NeuroAI and Beyond

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Authors: Jean‐Marc Fellous, Gert Cauwenberghs, Cornelia M. Fermuller, Yulia Sandamisrkaya, Terrence J. Sejnowski A B
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Abstract

Neuroscience and Artificial Intelligence (AI) have made significant progress in the past few years but have only been loosely inter-connected. Based on a workshop held in August 2025, we identify current and future areas of synergism between these two fields. We focus on the subareas of embodiment, language and communication, robotics, learning in humans and machines and Neuromorphic engineering to take stock of the progress made so far, and possible promising new future avenues. Overall, we advocate for the development of NeuroAI, a type of Neuroscience-informed Artificial Intelligence that, we argue, has the potential for significantly improving the scope and efficiency of AI algorithms while simultaneously changing the way we understand biological neural computations. We include personal statements from several leading researchers on their diverse views of NeuroAI. Two Strength-Weakness-Opportunities-Threat (SWOT) analyses by researchers and trainees are appended that describe the benefits and risks offered by NeuroAI.

Fields of Study & Subjects

Cognitive Computing and Networks Neural Networks and Applications Artificial Intelligence Applications

Publication details

Journal / source
arXiv (Cornell University)
Publication date
27 January 2026
Document type
Preprint