Continual learning in neural networks addresses the challenge of adapting to new information accumulated over time while retaining previously acquired knowledge. A central obstacle to this process is ...
Morning Overview on MSN
Brain-inspired AI pruning boosts learning while shrinking model size
A human infant is born with roughly twice as many synapses as it will eventually need. Over the first few years of life, the ...
Can AI learn by shrinking? A new study introduces a development-inspired continual learning framework for spiking neural ...
How does artificial intelligence continue to improve its capabilities? For a long time, expanding model size has been regarded as an important way to ...
Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...
The advent of high-density recording technologies, such as Neuropixels and large-scale calcium imaging, has provided an unprecedented look into the ...
Tech Xplore on MSN
Living brain cells enable machine learning computations
A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...
Can living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir ...
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