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A neural-network-based controller adapts in real time to switching reference signals in piezoelectric nano-positioning stages, reducing tracking errors.
by Kevin Max, Ismael Jaras, Arno Granier, Katharina A. Wilmes, Mihai A. Petrovici Neural responses to mismatches between expected and actual stimuli have been widely reported acro...
A collaborative research group has shown that biological neurons can be trained to perform a temporal pattern learning task that was previously carried out by artificial systems.
Researchers have successfully trained living biological neurons to perform complex machine learning tasks. By using microfluidic devices and "FORCE learning," the team demonstrated...
Efficiency, Adaptation, and the Future of Intelligent SystemsContinue reading on Medium »
The intricate dance of neurons in the brain has long fascinated scientists, driving relentless pursuit toward understanding the fundamental principles of neural computation. A grou...
Brain cells take in many signals through thousands of circuit connections. A new study discerns the rules that turn inputs into a functional arrangement for neurons that process vi...
A groundbreaking advancement in nano-positioning technology has been unveiled by a team of researchers from Huazhong University of Science and Technology and the University of Vict...
A new study introduces AI-based "neural network" controllers that stabilize renewable energy grids. By mimicking human brain processing, the AI reduces the need for physical sensor...
Engineers at Northwestern University have taken a striking leap toward merging machines with the human brain by printing artificial neurons that can actually communicate with real...
Nature Nanotechnology, Published online: 15 April 2026; doi:10.1038/s41565-026-02149-6Printed MoS2 memristive networks yield spiking neurons with multi-order complexity. Thermally...
Researchers are increasingly exploring a future in which robots and AI systems do not operate as isolated machines, but instead learn collectively across connected networks – shari...
by Jacopo Fadanni, Rosalba Pacelli, Alberto Zucchetta, Pietro Rotondo, Michele Allegra The rapid surge in the number of simultaneously recorded neurons demands reliable tools to e...
So I was reading about this study the other night (as one does 🫠), the one where researchers mapped every single neuron of a fruit fly…Continue reading on Medium »
New research challenges the long-held belief that the brain makes decisions in a simple, top-down hierarchy. By discovering decision-making signals in the primary somatosensory cor...
Why it mattersContinue reading on Medium »
Nature Nanotechnology, Published online: 18 May 2026; doi:10.1038/s41565-026-02186-1Artificial neurons based on printed molybdenum disulfide nanosheet networks achieve multi-order...
by Sami Mollard, Sander M. Bohte, Pieter R. Roelfsema Natural scenes usually contain many objects that need to be segregated from each other and the background. Object-based atten...
by Jaesung Choi, Athokpam Langlen Chanu, Shakul Awasthi Intracellular calcium ions (Ca2+) exhibit diverse dynamical behaviors linked with cellular physiological states related to...
What is the Shallow Brain Hypothesis? A new study shows how subcortical pathways can make AI models more flexible and biologically accurate.
Physicists have developed a mathematical "toy model" using statistical physics to explain one of the great mysteries of deep learning: why massive neural networks learn patterns in...
История технологий часто скрывает свои самые смелые прорывы под маской субкультуры. Пока Кремниевая долина только грезила о перцептронах, в Минске конца 80-х уже функционировал про...
A new brain-inspired AI framework mimics human development by "pruning" redundant connections as it learns. The model becomes more compact and energy-efficient while mastering incr...
by Sebastian Klavinskis-Whiting, Andrew J. King, Nicol S. Harper A major goal of neuroscience is to identify general principles that can explain the diverse structures and functio...
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