<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>#mlops | CurrentStack</title><description>Articles tagged with #mlops on CurrentStack.</description><link>https://currentstack.io/</link><language>en-us</language><item><title>KubeCon 2026 Inference Shift: A Platform Playbook for Dapr Agents and Kubernetes AI Runtime</title><link>https://currentstack.io/stories/kubecon-ai-inference-dapr-agents-platform-playbook-2026/</link><guid isPermaLink="true">https://currentstack.io/stories/kubecon-ai-inference-dapr-agents-platform-playbook-2026/</guid><description>How to prepare Kubernetes platforms for inference-heavy workloads with durable agent orchestration, GPU scheduling, and reliability guardrails.</description><pubDate>Mon, 30 Mar 2026 00:00:00 GMT</pubDate><category>kubernetes</category><category>ai</category><category>platform-engineering</category><category>site-reliability</category><category>mlops</category></item><item><title>TurboQuant and the New Quantization Race: A Production Playbook for LLM Teams</title><link>https://currentstack.io/stories/turboquant-llm-quantization-production-playbook-2026/</link><guid isPermaLink="true">https://currentstack.io/stories/turboquant-llm-quantization-production-playbook-2026/</guid><description>Reports of major compression advances renew the quantization race. Here is a practical path to ship lower-cost inference without quality collapse.</description><pubDate>Sun, 29 Mar 2026 00:00:00 GMT</pubDate><category>ai</category><category>llm</category><category>performance</category><category>mlops</category><category>architecture</category></item><item><title>Small Model Edge Voice Inference: Production Guide for 2026</title><link>https://currentstack.io/stories/small-model-edge-voice-inference-production-guide-2026/</link><guid isPermaLink="true">https://currentstack.io/stories/small-model-edge-voice-inference-production-guide-2026/</guid><description>A practical architecture for deploying low-latency small voice models at the edge with observability, fallback strategy, and cost discipline.</description><pubDate>Sat, 28 Mar 2026 00:00:00 GMT</pubDate><category>ai</category><category>edge</category><category>mlops</category><category>performance</category><category>platform-engineering</category><category>reliability</category></item><item><title>Defense AI Contracts at Scale: Software Assurance Controls from Day One</title><link>https://currentstack.io/stories/defense-ai-contracts-software-assurance-playbook-2026/</link><guid isPermaLink="true">https://currentstack.io/stories/defense-ai-contracts-software-assurance-playbook-2026/</guid><description>Large defense AI procurement deals demand modern software assurance, from secure MLOps baselines to reproducible model governance and audit-ready delivery.</description><pubDate>Sun, 15 Mar 2026 00:00:00 GMT</pubDate><category>ai</category><category>security</category><category>compliance</category><category>mlops</category><category>enterprise</category></item><item><title>Hardware-Aware LLM Selection: Turning Model Choice Into an SRE Discipline</title><link>https://currentstack.io/stories/hardware-aware-llm-selection-ops/</link><guid isPermaLink="true">https://currentstack.io/stories/hardware-aware-llm-selection-ops/</guid><description>Why teams need reproducible model-to-hardware routing policies as local inference and heterogeneous fleets expand.</description><pubDate>Sun, 08 Mar 2026 00:00:00 GMT</pubDate><category>ai</category><category>mlops</category><category>platform-engineering</category><category>performance</category><category>reliability</category></item><item><title>Sovereign AI Procurement in 2026: Building an Evaluation Stack Before Rollout</title><link>https://currentstack.io/stories/sovereign-ai-procurement-evaluation-stack/</link><guid isPermaLink="true">https://currentstack.io/stories/sovereign-ai-procurement-evaluation-stack/</guid><description>A practical framework for governments and regulated enterprises evaluating domestic AI models for broad internal deployment.</description><pubDate>Sun, 08 Mar 2026 00:00:00 GMT</pubDate><category>ai</category><category>enterprise</category><category>compliance</category><category>platform</category><category>mlops</category></item></channel></rss>