Scaling AI/ML deployments can be resource-limited and administratively complex while requiring expensive resources for hardware acceleration. Popular cloud platforms offer scalability and attractive tool sets, but those same tools often lock users in, limiting architectural and deployment choices. With Red Hat® OpenShift® Data Science (RHODS), data scientists and developers can rapidly develop, train, test, and iterate ML and DL models in a fully supported environment—without waiting for infrastructure provisioning. Red Hat OpenShift Service on AWS (ROSA) which is a turnkey application platform that provides a managed application platform service running natively on Amazon Web Services (AWS).
-
-
Articles récents
- Building a Sovereign GenAI Stack for the United Nations with Intel and OPEA
- Accelerating vLLM Inference: Intel® Xeon® 6 Processor Advantage over AMD EPYC
- KVCrush: Rethinking KV Cache Alternative Representation for Faster LLM Inference
- Scaling AI with Confidence: Lenovo’s Approach to Responsible and Practical Adoption
- Unlocking AI-Driven Media Monetization with Intel® Xeon® CPUs and Broadpeak BannersIn2
-
Neural networks news
Intel NN News
- Accelerating vLLM Inference: Intel® Xeon® 6 Processor Advantage over AMD EPYC
The vLLM (Virtualized Large Language Model) framework, optimized for CPU inference, is emerging as […]
- Building a Sovereign GenAI Stack for the United Nations with Intel and OPEA
The United Nations (UN) has taken a bold step toward digital sovereignty by developing an […]
- KVCrush: Rethinking KV Cache Alternative Representation for Faster LLM Inference
Developed by Intel, KVCrush can improve LLM inference throughput up to 4x with less than 1% […]
- Accelerating vLLM Inference: Intel® Xeon® 6 Processor Advantage over AMD EPYC
-