Over a decade ago, when I was first starting to pretend I could write about quantum mechanics, I covered a truly bizarre experiment. One half of a pair of entangled photons was sent through a device ...

A significant shift is under way in artificial intelligence, and it has huge implications for technology companies big and small. For the past half-decade, most of the focus in AI has been on training ...

While the tech world obsesses over headlines about the $100 million price tag to train GPT-4, the real economic story is happening in inference: the ongoing cost of actually running AI models in ...

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...

The creators of the open source project vLLM have announced that they transitioned the popular tool into a VC-backed startup, Inferact, raising $150 million in seed funding at an $800 million ...

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

As frontier models move into production, they're running up against major barriers like power caps, inference latency, and rising token-level costs, exposing the limits of traditional scale-first ...

Please join the JHU CFAR Biostatistics and Epidemiology Methodology (BEM) Core on Thursday, September 4, 2025, from 2-3 pm ET for a session covering the fundamentals of causal inference. If you have ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...