Instead of moving all data to a distant AI core, the AI Grid moves intelligence closer to where data is created and consumed.

Georgia Tech researchers have created a new AI model for decision-focused learning (DFL), called Diffusion-DFL. Recent tests ...

The Automotive Edge Computing Consortium (AECC) today announced the release of its latest white paper, "Data-First Architecture for Data-Driven Automotive Service Development." Developed by the AECC ...

If networks remain ZTE’s core business and foundation, computing power is emerging as its next growth engine. In 2025, ZTE ...

Powerful edge computing alone cannot deliver the full potential of agentic AI. Without equally sophisticated networking, ...

Open-Source Systems, Including Apache Spark, Delta Lake, and MLflow Redefined Data Processing and Enabled Modern AI at ...

Strategic investment facilitates collaboration on next-generation AI infrastructure optimized for memory-intensive ...

Abstract: The dynamic and distributed nature of the Cloud Edge Computing Continuum (CECC) necessitates innovative approaches to application profiling for microservices-based applications. Existing ...

Kubernetes wasn't built for GPUs, but new tools like Kueue and MIG are finally helping companies stop wasting money on expensive, idle AI infrastructure.

As organizations expand their use of cloud services, many are discovering that operating across multiple providers can quickly get complicated. While multicloud strategies can improve flexibility and ...

For the past several years, AI, along with related concepts such as LLMs and ML, has been among the most prevalent technologies in popular culture. The demand for more research into AI has risen, but ...