newsRed Hat AITrust 88 · LabPublished 13d agoLive · 11d ago
Scaling agentic AI: How llm-d enables infrastructure sovereignty
AI is entering the era of large-scale, distributed, agentic systems. Applications coordinate multiple models, tools, and services, process millions of requests, and demand enormous amounts of computer capacity. At the same time, infrastructure costs continue to climb, and access to AI hardware remains constrained by supply chains, vendor roadmaps, and rapidly evolving accelerator technologies.For many organizations, this creates a new kind of dependency. They've embraced open models and retained
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- PossiblePossibly related (embedding) · 67%Productive-Superintelligence/lllm →
- PossiblePossibly related (embedding) · 67%agentuniverse-ai/agentUniverse →
- PossiblePossibly related (embedding) · 65%dynamiq-ai/dynamiq →
- PossiblePossibly related (embedding) · 64%Agents in the Wild: Where Research Meets Deployment →
- PossiblePossibly related (embedding) · 64%10xHub/Agentflow →
- PossiblePossibly related (embedding) · 58%roy-tong/AgentMeasure →
