Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

no code implementations • 15 Oct 2022 • Anthony Zador, Blake Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Koerding, Alexei Koulakov, Yann Lecun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

Neuroscience has long been an important driver of progress in artificial intelligence (AI).

Gaussian Gated Linear Networks

1 code implementation • NeurIPS 2020 • David Budden, Adam Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness

We propose the Gaussian Gated Linear Network (G-GLN), an extension to the recently proposed GLN family of deep neural networks.

Denoising Density Estimation +2

Product Kanerva Machines: Factorized Bayesian Memory

no code implementations • 6 Feb 2020 • Adam Marblestone, Yan Wu, Greg Wayne

An ideal cognitively-inspired memory system would compress and organize incoming items.

Towards an integration of deep learning and neuroscience

no code implementations • 13 Jun 2016 • Adam Marblestone, Greg Wayne, Konrad Kording

We hypothesize that (1) the brain optimizes cost functions, (2) these cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior.

Neurons and Cognition