Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...

The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. Feburary 9, 2026: 🔥 We released a free interactive demo ...

Lab-grown “reductionist replicas” of the human brain are helping scientists understand fetal development and cognitive disorders, including autism. But ethical questions loom. Brain organoids, which ...

Abstract: Significant advancements in deep learning have been made possible by the utilization of large datasets, underscoring the critical importance of copyright protection. Adding meticulously ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

When Democratic lawmakers left Texas to try to prevent the Republican-led Legislature from redrawing the state's congressional districts, it marked the latest episode in a long national history of ...

Artificial intelligence models can secretly transmit dangerous inclinations to one another like a contagion, a recent study found. Experiments showed that an AI model that’s training other models can ...

In Catholic churches across Manhattan and Brooklyn, Salomé captivated the congregation, uplifting the faithful with her soulful singing and skilled organ playing. The New York Archdiocese Organist ...