MLOps Coffee Sessions #158 with Nils Reimer, MLOps Build or Buy, Large Language Model at Scale co-hosted by Abi Aryan. // Abstract Large Language Models with billions of parameters have the possibility to change how we work with textual data. However, running them on scale at potentially hundred millions of texts a day is a massive challenge. Nils talks about finding the right model size for respective tasks, model distillation, and promising new ways on transferring knowledge from large to smal...
May 16, 2023•1 hr 15 min•Season 1Ep. 158
We are having another LLMs in-production Virtual Conference. 50+ speakers combined with in-person activities around the world on June 15 & 16. Sign up free here: https://home.mlops.community/home/events/llm-in-prod-part-ii-2023-06-20 // Abstract This panel discussion is centered around a crucial topic in the tech industry - data privacy and security in the context of large language models and AI systems. The discussion highlights several key themes, such as the significance of trust in AI sy...
May 12, 2023•25 min
MLOps Coffee Sessions #157 with Katrina Ni & Aaron Maurer, MLOps Build or Buy, Startup vs. Enterprise? co-hosted by Jake Noble of tecton.ai. This episode is sponsored by tecton.ai - Check out their feature store to get your real-time ML journey started. // Abstract There are a bunch of challenges with building useful machine learning at a B2B software company like Slack, but we've built some cool use cases over the years, particularly around recommendations. One of the key challenges is ...
May 09, 2023•50 min
Sign up for the next LLM in production conference here: https://go.mlops.community/LLMinprod Watch all the talks from the first conference: https://go.mlops.community/llmconfpart1 // Abstract In this panel discussion, the topic of the cost of running large language models (LLMs) is explored, along with potential solutions. The benefits of bringing LLMs in-house, such as latency optimization and greater control, are also discussed. The panelists explore methods such as structured pruning and know...
May 06, 2023•36 min
MLOps Coffee Sessions #156 with Melissa Barr & Michael Mui, Machine Learning Education at Uber co-hosted by Lina Weichbrodt. // Abstract Melissa and Michael discuss the education program they developed for Uber's machine learning platform service, Michelangelo, during a guest appearance on a podcast. The program teaches employees how to use machine learning both in general and specifically for Uber. The platform team can obtain valuable feedback from users and use it to enhance the platf...
May 02, 2023•59 min•Season 1Ep. 156
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 house ML". As a special treat Matei talked to us about the details of the "DSP" (Demonstra...
Apr 25, 2023•58 min•Season 1Ep. 155
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 and small data. // Bio Dr. Waleed Kadous leads engineering at Anyscale, the company behind the open...
Apr 18, 2023•1 hr 1 min•Season 1Ep. 154
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/events/llms-in-production-conference-2023-04-13...
Apr 13, 2023•48 min
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 what language is better, but rather what language solves the given section of your problem better for you. // Bio Rodo has been working in the "Data Space" for almost 7 years. He wa...
Apr 10, 2023•1 hr•Season 1Ep. 153
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: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: http...
Apr 07, 2023•59 min
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...
Apr 04, 2023•56 min•Season 1Ep. 152
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. ...
Mar 28, 2023•50 min•Season 1Ep. 151
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 ...
Mar 23, 2023•58 min
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 wo...
Mar 21, 2023•51 min•Season 1Ep. 150
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-styl...
Mar 14, 2023•56 min•Season 1Ep. 149
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 mor...
Mar 07, 2023•47 min•Season 1Ep. 148
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 examp...
Feb 28, 2023•58 min•Season 1Ep. 147
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. // Bi...
Feb 21, 2023•59 min•Season 1Ep. 146
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...
Feb 14, 2023•46 min•Season 1Ep. 145
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 stak...
Feb 07, 2023•48 min•Season 1Ep. 144
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 imp...
Jan 31, 2023•41 min•Season 1Ep. 143
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 ...
Jan 24, 2023•39 min•Season 1Ep. 142
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. Ste...
Jan 17, 2023•52 min•Season 1Ep. 141
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 infrastructure...
Jan 10, 2023•52 min•Season 1Ep. 140
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 con...
Jan 03, 2023•52 min•Season 1Ep. 139
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...
Dec 27, 2022•41 min•Season 1Ep. 138
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 is...
Dec 20, 2022•59 min•Season 1Ep. 137
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 exist...
Dec 13, 2022•40 min•Season 1Ep. 136
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 Mac...
Dec 09, 2022•52 min•Season 1Ep. 135
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...
Dec 06, 2022•50 min•Season 1Ep. 134
