The Most Counterintuitive Way to Build a Brain

Get a 20% discount to my favorite book summary service at https://shortform.com/artem ===== My name is Artem, I'm a neuroscience PhD student at Harvard University. 🌎 Website and Social links: https://kirsanov.ai/ 📥 "Receptive Field" neuro-newsletter: https://artemkirsanov.substack.com/ ✨ Support me on Patreon to get access to Discord community:   / artemkirsanov   ===== In this video, we explore Reservoir Computing: a radical approach to recurrent neural networks inspired by how biological brains might actually work. Instead of precisely engineering every connection in the network to produce perfectly-tuned dynamics, we leave a random bucket of neurons untouched and simply learn to "listen" to it in the right way, reducing a complex learning problem to linear regression. The secret behind why this works turns out to be deeply connected to Fourier's 200-year-old insight about building any signal from simple building blocks. 🕒 OUTLINE: 00:00 Introduction 01:04 Recurrent Neural Networks 03:09 Echo-State Property 05:36 Sponsor: Shortform 06:36 Reservoir Computing Paradox 09:28 Why it works at all 12:00 Putting it together ===== Icons by Freepik and Biorender Music by Artlist This video was sponsored by Shortform ===== Disclaimer: This channel is my personal project. The views and content expressed here are my own and are separate from my research role at Harvard University.