Last semester, I assigned students in my energy storage systems class a problem set comparing the electrical designs of ...
It sounds like science fiction, but also strangely familiar: drones buzzing around, inspecting tomatoes in greenhouses, ...
A cell on its way to becoming skin pigment, blood, or nerve does not make that shift alone. It responds to a dense web of ...
Scientists have developed a new AI method that can work backward from patterns to uncover the hidden processes driving them.
A new approach has been proposed to address the problem of "overconfidence"—one of the most critical risks of artificial ...
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AI Researchers Are Confronting Neural Networks’ Reasoning Gaps Despite Rapid Advances
In 2026, neural networks are achieving unprecedented efficiency, multimodal integration, and workflow comprehension, yet benchmarks like MLRegTest reveal persistent struggles with formal rule learning ...
Programmable optical particle transport based on structured light plays a crucial role in microscale manipulation. Scientists ...
The future of robotics doesn’t belong to AI-first approach or mechanism-first approach. It belongs to the integration of both ...
Elevoc Technology announced that its co-founder, Professor DeLiang Wang, has been recognized in the 2025 ScholarGPS "Highly ...
Spiking Neural Networks (SNNs) represent the "third generation" of neural models, capturing the discrete, asynchronous, and energy-efficient nature of ...
The rapid ascent of large-scale artificial intelligence has provided neuroscience with a new set of powerful tools for modeling complex cognitive functions.
Machine learning's transformative shift mirrors the MapReduce moment, revolutionizing efficiency with decentralized consensus ...
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