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TWIML | The Voice of Machine Learning and Artificial IntelligenceIntelligent content that gives practitioners, innovators, and leaders an inside look at the present and future of ML & AI technologies.TWIML | The Voice of Machine Learning and Artificial Intelligence Skip to content Login About Contact Newsletter Twiml-icon-facebook Twiml-icon-twitter Twiml-icon-youtube1 Linkedin Instagram Podcast Solutions Events Resources Community Articles Podcast Solutions Events Resources Community Articles About Contact Newsletter Login SEARCH Intelligent content that gives practitioners, innovators and leaders an inside look at the present and future of ML & AI technologies. Podcast Latest Play Video An Agentic Mixture of Experts for DevOps with Sunil Mallya EPISODE 708  |   November 4, 2024 0 Today we're joined by Sunil Mallya, CTO and co-founder of Flip AI. We discuss Flip’s incident debugging system for DevOps, which was built using a custom mixture of experts (MoE) large language model (LLM) trained on a novel "CoMELT" observability dataset which combines traditional MELT data—metrics, events, logs, and traces—with code to efficiently identify root failure causes in complex software systems. We discuss the challenges of integrating time-series data with LLMs and their multi-decoder architecture designed for this purpose. Sunil describes their system's agent-based design, focusing on clear roles and boundaries to ensure reliability. We examine their "chaos gym," a reinforcement learning environment used for testing and improving the system's robustness. Finally, we discuss the practical considerations of deploying such a system at scale in diverse environments and much more. All Episodes All Episodes Discover TWIMLcon 2022Data-Centric AINew to the Pod? Now available On Demand!  Our premier event of the year where we discuss the platforms, tools, technologies, and practices necessary to enable and scale enterprise machine learning and AI.  The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools You’re not Facebook: Architecting MLOps for B2B Use Cases Site Reliability Engineering for Reliable Machine Learning in Production Culture and Organizational Strategies for ML Success TWIMLcon 2022 TWIMLcon 2022 New! Check out our recent panel on real-world data-centric AI: Don't miss our in-depth interviews with data-centric AI experts: Data Debt in Machine Learning with D. Sculley Principle-Centric AI with Adrien Gaidon The Fallacy of “Ground Truth” with Shayan Mohanty Feature Platforms for Data-Centric AI with Mike Del Balso Data-Centric AI Data-Centric AI Are you a new listener of the TWIML AI Podcast? We suggest you get started with these great interviews! Live from TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng AI Rewind 2019: Trends in Fairness and AI Ethics with Timnit Gebru How AI Predicted the Coronavirus Outbreak with Kamran Khan What are the Implications of Algorithmic Thinking? with Michael I. Jordan ML Innovation in Healthcare with Suchi Saria Machine Learning at GSK with Kim Branson New to Pod New to Pod EVENTS TWIML hosts a variety of events throughout the year to educate and inspire our listeners and community members. Take a look at our upcoming events below and click the events link to find out more about past events. TWIMLcon: AI Platforms is happening now! This virtual conference will once again bring to light the platforms, tools, technologies, and practices necessary to enable and scale enterprise machine learning and AI. Registration is FREE and it’s not too late to join us. Visit the TWIMLcon: AI Platforms 2022 event page to check out our exciting line up of speakers and sessions, and to register for the event. MORE EVENTS MORE EVENTS Solutions Our conversations with hundreds of ML/AI practitioners and teams have demonstrated that effective tools and platforms are the key to delivering ML and AI at scale—allowing teams to innovate more quickly and consistently.The TWIML Solutions guide helps you identify technologies and solutions that can help your organization deliver models into production more quickly and efficiently. Latest Research re:Invent Roundup 2021 Long before starting the TWIML podcast, I worked at the intersection of the two technology shifts that ultimately enabled modern artificial intelligence: cloud computing and big data. AWS was the clear leader in cloud even back then, so I jumped at the opportunity to attend the company’s first re:Invent conference way back in 2012. Pachyderm Profile Pachyderm provides the ability to modularize, orchestrate, and scale the steps of your ML pipeline