In contrast to computers, the computational and memory resources of artificial neural networks are mixed together ... and traverse the London Underground map. Visualization of a DNC trained ...

Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots ...

IMC hardware for inference of Convolution Neural Networks (CNNs), and provide methodologies for implementing the various architectural components of the IMC core. Specifically, we present methods for ...

We use this handy neural mechanism to learn, remember, solve problems and generally navigate our reality. “It’s a network ... if it was a computer, he added, with a very mechanistic perspective.

Of course, the new computer isn’t a physical piece ... DeepMind’s technique merges notions of memory with more traditional neural networks using a “controller.” The controller saves ...

Learn more A new neural-network architecture ... models (LLMs): extending their memory at inference time without exploding the costs of memory and compute. Called Titans, the architecture enables ...

An international team of researchers has designed and built a chip that runs computations directly in memory and ... data-parallelism by mapping a layer in the neural network model onto multiple ...

Artificial neural networks have found a variety of commercial applications, from facial recognition to recommendation engines. Compute-in-memory accelerators seek to improve the computational ...

not only did he provide a mathematical framework for understanding memory storage and retrieval in the human brain, he also developed one of the first recurrent artificial neural networks—the ...