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Communications of the ACM2d
Empowering Sustainability in the Energy Sector through AI
The results are really astonishing. Tests show that offices save up to 37% on their energy bills with AI-optimized and ...
Predicting 'sleep learning': Neural activity patterns reveal conditions for strengthening synaptic connections
In the cerebral cortex, numerous neurons exchange information through junctions known as synapses. The strength of each ...
Tech Xplore on MSN4d
New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...
Op-Ed: LENS neuromorphic robotics — The Next Big Thing in tech, and there’s no avoiding it
Robots don’t have to be humanoid, but they do have to interact with humans. That is a problem, and the solutions must be ...
Brains over bots: Why toddlers still beat AI at learning language
Even the smartest machines can't match young minds at language learning. Researchers share new findings on how children stay ...
Tech Xplore on MSN2d
Multimodal LLMs and the human brain create object representations in similar ways, study finds
A better understanding of how the human brain represents objects that exist in nature, such as rocks, plants, animals, and so ...
IEEE24d
Development of Few-Shot Learning Capabilities in Artificial Neural Networks When Learning Through Self-Supervised Interaction | IEEE Journals & Magazine | IEEE Xplore
Most artificial neural networks used for object recognition are trained in a fully supervised setup. This is not only resource consuming as it requires large data sets of labeled examples but also ...