It is almost certainly not a coincidence that a networking expert at Google has risen to the top to be put in charge of the infrastructure development at the search engine, advertising, and now AI ...

Google is dedicating a chip to running artificial intelligence models, and a separate processor to training models. Amazon is pursuing a similar strategy, as both companies take on Nvidia by offering ...

Maryland has become the first state in the U.S. to ban stores from engaging in dynamic pricing, a controversial practice gaining traction at retailers nationwide. Gov. Wes Moore first introduced the ...

The company says its new architecture marks a shift from training-focused infrastructure to systems optimized for continuous, low-latency enterprise AI workloads. 2026 is predicted to be the year that ...

Abstract: There is a high demand for system reliability in the field of avionics. With the increase in system complexity, it is becoming increasingly difficult to analyze the reliability of integrated ...

Adapting to the addressee is crucial for successful explanations, yet poses significant challenges for dialog systems. We adopted the approach of treating explanation generation as a non-stationary ...

Arrcus launched a new network fabric layer targeted at potential traffic bottlenecks caused by the growing use of AI inferencing services. The Arrcus Inference Network Fabric (AINF) is designed to ...

Lotteries are hard to win. The odds of hitting the Powerball jackpot are so tiny that, as a CNN commenter once put it, you have a better chance of becoming an astronaut, dating a supermodel, and ...

The multibillion-dollar deal shows how the growing importance of inference is changing the way AI data centers are designed and operated. OpenAI has signed a multibillion-dollar agreement to buy ...

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...

Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...