The Boston startup uses AI to translate and verify legacy software for defense contractors, arguing modernization can’t come at the cost of new bugs.

There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.

Alibaba unveiled Qwen3.5, an open-weight, 397-billion-parameter mixture-of-experts model that only wakes up 17 billion neurons per prompt. The payoff? You get 60% lower inference ...

Learn why identity must be built into SaaS architecture from day one to ensure secure authentication, compliance, and scalable growth.

Homeland Security aims to combine its face and fingerprint systems into one big biometric platform—after dismantling ...

Android Authority leak says Google is testing Project Toscana, an advanced face unlock for Pixel and Chromebooks that works ...

This study is a valuable contribution that comprehensively identifies and characterizes LC3B-binding peptides through a bacterial cell-surface display screen covering approximately 500,000 human ...

A new study finds that most people, even those with exceptional face-recognition skills, struggle to tell real faces from AI-generated ones.

More details emerge on the upgraded sensor ...

Most people believe they can spot AI-generated faces, but that confidence is out of date, research from UNSW Sydney and the Australian National University (ANU) has demonstrated. With AI-generated ...

It was a rocky 10-month effort by the Milwaukee police who attempted to convince the public getting facial recognition was a positive.

When companies and governments expand data collection in the name of security, sometimes the only way you can object is to opt out. And with facial recognition, the time to object is now.