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PODCAST

MLOps.community

Relaxed Conversations around getting AI into production, whatever shape that may come in (agentic, traditional ML, LLMs, Vibes, etc)

technology

All Episodes

00:56:20

How A Manager Became a Believer in DevOps for Machine...

MLOps.community ·

2023/04/04

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 from a monolith to microservices in the healthcare sector without any downtime. Keith's background

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00:50:20

ML in Production: A DS from Ubisoft Perspective //...

MLOps.community ·

2023/03/28

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 is focused on tying machine learning products back to business use cases and the ROI they provide

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00:57:47

Large Language Models in Production Round-table...

MLOps.community ·

2023/03/23

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 issues, and a bunch of random tangents. We have some heavy hitters for this event! // MLOps Jobs board

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00:50:48

The Future of Search in the Era of Large Language...

MLOps.community ·

2023/03/21

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 importance of product thinking and the trade-offs between relevance, throughput, and latency when

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00:55:41

The Challenges of Deploying (many!) ML Models //...

MLOps.community ·

2023/03/14

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 for data scientists. The challenging 10% of deployments will often be "edge" cases, whether CDN-style

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00:47:17

Intelligence & MLOps // Karl Fezer // MLOps Podcast #...

MLOps.community ·

2023/03/07

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 overlap between foundational models and MLOps, emphasizing the importance of making high-impact tasks more

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00:58:03

The Rise of Serverless Databases // Alex DeBrie //...

MLOps.community ·

2023/02/28

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, Elasticsearch). In the last few years, we're finally seeing data infrastructure that is truly built for the cloud. Elastic, scalable, resilient, managed, etc. Early examples were

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00:59:19

The Ops in MLOps - Process and People // Shalabh...

MLOps.community ·

2023/02/21

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 provides a unique and insightful perspective on MLOps from the lens of customer success. // Bio Shalabh has

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00:45:59

Griffin, ML Platform at Instacart // Sahil Khanna //...

MLOps.community ·

2023/02/14

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 machine learning teams. Sahil emphasizes the soft factors, such as staying customer-focused and the

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00:48:09

Non-traditional Career Paths in MLOps // Matthew...

MLOps.community ·

2023/02/07

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 that are required across different roles. This episode also highlights the significance of stakeholder

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00:41:08

Investing in the Next Generation of AI & ML // Jill...

MLOps.community ·

2023/01/31

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 discussion also touches on the idea of generative AI and large language models, and their potential

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00:39:15

Approaches to Fairness and XAI // Murtuza Shergadwala...

MLOps.community ·

2023/01/24

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 fully utilize the potential of XAI tools. Additionally, there is a discrepancy in the approach to

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00:51:46

Airflow Sucks for MLOps // Stephen Bailey // MLOps...

MLOps.community ·

2023/01/17

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 data classification to make it easier for end users to understand which data to use. Stephen also

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00:51:38

Updated The Evolution of ML Infrastructure // Sakib...

MLOps.community ·

2023/01/10

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 Francisco office where he primarily focuses on early-stage investments in developer platforms, data

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00:52:27

Foundational Models are the Future but... with Alex...

MLOps.community ·

2023/01/03

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, democratized practice. Before they can achieve this impact, however, we need to bridge the cost, quality, and

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00:41:12

Explainability in the MLOps Cycle // Dattaraj Rao //...

MLOps.community ·

2022/12/27

MLOps Coffee Sessions #138 with Dattaraj Rao, Explainability in the MLOps Cycle co-hosted by Vishnu Rachakonda. // Abstract When it comes to Dattaraj's interest, 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-based systems , and how to incorporate systems into more systems. there is no difference between ML systems and deploying

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00:59:24

Machine Learning Operations — What is it and Why Do...

MLOps.community ·

2022/12/20

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 on their expectations. The paradigm of Machine Learning Operations (MLOps) addresses this issue. // Bio

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00:39:30

Systems Engineer Navigating the World of ML // Andrew...

MLOps.community ·

2022/12/13

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 Machine Learning Engineer and how the two can play together nicely. Most MLOps teams are formed using

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00:52:13

"Real-Time" ML: Features and Inference // Sasha...

MLOps.community ·

2022/12/09

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 do this move, what tools to use, and what steps to take. // Bio Sasha Ovsankin Sasha is currently a Tech Lead of Machine Learning

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00:50:27

Building Threat Detection Systems: An MLE's...

MLOps.community ·

2022/12/06

MLOps Coffee Sessions #134 with Jeremy Thomas Jordan, Building Threat Detection Systems: An MLE's Perspective co-hosted by Vishnu Rachakonda. // Abstract There is a clear pattern that we have been seeing with some of these greats in MLOps. So many use writing as a forcing function to learn about where they have holes in their understanding of something. If you are not writing, this episode is important as to why writing is important for your own development. Jeremy goes into writing in depth as

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514 results

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