A newly developed AI control system using neuron-inspired learning enables soft robotic arms to learn a broad set of motions ...

Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers redesigned AI systems to better resemble biological brains, some models produced ...

The nervous system does an astonishing job of tracking sensory information, and does so using signals that would drive many computer scientists insane: a noisy stream of activity spikes that may be ...

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 ...

Abstract: The paper focuses on the development of a software program for creating and training ANN (artificial neural network) models. This program allows users to create their own ANN models without ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...