within a language-agnostic platform — with the added ability to trace the lineage and versioning of both code and data. Building Responsible AI A recent tweet from Soft Linden illustrated the importance of strong responsible AI, governance and testing frameworks for organizations deploying public-facing machine learning applications. Following a search for “had a seizure now what”, the tweet showed that Google’s “featured snippet” highlighted actions that a University of Utah healthcare site explicitly advised readers NOT to take. Introducing TWIML’s New ML and AI Solutions Guide We’re proud to announce the new TWIML Solutions Guide, a directory of machine learning tools and platform technologies for data scientists, ML engineers and other AI practitioners and leaders. The Guide aims to help them explore and compare open source and commercial offerings for building, delivering, and improving their ML and AI projects. This post explains why we think the guide is important and highlights some of its key features. Developing your Machine Learning Platform Strategy In order to help enterprise machine learning, data science, and AI innovators understand how model-driven enterprises are successfully scaling machine learning, we have conducted numerous interviews on the topic. Machine Learning Platform Case Studies In this post, we present three representative ML platforms: Airbnb’s Bighead, Facebook’s FBLearner, and LinkedIn’s Pro-ML. Each of these platforms was developed in response to the unique situation, challenges, and considerations faced by its creator. MORE RESEARCH MORE RESEARCH Explore Solutions Comet Build better models faster by using state-of-the-art hyperparameter optimization and supervised early stopping tools. Focus on adding business value to your data pipeline while Comet automates the rest. Dataiku Data Science Studio Dataiku Data Science Studio is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Run:ai Atlas Run:ai Atlas is a compute orchestration platform that speeds up data science initiatives by pooling all available GPU resources and then dynamically allocating resources as you need them. One-click execution of experiments, no code changes required by the user, and most importantly, no more waiting around to access GPUs. Atlas automates provisioning of multiple GPU or fractions of GPU across teams, users, clusters and nodes, and IT gains control and visibility over the full AI infrastructure stack through comprehensive, easy-to-use dashboards. Intel SigOpt SigOpt is a model development platform that makes it easy to track runs, visualize training, and scale hyperparameter optimization for any type of model built with any library on any infrastructure Tecton Introducing the first enterprise-ready feature store for machine learning. Built by the creators of Uber Michelangelo, Tecton provides the first enterprise-ready feature store that manages the complete lifecycle of features — from engineering new features to serving them online for real-time predictions. Weights & Biases Experiment tracking, Datasetset tracking, Dataset visualization MORE SOLUTIONS MORE SOLUTIONS Community The TWIML Community is a global network of machine learning, deep learning and AI practitioners and enthusiasts.We organize ongoing educational programs including study groups for several popular ML/AI courses such as Fast.ai Deep Learning, Machine learning and NLP, Stanford CS224N, Deeplearning.ai and more. We also host several special interest groups focused on topics like Swift for Tensorflow, and competing in Kaggle competitions. GET STARTED GET STARTED Work with Us TWIML creates and curates intelligent content that helps makers build better experiences for their users, and gives executives an inside look at the real-world application of intelligence technologies. We also build and support communities of innovators who are as excited about these technologies as we are. We advise a variety of leading organizations as well, helping to craft strategies for taking advantage of the vast opportunities created by ML and AI.  GET IN TOUCH GET IN TOUCH © 2024 CloudPulse Strategies All rights reserved About TWIML Login About Contact Newsletter Our Policies Privacy Policy Terms of Service Media Policy Popular Content Podcast Episodes Podcast Series Podcast Topics TWIMLcon About TWIML Login About Contact Newsletter Our Policies Privacy Policy Terms of Service Media Policy Popular Content Podcast Episodes Podcast Series Podcast Topics TWIMLcon © 2021 CloudPulse Strategies / All rights reservedenusen-US1734588001https://twimlai.com

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