Coding tools are becoming an increasingly big target for Google and Microsoft as they try to catch up to Anthropic and OpenAI.

Introduction Artificial intelligence has become one of the strongest investment themes in technology history. Since the emergence of generative AI, investors have poured billions of dollars into companies positioned to benefit from the enormous infrastructure spending required to train and deploy increasingly sophisticated AI models.

Existing generative AI models are built on batch processing: You give the system instructions; it runs computations; then spits back the results. Now comes a Silicon Valley startup that says it can produce gen-AI video (and other outputs) in real time — a potentially groundbreaking advance: San Francisco-based Reactor,

Nearly four years after OpenAI's ChatGPT first launched, one in six people worldwide is now using generative AI tools, according to Microsoft's 2025 AI Diffusion report. That includes 28 percent of the U.

Generative AI makes stuff up. It can be biased. Sometimes it spits out toxic text. So can it be “safe”? Rick Caccia, the CEO of WitnessAI, believes it can. “Securing AI models is a real problem, and it’s one that’s especially shiny for AI ...

President Donald Trump has signed an executive order asking that certain AI companies to let the government review their new models.

At a deeper level, AI has tended to be perceived as a technology deployment rather than an enterprise capability.

We need more empirical studies about the impact of generative AI on our mental health. I dissect one recent study to show counterintuitive results. An AI Insider scoop.

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations prepare, manage, and move their data. AI-ready data platforms, vector databases,