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Recent advances and future prospects for memristive materials, devices, and systems
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
The grand challenges of Science Robotics
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 …
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
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 …
understanding its function. Grid cells are neurons in the entorhinal cortex that represent the …
Designing ecosystems of intelligence from first principles
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 …
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
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 …
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
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 …
plasticity mechanisms can lead to the development of real-time, energy-efficient, and …
Predictive learning shapes the representational geometry of the human brain
Predictive coding theories propose that the brain constantly updates internal models to
minimize prediction errors and optimize sensory processing. However, the neural …
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 …
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 …
PEOPLE IN ARTIFICIAL INTELLIGENCE The noted inventor and futurist's successor to his …
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks
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 …
outperforming human experts. However, a known limitation of current neural architectures is …