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 ...

How does artificial intelligence continue to improve its capabilities? For a long time, expanding model size has been regarded as an important way to ...

Can AI learn by shrinking? A new study introduces a development-inspired continual learning framework for spiking neural ...

The advent of high-density recording technologies, such as Neuropixels and large-scale calcium imaging, has provided an unprecedented look into the ...

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 ...

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 living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir ...

The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...