AI tools may slow down experienced developers instead of boosting productivity, according to a 2025 experiment.

From adoption to optimization, the next phase will drive innovation without compromising efficiency and sustainability.

AI regulation and risk governance have evolved from niche concerns to board-level priorities in under three years.

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine a rising interest in parsing out ...

In artificial intelligence, 2025 marked a decisive shift. Systems once confined to research labs and prototypes began to ...

Z.ai released GLM-4.7 ahead of Christmas, marking the latest iteration of its GLM large language model family. As open-source models move beyond chat-based applications and into production ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

As artificial intelligence tools move from testing to daily use, a shift is taking place across small and medium-sized ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...

Nearly every SaaS product is either integrating AI or planning to do so. However, the term “AI” has become so broad that it’s ...

Giant AI data centers are causing some serious and growing problems – electronic waste, massive use of water (especially in ...

The future of AI isn’t in a distant server farm – it’s in your pocket, finally awake, and it doesn’t need Wi-Fi to prove it, ...