Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

Neural networks have emerged as versatile computational frameworks that mimic the functionality of biological brains, while time-delay systems capture the essence of processes where responses are ...

The work that we’re doing brings AI closer to human thinking,” said Mick Bonner, who teaches cognitive science at Hopkins.

Choosing the right blueprint can accelerate learning in visual AI systems. Artificial intelligence systems built with biologically inspired structures can produce activity patterns similar to those ...

Artificial intelligence systems that are designed with a biologically inspired architecture can simulate human brain activity before ever being trained on any data, according to new research from ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

From large language models to whole brain emulation, two rival visions are shaping the next era of artificial intelligence.

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...