Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...

The evolution of AI-powered vehicle inspection has moved rapidly from experimental research to an essential pillar of the modern automotive ecosystem. Historically, vehicle checks were manual and ...

From Deep Blue to modern AI, how chess exposed the shift from brute-force machines to learning systems, and why it matters AI ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

As a national leader in applied technology education, Pennsylvania College of Technology is built for a global economy driven ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Ultimately, the goal is to empower the automotive industry with smarter, more efficient technology. By focusing on full-stack ...

Sandhu claims that Chandigarh University doesn’t use AI to replace a student’s learning journey but to identify students' ...

Mobile robots must continuously estimate their position to navigate autonomously. However, satellite-based navigation systems are not always reliable: signals may degrade near buildings or become ...