and this was one of those times. What made this result so shocking at the time was that the common wisdom was that RNN

saved by

• Pranav
• Rajan Agarwal
• Claire Wang
• Julian Quevedo
• Ivy Zhang
• Sarah Pan
• KL Yap
• Laerdon Kim
• Lydia Nottingham
• Yudhister Joel Kumar
• Timothy Kostolansky
• Julia

related reading

• The Unreasonable Effectiveness of Recurrent Neural Networkskarpathy.github.io
• Understanding LSTM Networks -- colah's blogcolah.github.io
• Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
• Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs · Denny's Blogdennybritz.com
• Recurrent neural networks - Scholarpediascholarpedia.org
• Recurrent neural network - Wikipediaen.wikipedia.org
• Recursive Language Models | Alex L. Zhangalexzhang13.github.io
• What Is ChatGPT Doing … and Why Does It Work?-Stephen Wolfram Writingswritings.stephenwolfram.com
• [2501.00663] Titans: Learning to Memorize at Test Timearxiv.org
• GitHub - karpathy/char-rnn: Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch · GitHubgithub.com
• The Decade of Deep Learning | Leo Gaobmk.sh
• [2606.06479] Pretraining Recurrent Networks without Recurrencearxiv.org