Browsing: Artificial

GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting…

The increasing demand for future digital technologies and high-temperature neuromorphic hardware will rely on non-volatile behavior and power efficiency. High-temperature…

An encoder (optical system) maps objects to noiseless images, which noise corrupts into measurements. Our information estimator uses only these…

Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial…

Fluorescence nanoscopy has opened a new frontier for visualizing and understanding polymeric and fibrous materials with molecular precision. Building on…

× Predicting Ego-centric Video from human Actions (PEVA). Given past video frames and an action specifying a desired change in…

What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting…

In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer. Unlike traditional…

Scientists at the USC Viterbi School of Engineering and the School of Advanced Computing have created artificial neurons that reproduce…

Every generative AI system, no matter how advanced, is built around prediction. Remember, a model doesn’t truly know facts—it looks…