MLOps.community

MLOps Coffee Sessions #155 with Matei Zaharia, The Birth and Growth of Spark: An Open Source Success Story, co-hosted by Vishnu Rachakonda. // Abstract We dive deep into the creation of Spark, with the creator himself, Matei Zaharia, Chief Technologist at Databricks. This episode also explores the development of Databricks' other open source home run, ML Flow, and the concept of "lake hou...

MLOps Coffee Sessions #154 with Waleed Kadous, ML Scalability Challenges, co-hosted by Abi Aryan. // Abstract Dr. Waleed Kadous, Head of Engineering at Anyscale, discusses the challenges of scalability in machine learning and his company's efforts to solve them. The discussion covers the need for large-scale computing power, the importance of attention-based models, and the tension between big...

This exclusive podcast episode covers the key findings from the LLM in-production survey that we conducted over the past month. For all the data to explore yourself use this link  https://docs.google.com/spreadsheets/d/13wdBwkX8vZrYKuvF4h2egPh0LYSn2GQSwUaLV4GUNaU/edit?usp=sharing Sign up for our LLM in-production conference happening on April 13th (TODAY) here: https://home.mlops.community/home/ev...

MLOps Coffee Sessions #153 with Rodolfo Núñez, Multilingual Programming and a Project Structure to Enable It, co-hosted by Abi Aryan. // Abstract It's really easy to mix different programming languages inside the same project and use a project template that enables easy collaboration. It's not about which language is better, but rather what language solves the given section of your problem...

Worlds are colliding! This week, we join forces with the hosts of the Practical AI podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc. --------------- ✌️Connect With Us ✌️ ------------- Join our Slack community: htt...

MLOps Coffee Sessions #152 with Keith Trnka, How A Manager Became a Believer in DevOps for Machine Learning. // Abstract Keith Trnka, a seasoned leader in the technology industry, set foot on the MLOps Podcast in a special episode where he shared insights into his experience leading data teams and machine learning teams, becoming a better software engineer, and overseeing a successful migration fr...

MLOps Coffee Sessions #151 with Jean-Michel Daignan, ML in Production: A DS from Ubisoft Perspective, co-hosted by Abi Aryan. // Abstract As a data scientist himself, Jean-Michel has a unique perspective on the needs of data scientists when it comes to platform development. He talks about the non-invasive approach his team is taking to bring people onto the platform and their SDK, Merlin. The team...

LLM in Production Round Table with Demetrios Brinkmann, Diego Oppenheimer, David Hershey, Hannes Hapke, James Richards, and Rebecca Qian. // Abstract Using LLM in production. That's right. Hype or here to stay? The conversation answers some of the questions that have been asked by our community members like; performance & cost of production, the difference in architectures, Reliability iss...

MLOps Coffee Sessions #150 with Saahil Jain, The Future of Search in the Era of Large Language Models, co-hosted by David Aponte. // Abstract Saahil shares insights into the You.com search engine approach, which includes a focus on a user-friendly interface, third-party apps, and the combination of natural language processing and traditional information retrieval techniques. Saahil highlights the...

MLOps Coffee Sessions #149 with Jason McCampbell, The Challenges of Deploying (many!) ML Models, co-hosted by Abi Aryan and sponsored by Wallaroo. // Abstract In order to scale the number of models a team can manage, we need to automate the most common 90% of deployments to allow ops folks to focus on the challenging 10% and automate the monitoring of running models to reduce the per-model effort...

MLOps Coffee Sessions #148 with Karl Fezer, Intelligence & MLOps co-hosted by Abi Aryan. // Abstract This conversation explores various topics, including biases, defining intelligence, and the future of large language models and MLOps. Karl discusses his paper on defining intelligence and how it relates to the increasing interest in Artificial Intelligence. Karl shares his thoughts on the over...

MLOps Coffee Sessions #147 with Alex DeBrie, Something About Databases, co-hosted by Abi Aryan. // Abstract For databases, it feels like we're in the middle of a big shift. The first 10-15 years of the cloud were mostly about using the same core infrastructure patterns, but in the cloud (SQL Server, MySQL, Postgres, Redis, and Elasticsearch).   In the last few years, we're finally seeing d...

