Abstract: Efficient detection of infrared small targets in complex backgrounds is of great significance for infrared search and track systems. Existing methods generally perform well in simple ...

Speaking at WSJ Opinion Live in Washington, D.C., WSJ Editorial Page Editor Paul Gigot and SandboxAQ CEO Jack Hidary discuss Large Quantitative Models (LQMs) and their role in AI applications, the ...

Our long-term goal is to build efficient and reliable 2.5B diffusion-based decoding for document OCR. MinerU-Diffusion reframes document OCR as an inverse rendering problem and replaces slow, ...

Abstract: With the rapid advancement of Internet of Things (IoT) technology, its widespread application has led to numerous conveniences; however, it also presents significant security challenges.

MIT estimated the computing power for 809 large language models. Total compute affected AI accuracy more than any algorithmic tricks. Computing power will continue to dominate AI development. It's ...

Purpose: The purpose of this study was to evaluate the effectiveness of implementation of an FDA-cleared artificial intelligence (AI) solution (Aidoc, Tel Aviv, Israel) for detecting intracranial ...

Quantum sensors are transforming how we measure and navigate, offering levels of precision far beyond classical systems. By exploiting atomic superposition, cold atom interferometers, and diamond NV ...

The American Clinical Neurophysiology Society updated its guidelines on continuous EEG monitoring last year, providing support for the use of the technology in neonates at high risk for seizures.

How far can we push large language model speed by reusing “free” GPU compute, without giving up autoregressive level output quality? NVIDIA researchers propose TiDAR, a sequence level hybrid language ...

Background: Wearable devices can capture 1-lead ECGs but are primarily used for detecting rhythm disorders. AI deployed on these ECGs could enable scalable detection of structural heart diseases (SHDs ...