A new study shows LLMs introduce more vulnerabilities with each code iteration, highlighting critical risks for CISOs and the need for skilled human oversight.

Army streamlines bureaucracy, collapses acquisition offices, and empowers leaders to accelerate delivery of cutting-edge technologies to the joint force.

Google DeepMind introduced SIMA 2, the latest iteration of its generalist AI research, building on last year’s SIMA (Scalable ...

Data analytics are transforming how casinos understand and interact with players. At Millioner Casino, these insights help ...

GPT-5 looks strong in theory, but daily coding needs speed, low cost, and steerability. See which models win and how to guide ...

Build a niche AI SaaS people will pay for. Learn the stack, from Lovable.dev and Supabase to Replicate, tips for security, ...

James Glover, principal and finance transformation AI leader at Deloitte, emphasized that AI must align with a company’s core ...

State-level enthusiasm for AI regulation has surged in the absence of a unified, national approach, but some state leaders ...

Canon's Utsunomiya factory is home to the company's highest-end manufacturing facilities as well as its lens development ...

The rapid development and integration of artificial intelligence (AI), including predictive, generative, and emerging agentic ...

A leading research and market intelligence firm found that on average, only 48 percent of AI projects progress to the ...

Researchers from Standford, Princeton, and Cornell have developed a new benchmark to better evaluate coding abilities of large language models (LLMs). Called CodeClash, the new benchmark pits LLMs ...