--- title: "The Good, the Bad, and the Blurry: A Clearer Vision for Computer Vision" newsletter: "MLOps Community" date: 2025-04-24 source: https://aaif.live/newsletters/mlopscommunity/2025-04-24-the-good-the-bad-and-the-blurry-a-clearer-vision-for-compute --- # The Good, the Bad, and the Blurry: A Clearer Vision for Computer Vision *Plus, what is MLOps?, choosing the right AI starter kit, Confessions, and Hidden Gems.* *MLOps Community — Agentic AI Foundation, 2025-04-24* ## We’re going on tour! We’re hitting the road with a global series of mega meetups, kicking things off back at the Hibernia in San Francisco on May 28 [https://go.mlops.community/WorldTourSF] with a mini-conference. Expect 30+ booths sharing agents in production, lightning talks and keynotes from experts. More dates and cities coming soon, so keep an eye out. At this stage I can neither confirm nor deny we've locked in these iconic venues: * LLM Grand in Las Vectors * Sydney MLOpsra House * The Royal Albert Hallgorithm * The Hollywood Bowl-ean * CoacheLLMa [Subscribe here](https://go.mlops.community/GwazeEmail) ## How Sama is Improving ML Models to Make AVs Safer Every model needs a clear vision - and sometimes, clear vision is the whole point. In this episode we talked about the challenges of working with computer vision and visual data in real-world AI systems: collecting it, labeling it, and making sure it’s actually useful. Duncan shared how smarter data selection can cut costs and improve performance, especially at scale. He broke down three tactics that make a real difference: * Event-driven curation: Skip the routine footage and focus on moments where something unpredictable happens. * Attribute balancing: Go beyond class labels to include variation in lighting, weather, skin tone, and more. * Pre-labeling and correction loops: Let models take a first pass, then have humans fix only the mistakes. Click below to listen and make visual data clear. Video [https://go.mlops.community/66wgnh] || Spotify [https://go.mlops.community/gi4h5m] || Apple [https://go.mlops.community/n2gr8d] [https://go.mlops.community/n2gr8d](https://go.mlops.community/n2gr8d) [https://go.mlops.community/66wgnh](https://go.mlops.community/66wgnh) [https://go.mlops.community/gi4h5m](https://go.mlops.community/gi4h5m) ## dccwest_mlops ## DATACONNECT WEST We’re proud to be supporting DataConnect West as a community partner! Happening May 20 in San Francisco, this year’s theme is Agentic AI – AI That Reasons, Acts, and Adapts. Talks will cover how teams are building adaptive systems that operate independently, plus real examples from people shipping agent workflows in production. Use promo code dccwest_mlops to get 15% off your ticket to #DCCWest. Register here [https://go.mlops.community/DCCWestDirect] ## I Am Once Again Asking "What is MLOps?" One of the positives of VibeOps is that it’s a lot easier to define than MLOps. The foundations of MLOps came up as Oleksandr compared building ML platforms across chemistry and video generation. Tooling matters, but team structure and tight feedback loops matter more. For him, MLOps is ultimately about breaking down silos and reducing the time between ideas and outcomes. Rather than chasing silver bullets, strong teams focus on shared context: * T-shaped roles work best: Teams need deep expertise in one area and enough breadth to collaborate across disciplines. * Shift-left isn’t just for code: Applying it to data is harder, but just as essential. Know what’s easier than defining MLOps? Clicking below to listen. Video [https://go.mlops.community/mygmev] || Spotify [https://go.mlops.community/ufh6xd] || Apple [https://go.mlops.community/w0bmzz] [https://go.mlops.community/w0bmzz](https://go.mlops.community/w0bmzz) [https://go.mlops.community/mygmev](https://go.mlops.community/mygmev) [https://go.mlops.community/ufh6xd](https://go.mlops.community/ufh6xd) ## 88% off - Build Your First MLOps Stack ## MLOPS STACK COURSE Built by community member Stefano Bosisio, this course gets you working with Apache Beam, Kubeflow, Vertex AI, and MLflow through short theory bursts and code-driven tutorials, with access to a private Slack channel for support. Just $29 for a limited time. Grab your discount code here [https://go.mlops.community/Stack88off] ## Job of the Week [https://go.mlops.community/USjob24Apr](https://go.mlops.community/USjob24Apr) [https://go.mlops.community/MLConfess](https://go.mlops.community/MLConfess) ## Framework, Template, or Example? Choosing the Right AI Starter Kit for Your Team Good, fast, cheap – pick any two. It’s a classic for a reason. This blog explores the trade-offs between Frameworks, Templates, and Examples as AI starter kits, comparing structure, speed, and flexibility. Frameworks enforce consistency but can feel restrictive. Examples offer fast, task-specific guidance but don’t scale well. Templates often strike the right balance for MLOps teams handling varied projects. When you need shared DevOps patterns without dictating internal logic, Templates are a strong option. They offer: * Quick setup with CI/CD and packaging pre-configured * Customizable structure using tools like Cookiecutter * Consistency across teams while supporting different ML tasks An easy pick? Clicking below to read. Read it here [https://home.mlops.community/home/blogs/framework-template-or-example-choosing-the-right-ai-starter-kit-for-your-team] [Read it here](https://home.mlops.community/home/blogs/framework-template-or-example-choosing-the-right-ai-starter-kit-for-your-team) ## Hidden Gems ## CALL FOR SPEAKERS 🎶🎤I'd like to teach the world to sing sync in perfect harmony 🎶 Here's your chance - the call for speakers [https://go.mlops.community/5vpcma] is open for World Summit AI, Amsterdam, 8-9 October. ## HERE TO HELP Before you go, here are three ways I can help - just hit reply: * Curated intros to other community members * What problems are you dealing with? Let me help you find the best solutions through my network * Looking to augment your staff for an MLOps or AI project? I got you covered Thanks for reading, catch you next time! --- Source: https://aaif.live/newsletters/mlopscommunity/2025-04-24-the-good-the-bad-and-the-blurry-a-clearer-vision-for-compute