"I put it in the model, this is GPT-5, and it answered it perfectly," Altman said, saying it gave him a "weird feeling" to ...

Signal bias and social noise are persistent threats. Vocal minorities, bots and echo chambers can distort the picture.

The model reveals that more connected brain regions are more prone to damage, while isolated areas remain resilient. This approach offers a powerful framework for understanding disease progression and ...

Flood modeling in arid environments like Saudi Arabia is constrained by the absence of reliable hydrological datasets and extreme variability in topography. To overcome these limitations, the study ...

MIT researchers developed SEAL, a framework that lets language models continuously learn new knowledge and tasks.

A Tribune reporter and data nerd went looking for a smarter way to evaluate and draft NBA players. From Cooper Flagg to a few under-the-radar risers, here's what he found.

This is of limited utility as models don't have an inherent understanding of JSON. The Host application has been written in advance to intercept the Structured Output and provide some form of ...

In the college baseball's new data age, standing still isn't an option. As Jacob Rudner reports, top programs have leaned heavily into analytics and models.

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.

AI tools can expose your personal data. Tech expert Kurt “CyberGuy" Knutsson helps you learn the risks and how to protect your privacy.

AI’s growth is limited by poor-quality data, not model size. Human expertise in data curation, decentralized feedback and ethical oversight is essential for building trustworthy, high-performing AI.