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MLOps Community
The MLOps Community is where machine learning practitioners come together to define and implement MLOps.
Our global community is the default hub for MLOps practitioners to meet other MLOps industry professionals, share their real-world experience and challenges, learn skills and best practices, and collaborate on projects and employment opportunities. We are the world's largest community dedicated to addressing the unique technical and operational challenges of production machine learning systems.
Events
4:30 PM - 5:30 PM, Mar 25 GMT
Operationalizing AI Agents: From Experimentation to Production
5:00 PM - 6:00 PM, Mar 6 GMT
Coding Agents Lunch & Learn, Session 4
8:00 PM - 9:00 PM, Feb 27 GMT
Coding Agents Lunch & Learn, Session 3: Working on an AI-First Team
Content
Blog
mAIdAI is a lightweight personal AI assistant built with Google Chat, Cloud Run, and Vertex AI, designed to automate repetitive micro-tasks. By grounding the model with a local markdown context file, it provides highly personalized workflow assistance directly within your chat environment.
Mar 10th, 2026 | Views 1
Blog
This article explores how to use "Agent Skills"—simple Markdown-based context modules—to ensure AI agents strictly adhere to your team's MLOps practices and tooling preferences. By providing explicit organizational rules upfront, developers can eliminate generic boilerplate and align AI-generated code with production-grade standards.
Mar 3rd, 2026 | Views 136
Video
We present LingBot-World, an open-sourced world simulator stemming from video generation. Positioned as a top-tier world model, LingBot-World offers the following features. (1) It maintains high fidelity and robust dynamics in a broad spectrum of environments, including realism, scientific contexts, cartoon styles, and beyond. (2) It enables a minute-level horizon while preserving contextual consistency over time, which is also known as "long-term memory". (3) It supports real-time interactivity, achieving a latency of under 1 second when producing 16 frames per second. We provide public access to the code and model in an effort to narrow the divide between open-source and closed-source technologies. We believe our release will empower the community with practical applications across areas like content creation, gaming, and robot learning.
Feb 27th, 2026 | Views 100




