3D printing has matured from a speculative sci-fi fantasy into a practical tool.

The vision system scanned the part and logged a pass. The SPC chart stayed inside its control limits. The line kept moving.

The premise of AI large language models (LLMs) is that any problem can be solved by vacuuming up as much information as possible, running it through probability models, and performing complex calculations to make predictions and come up with the optimal solution.

The deployment of automated software systems called AI agents has recently exploded.

Whether you’re a researcher stumped by a mystery compound or a manufacturer perplexed by an unknown substance, there’s a major resource you can rely on: a library of chemical fingerprints, known as mass spectra, that the National Institute of Standards and T

Manufacturers are exploring artificial intelligence, but most are still struggling to scale it across operations.

Every boardroom has heard it. Every procurement checklist includes it. Every investor deck now features it somewhere between the mission statement and the revenue model. “AI ethics” has become the term that signals seriousness without necessarily delivering it.

Two years ago, the dominant conversation around AI in enterprise software was about pilots.

Researchers at the U.S. Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) have created a new tool that can catch and correct potential mistakes in real time while 3D-printing large plastic parts.

Artec 3D is best known for professional 3D scanners.