Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...

This matchup promises to be a battle of styles and efficiency, with the Celtics holding a +7.2 net rating compared to the ...

Across red states and blue, a grassroots movement is pushing back on the unchecked growth of the artificial intelligence industry.

Here is a blueprint for architecting real-time systems that scale without sacrificing speed. A common mistake I see in early-stage personalization teams is trying to rank every item in the catalog in ...

The latest Gemini model makes impressive strides in benchmarks, but forthcoming models could give it a reality check.

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

When we talk about the cost of AI infrastructure, the focus is usually on Nvidia and GPUs -- but memory is an increasingly ...

Poorly aligned data is typically seen as an obstacle to enterprise AI adoption, but is this the wrong way to look at things?

Abstract: Inspired by soft-bodied animals, soft continuum robots provide inherently safe and adaptive solutions in robotics, especially suited for applications requiring gentle interactions. However, ...

Abstract: This paper presents D-band channel modeling campaigns for short-range line-of-sight (LOS) communications in representative data center and industrial environments. An accurate multipath ...