After hosting a webinar with Gunjan Shah, a former Senior Cloud Engineer, AI and Machine Learning at Google, analysts at Bernstein provided their thoughts on the amount of memory AI data centers ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

The rapid acceleration of artificial intelligence has pushed demand for high-performance GPUs far beyond global supply. These ...

Artificial intelligence has grown so large and power hungry that even cutting edge data centers strain to keep up, yet a technique borrowed from quantum physics is starting to carve these systems down ...

Shadow rollouts and silent upgrades are common in mobile AI deployments. Google's release of Gemini 3 in late 2025 is a clear example of this practice. The company introduced the model to millions of ...

The $12K machine promises AI performance can scale to 32 chip servers and beyond but an immature software stack makes harnessing that compute challenging ...

Not only has Google's Gemini 3 model been trained on the company's own TPUs, but I've been using a MacBook Pro with Apple's ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

Researchers at Virginia Tech are using quantum entanglement to help AI drone swarms and robots coordinate in "signal lost" ...

Learn the right VRAM for coding models, why an RTX 5090 is optional, and how to cut context cost with K-cache quantization.