There are two main umbrellas of artificial intelligence, and each have their own applications and implications.

AI is not failing because the models are weak. AI is failing because organizations are. CX teams keep buying tools, launching pilots and layering chatbot strategies on top of legacy operational debt ...

AI can crank out insights at lightning speed, but without solid analytics foundations, it just amplifies noise instead of ...

As far back as 1980, the American philosopher John Searle distinguished between strong and weak AI. Weak AIs are merely useful machines or programs that help us solve problems, whereas strong AIs ...

Artificial intelligence (AI) is dominating headlines and boardroom conversations, yet most projects stall before they matter. MIT reports that 95% of generative AI pilots fail to show measurable ...

Nvidia’s results confirm strong AI infrastructure demand, but don’t settle wider bubble fears. Debt-driven data-center build-outs, not chip sales, remain a main pressure point in AI spending. However, ...