Modern AI systems are no longer built around a single model that handles every task. Instead, they rely on collections of models, each designed for specific purposes. At the center of this setup is ...

Overview: Building AI models begins with clear goals, clean data, and selecting appropriate algorithms.Beginners can use tools like Python, scikit-learn, and Te ...

The Midwestern Regional Climate Center (MRCC) recently launched a searchable, downloadable archive of 19th-century weather records. Pulled from more than 450 U.S. observation stations, including over ...

The extracted features from both modalities are concatenated and passed through a fully connected classifier to generate the final prediction. This architecture is designed to handle multi-modal data ...

A strategy has been proposed for designing stable and high-performance oxygen evolution reaction (OER) catalysts, specifically for neutral seawater splitting. A promising series of dopants (Fe, Ni, V, ...

The new science of “emergent misalignment” explores how PG-13 training data — insecure code, superstitious numbers or even extreme-sports advice — can open the door to AI’s dark side.

With that in mind, here are some early warning signs that have popped up since the start of training camp and throughout the first full week of preseason games.

Microsoft has launched Copilot 3D, a free AI tool to create 3D models from images. Early tests show promise for simple objects but comical failures on complex subjects.

The splashy stuff is fun, but the reality is some of those lower-dollar steals can make a huge difference. Now that teams are deep into training camp, we can begin to identify some of those coups.

The Michigan football team is down a running back a week into training camp. CJ Hester, a transfer from UMass, departed the program this week and will not be part of the team in 2025, spokesman ...