--- title: "Celebrating the artists behind a masterpiece" newsletter: "MLOps Community" date: 2024-06-13 source: https://aaif.live/newsletters/mlopscommunity/2024-06-13-celebrating-the-artists-behind-a-masterpiece --- # Celebrating the artists behind a masterpiece *Plus, system of a down (and up), how to make your millions, a free course, dealing with diverse data, and hidden gems.* *MLOps Community — Agentic AI Foundation, 2024-06-13* ## Uber's Michelangelo: Strategic AI Overhaul and Impact // MLOps Podcast #239 We're taking a different route this episode. Inspired by Uber's recent blog post on Michelangelo’s evolution, I wanted to break it down and share some key learnings and takeaways. As well as the blog I also pulled from other podcasts to talk about some of the big improvements, like using project tiering to focus on important ML projects and adopting Kubernetes for better GPU management. But it's not just about the tech; Uber’s engineering culture really stands out. They not only develop these innovations but also share them with everyone. Plus, it's great to see so many Uber team members starting their own companies. Click below to come along for the ride. Video [https://home.mlops.community/home/videos/ubers-michelangelo-strategic-ai-overhaul-and-impact] || Spotify [https://open.spotify.com/episode/75v3qsiBhrzWHKet6IrLmv?si=ZLqHC_U7Sj-Z5TH5GfUoAA] || Apple [https://podcasts.apple.com/us/podcast/ubers-michelangelo-strategic-ai-overhaul-and-impact-239/id1505372978?i=1000658201206] [https://podcasts.apple.com/us/podcast/ubers-michelangelo-strategic-ai-overhaul-and-impact-239/id1505372978?i=1000658201206](https://podcasts.apple.com/us/podcast/ubers-michelangelo-strategic-ai-overhaul-and-impact-239/id1505372978?i=1000658201206) [https://home.mlops.community/home/videos/ubers-michelangelo-strategic-ai-overhaul-and-impact](https://home.mlops.community/home/videos/ubers-michelangelo-strategic-ai-overhaul-and-impact) [https://open.spotify.com/episode/75v3qsiBhrzWHKet6IrLmv?si=ZLqHC_U7Sj-Z5TH5GfUoAA](https://open.spotify.com/episode/75v3qsiBhrzWHKet6IrLmv?si=ZLqHC_U7Sj-Z5TH5GfUoAA) ## Kickstart your RAG project with Milvus Lite https://milvus.io/blog/introducing-milvus-lite.md?utm_source=vendor&utm_medium=referral&utm_campaign=2024-06-12_email_mlops-newsletter-spn_mlops A lightweight version of Milvus [https://milvus.io/?utm_source=vendor&utm_medium=referral&utm_campaign=2024-06-12_email_mlops-newsletter-spn_mlops], the popular open source vector database created by Zilliz [https://zilliz.com/?utm_source=vendor&utm_medium=referral&utm_campaign=2024-06-12_email_mlops-newsletter-spn_mlops], is here! Milvus Lite offers the easiest way to start with Milvus. Just run ‘pip-install pymilvus’ on your laptop or notebook to start prototyping your GenAI applications. When your applications are ready for production, the shared API makes it easy to deploy on Docker, Kubernetes, or the cloud. Milvus Lite is integrated [https://milvus.io/docs?utm_source=vendor&utm_medium=referral&utm_campaign=2024-06-12_email_mlops-newsletter-spn_mlops] with many of your favorite AI frameworks and development stacks, including LangChain, LlamaIndex, Haystack, Voyage AI, Ragas, and many more. To help you get started, we’ve created a sample RAG notebook [https://github.com/milvus-io/bootcamp/blob/master/bootcamp/tutorials/quickstart/build_RAG_with_milvus.ipynb] and an image search example [https://github.com/milvus-io/bootcamp/blob/master/bootcamp/tutorials/quickstart/image_search_with_milvus.ipynb]. Check out the code and try it for yourself. Get started with Milvus Lite [https://milvus.io/blog/introducing-milvus-lite.md?utm_source=vendor&utm_medium=referral&utm_campaign=2024-06-12_email_mlops-newsletter-spn_mlops] ## From Robotics to Recommender Systems // Miguel Fierro // MLOps Podcast #240 Some readers may have noticed I like to sprinkle musical references in the newsletter as a subtle way of giving some recommendations. After this chat with Miguel, I think I might have to start being more explicit. We talked about the impact of recommender systems, especially their revenue contribution. Stats, like Amazon generating 35% of its revenue through them, led Miguel to pivot from robotics. He talked me through the three main architectures for recommender systems and the benefits and challenges of each. Plus, we discussed the role of ML in robotics and the future of sports analytics. So, until I build out my recommendation system, I’ll give a couple of explicit recommendations: "The Look" by Metronomy, and of course, clicking the link below. Video [https://home.mlops.community/home/videos/from-robotics-to-recommender-systems] || Spotify [https://open.spotify.com/episode/1fpcEI1sR7OV0Ryy5aOeDk?si=dcOCclMsTqO00AjzUiw0Mw]|| Apple [https://podcasts.apple.com/us/podcast/from-robotics-to-recommender-systems-miguel-fierro-240/id1505372978?i=1000658674105] [https://podcasts.apple.com/us/podcast/from-robotics-to-recommender-systems-miguel-fierro-240/id1505372978?i=1000658674105](https://podcasts.apple.com/us/podcast/from-robotics-to-recommender-systems-miguel-fierro-240/id1505372978?i=1000658674105) [https://home.mlops.community/home/videos/from-robotics-to-recommender-systems](https://home.mlops.community/home/videos/from-robotics-to-recommender-systems) [https://open.spotify.com/episode/1fpcEI1sR7OV0Ryy5aOeDk?si=dcOCclMsTqO00AjzUiw0Mw](https://open.spotify.com/episode/1fpcEI1sR7OV0Ryy5aOeDk?si=dcOCclMsTqO00AjzUiw0Mw) ## Job of the Week [https://www.linkedin.com/jobs/view/3944675547/](https://www.linkedin.com/jobs/view/3944675547/) ## Under the Hood of an Algorithmic Hedgefund // Pierre Cilliers // MLOps Community IRL #81 Bristol ## MLOps Community IRL Meetup I’m not saying watching this will make you a millionaire, but it won’t hurt your chances. Pierre oversees AI-driven investment strategies and shares some of his insights about developing, testing, and deploying trading strategies using machine learning for optimal performance. He emphasizes extensive backtesting with historical data before demo trading and discusses CI/CD pipelines for efficient strategy deployment and maintenance. Technical aspects like strategy containerization, automated scaling, and advanced monitoring systems are also covered. Just remember Pierre and the MLOps Community when you’re a billionaire. Watch it here [https://home.mlops.community/home/videos/under-the-hood-of-an-algorithmic-hedgefund] [Watch it here](https://home.mlops.community/home/videos/under-the-hood-of-an-algorithmic-hedgefund) ## Bridging The Gap Between Data Scientists and Machine Learning Engineers Making the leap from data science to ML can feel like jumping Tower Bridge in a double-decker bus. That’s what inspired colossal community contributor Médéric to create the FREE MLOps Coding Course [https://webhook.mlops.community/v2/lp-course?email={{customer.email | default:] to bridge this gap. This blog gives a short intro to the course. It has a short explainer on why coding skills are essential, some course highlights like how to set up your system and how to structure code into proper Python packages, explains the personalized support you’ll get and the companion repository that goes with the course. All for FREE. Give the blog a read, sign up for the course, and you’ll soon be flying like Albert Gunter [https://www.youtube.com/watch?v=y2cPQAsqUYE&ab_channel=BritishPath%C3%A9]. With thanks to Médéric Hurier for their contribution. Your Multimodal Data Is Constantly Evolving - How Bad Can It Get? [https://home.mlops.community/home/blogs/your-multimodal-data-is-constantly-evolving-how-bad-can-it-get] Numerical, text, image, video, an android in Star Trek—data comes in many forms. In this blog, Vishakha explores the challenges of working with diverse data types, such as maintaining quality consistency, managing large storage requirements, and efficient retrieval. Solutions discussed include advanced storage architectures and efficient retrieval techniques to handle growing complexity and volume, highlighting the need for new technologies to meet these demands. Read this so you can adapt to the challenges like that kid in The Goonies. With thanks to Vishakha Gupta for their contribution. [Bridging The Gap Between Data Scientists and Machine Learning Engineers](https://home.mlops.community/public/blogs/mlops-coding-course-bridging-the-gap-between-data-scientists-and-machine-learning-engineers) ## Hidden Gems ## IRL Meetups Stockholm [https://mlops.community/event/mlops-start-ups/] - June 18 - 📣shoutout to HPE London [https://mlops.community/event/mlops-community-london-chapter-skyscanner/] - June 19 San Francisco [https://www.aiqualityconference.com/] - June 25 - 🙏with Kolena Denver [https://mlops.community/event/pizza-pints-expert-speaker-intro-to-machine-learning-toolkits-with-kubeflow/] - July 30 [Stockholm](https://mlops.community/event/mlops-start-ups/) Thanks for reading. See you in Slack [https://go.mlops.community/slack], YouTube [https://www.youtube.com/channel/UCG6qpjVnBTTT8wLGBygANOQ?view_as=subscriber], and podcast [https://home.mlops.community/public/content/] land. Oh yeah, and we are also on X [https://twitter.com/mlopscommunity]. The MLOps Community newsletter is edited by Jessica Rudd [https://www.linkedin.com/in/jmrudd/]. --- Source: https://aaif.live/newsletters/mlopscommunity/2024-06-13-celebrating-the-artists-behind-a-masterpiece