Recent advances and future prospects for memristive materials, devices, and systems

MK Song, JH Kang, X Zhang, W Ji, A Ascoli… - ACS …, 2023 - ACS Publications
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

The grand challenges of Science Robotics

GZ Yang, J Bellingham, PE Dupont, P Fischer… - Science robotics, 2018 - science.org
One of the ambitions of Science Robotics is to deeply root robotics research in science while
develo** novel robotic platforms that will enable new scientific discoveries. Of our 10 …

A framework for intelligence and cortical function based on grid cells in the neocortex

J Hawkins, M Lewis, M Klukas, S Purdy… - Frontiers in neural …, 2019 - frontiersin.org
How the neocortex works is a mystery. In this paper we propose a novel framework for
understanding its function. Grid cells are neurons in the entorhinal cortex that represent the …

Designing ecosystems of intelligence from first principles

KJ Friston, MJD Ramstead, AB Kiefer… - Collective …, 2024 - journals.sagepub.com
This white paper lays out a vision of research and development in the field of artificial
intelligence for the next decade (and beyond). Its denouement is a cyber-physical …

The role of monoamine oxidase A in the neurobiology of aggressive, antisocial, and violent behavior: A tale of mice and men

NJ Kolla, M Bortolato - Progress in neurobiology, 2020 - Elsevier
Over the past two decades, research has revealed that genetic factors shape the propensity
for aggressive, antisocial, and violent behavior. The best-documented gene implicated in …

Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits

L Khacef, P Klein, M Cartiglia, A Rubino… - Neuromorphic …, 2023 - iopscience.iop.org
Understanding how biological neural networks carry out learning using spike-based local
plasticity mechanisms can lead to the development of real-time, energy-efficient, and …

Predictive learning shapes the representational geometry of the human brain

A Greco, J Moser, H Preissl, M Siegel - Nature Communications, 2024 - nature.com
Predictive coding theories propose that the brain constantly updates internal models to
minimize prediction errors and optimize sensory processing. However, the neural …

A thousand brains: toward biologically constrained AI

KJ Hole, S Ahmad - SN Applied Sciences, 2021 - Springer
This paper reviews the state of artificial intelligence (AI) and the quest to create general AI
with human-like cognitive capabilities. Although existing AI methods have produced …

[LLIBRE][B] The singularity is nearer: When we merge with AI

R Kurzweil - 2024 - books.google.com
AN INSTANT NEW YORK TIMES BESTSELLER ONE OF TIME'S 100 MOST INFLUENTUAL
PEOPLE IN ARTIFICIAL INTELLIGENCE The noted inventor and futurist's successor to his …

Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks

N Garau, N Bisagno, Z Sambugaro… - Proceedings of the …, 2022 - openaccess.thecvf.com
Deep neural networks achieve outstanding results in a large variety of tasks, often
outperforming human experts. However, a known limitation of current neural architectures is …