MLOps Coffee Sessions #146 with Shalabh Chaudri, The Ops in MLOps - Process and People, co-hosted by Abi Aryan. // Abstract Shalabh talks through their newfound appreciation for the MLOps perspective from a customer success standpoint. Shalabh's emphasis on setting realistic expectations and ensuring the delivery of promised value adds is particularly valuable.     Generally, this episode prov...

MLOps Coffee Sessions #145 with Sahil Khanna, Griffin, ML platform at Instacart, co-hosted by Mike Del Balso. // Abstract The conversation revolves around the journey of Instacart in implementing machine learning, starting from batch processing to real-time processing. The speaker highlights the importance of real-time processing for businesses and the relevance of Instacart's journey to other...

MLOps Coffee Sessions #144 with Matthew Dombrowski, Non-traditional Career Paths in MLOps, co-hosted by Mihail Eric. // Abstract Let's explore the different aspects of ML and data roles and the variety of responsibilities each role entails! This conversation emphasizes the need for understanding the unique insights each role provides and the similarities in responsibilities and soft skills tha...

MLOps Coffee Sessions #143 with Jill Chase & Manmeet Gujral, Investing in the Next Generation of AI & ML. // Abstract Investors are currently focusing on developer tooling and the foundational AI model movement, as they have seen explosive growth in this area. This podcast explores the impact of foundational models on investment thesis and the future of machine learning operations. The dis...

MLOps Coffee Sessions #142 with Murtuza Shergadwala, Approaches to Fairness and XAI, co-hosted by Abi Aryan. This episode is sponsored by Fiddler AI. // Abstract The field of Explainable Artificial Intelligence (XAI) is continuously evolving, with an increasing focus on providing model-centric explanations in a human-centric manner. However, better frameworks and training for users are needed to f...

MLOps Coffee Sessions #141 with Stephen Bailey, Airflow Sucks for MLOps, co-hosted by Joe Reis. // Abstract Stephen discusses his experience working with data platforms, particularly the challenges of training and sharing knowledge among different stakeholders. This talk highlights the importance of having clear priorities and a sense of practicality and mentions the use of modular job design and...

MLOps Coffee Sessions #140 with Sakib Dadi, The Evolution of ML Infrastructure sponsored by Wallaroo. // Abstract The toolkit and infrastructure empowering machine learning practitioners are advancing as ML adoption accelerates. We'll go through the current landscape of ML tooling, startups, and new projects from an investor's perspective. // Bio Sakib is a vice president in the San Franci...

MLOps Coffee Sessions #139 with Alex Ratner, Putting Foundation Models to Use for the Enterprise, co-hosted by Abi Aryan, sponsored by Snorkel AI . // Abstract Foundation models are rightfully being compared to other game-changing industrial advances like steam engines or electric motors. They’re core to the transition of AI from a bespoke, less predictable science to an industrialized, democratiz...

MLOps Coffee Sessions #138 with Dattaraj Rao, Explainability in the MLOps Cycle, co-hosted by Vishnu Rachakonda. // Abstract When it comes to Dattaraj's interests, you'll hear about his top 3 areas in Machine Learning. What he sees as up and coming, what he's investing his company's time into, and where he invests his own time. Learn more about rule-based systems, deploying rule-ba...

MLOps Coffee Sessions #137 with Niklas Kühl, Machine Learning Operations — What is it and Why Do We Need It? co-hosted by Abi Aryan. // Abstract The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production.    However, it is highly challenging to automate and operationalize ML products, and thus, many ML endeavors fail to deliver...

MLOps Coffee Sessions #136 with Andrew Dye, Systems Engineer, Navigating the World of ML, co-hosted by David Aponte. // Abstract We don't hear that much about working at a very low level on this podcast, but they are still very valid. Andrew is able to give us his take on why and what you need to keep in mind when you are working at these low levels, and why it is very important when you are a...

MLOps Coffee Sessions #135 with Sasha Ovsankin and Rupesh Gupta, Real-time Machine Learning: Features and Inference, co-hosted by Skylar Payne.   // Abstract Moving from batch/offline Machine Learning to more interactive "near" real-time requires knowledge, team, planning, and effort. We discuss what it means to do real-time inference and near-real-time features, when to make this move,...

MLOps Coffee Sessions #134 with Jeremy Thomas Jordan, Building Threat Detection Systems: An MLE's Perspective, co-hosted by Vishnu Rachakonda. Join the Community: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTJoinIn⁠⁠⁠⁠⁠⁠...