The next generation of inference platforms must evolve to address all three layers. The goal is not only to serve models ...

AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...

But the same qualities that make those graphics processor chips, or GPUs, so effective at creating powerful AI systems from scratch make them less efficient at putting AI products to work. That’s ...

Microsoft is also inviting developers and AI startups to explore model and workload optimisation with the new Maia 200 SDK.

Nvidia is aiming to dramatically accelerate and optimize the deployment of generative AI large language models (LLMs) with a new approach to delivering models for rapid inference. At Nvidia GTC today, ...

No, we did not miss the fact that Nvidia did an “acquihire” of AI accelerator and system startup and rival Groq on Christmas ...

The small form factor HPE Edgeline EL8000 is designed for AI tasks such as computer vision and natural-language processing. Later this month, HP Enterprise will ship what looks to be the first server ...

Kubernetes has become the leading platform for deploying cloud-native applications and microservices, backed by an extensive community and comprehensive feature set for managing distributed systems.

AMD is strategically positioned to dominate the rapidly growing AI inference market, which could be 10x larger than training by 2030. The MI300X's memory advantage and ROCm's ecosystem progress make ...