Nvidia's ProRL Agent Decouples Training from Rollout. That Changes How Agentic AI Gets Built. Stop chasing common trends. Get C-Level insights and independent analysis on AI, SaaS, and how technology drives verifiable revenue growth.

Nvidia's ProRL Agent solves a quiet but expensive AI problem.

Training an AI agent requires two very different workloads running at the same time. They've been forced together. ProRL Agent separates them.

www.shashi.co/2026/03/nvid...

#AI #AgenticAI #Nvidia #MLInfrastructure

Most mature orgs end up with a hybrid. The interesting part isn't which algorithm wins. It's how teams build trust in the rules.

#MLOps #GPUCompute #MachineLearning #MLInfrastructure

Peloton: Uber's Unified Resource Scheduler for Diverse Cluster Workloads | Uber Blog Uber developed Peloton to help us balance resource use, elastically share resources, and plan for future capacity needs.

#MLOps #PlatformEngineering #Kubernetes #MLInfrastructure

- Shopify Skypilot: shopify.engineering/skypilot

- Microsoft Philly: www.usenix.org/system/file...

- Uber Peloton: www.uber.com/blog/resour...

- UCSD DSMLP: support.ucsd.edu/services?id...

Can jobs queue (not crash) when capacity is short? Adept hit this gap with orchestration vs Slurm.

Do you measure GPU busy vs allocated, not just "utilisation"?

Is preemption a documented promise users can plan around?

#MLOps #PlatformEngineering #MLInfrastructure #GPU

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Scaling ML initiatives or building teams focused on #DataOps and #MLInfrastructure?

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