MLOps & Infrastructure
All things MLOps & Infrastructure on Edge.
Scaling Item Knowledge with JD's Oxygen AIIC Platform
JD.com's Oxygen AIIC uses a hybrid LLM/VLM architecture to automate item-knowledge production at scale, achieving 94.2% precision and 82.8% recall across tens of billions of SKUs.
Building Deterministic Infrastructure for Autonomous AI Agents
Reliability in agentic systems is an infrastructure challenge, not a model one. To scale agents, you must build a 'control plane' that separates model reasoning from production execution via validation, policy enforcement, and circuit breakers.
Why Ford Reintegrated Human Expertise After AI Quality Failures
Ford rehired 350 veteran engineers to address quality issues caused by over-reliance on automated AI systems, resulting in significant cost savings and improved quality rankings.
Scaling Enterprise AI: HP's Frontier Operating Model
HP is scaling AI across its enterprise by using OpenAI's Frontier platform to unify governance, context, and deployment, moving from isolated pilot successes to a repeatable, production-ready operating model.
Automating Weekly Releases with AI and Human-in-the-Loop
Hugging Face reduced release cycles from 6 weeks to 1 week by using a 'trust-but-verify' pipeline where open-weights models draft release notes and deterministic scripts enforce accuracy, keeping a human in the loop only for final review.
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