talk-data.com
Activities & events
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From Swift to Mojo and high-performance AI Engineering with Chris Lattner
2025-11-05 · 16:00
Chris Lattner
– guest
,
Gergely Orosz
– host
Brought to You By: • Statsig — The unified platform for flags, analytics, experiments, and more. Companies like Graphite, Notion, and Brex rely on Statsig to measure the impact of the pace they ship. Get a 30-day enterprise trial here. • Linear – The system for modern product development. Linear is a heavy user of Swift: they just redesigned their native iOS app using their own take on Apple’s Liquid Glass design language. The new app is about speed and performance – just like Linear is. Check it out. — Chris Lattner is one of the most influential engineers of the past two decades. He created the LLVM compiler infrastructure and the Swift programming language – and Swift opened iOS development to a broader group of engineers. With Mojo, he’s now aiming to do the same for AI, by lowering the barrier to programming AI applications. I sat down with Chris in San Francisco, to talk language design, lessons on designing Swift and Mojo, and – of course! – compilers. It’s hard to find someone who is as enthusiastic and knowledgeable about compilers as Chris is! We also discussed why experts often resist change even when current tools slow them down, what he learned about AI and hardware from his time across both large and small engineering teams, and why compiler engineering remains one of the best ways to understand how software really works. — Timestamps (00:00) Intro (02:35) Compilers in the early 2000s (04:48) Why Chris built LLVM (08:24) GCC vs. LLVM (09:47) LLVM at Apple (19:25) How Chris got support to go open source at Apple (20:28) The story of Swift (24:32) The process for designing a language (31:00) Learnings from launching Swift (35:48) Swift Playgrounds: making coding accessible (40:23) What Swift solved and the technical debt it created (47:28) AI learnings from Google and Tesla (51:23) SiFive: learning about hardware engineering (52:24) Mojo’s origin story (57:15) Modular’s bet on a two-level stack (1:01:49) Compiler shortcomings (1:09:11) Getting started with Mojo (1:15:44) How big is Modular, as a company? (1:19:00) AI coding tools the Modular team uses (1:22:59) What kind of software engineers Modular hires (1:25:22) A programming language for LLMs? No thanks (1:29:06) Why you should study and understand compilers — The Pragmatic Engineer deepdives relevant for this episode: • AI Engineering in the real world • The AI Engineering stack • Uber's crazy YOLO app rewrite, from the front seat • Python, Go, Rust, TypeScript and AI with Armin Ronacher • Microsoft’s developer tools roots — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe |
The Pragmatic Engineer |
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DevOps Society London Event @Zilch
2025-10-01 · 17:00
DevOps Society Meetup – Wednesday 1st October @6PMLocation: Zilch Offices, London - 111 Buckingham Palace Rd, London SW1W 0SR We’re excited to invite you to our next DevOps Society Meetup, hosted by Zilch in London. This event brings together the DevOps and cloud-native community for an evening of conversation, learning, and networking. A huge thank you to Zilch for sponsoring this event, and for providing the venue, refreshments, and support! Format of the Meetup:6:00pm – 6:30pm — Networking on arrival, with pizza and drinks provided by Zilch 6:30pm – 7:10pm — First speakers will take to the stage 7:10pm – 7:20pm — Break for refreshments and networking 7:20pm – 8:00pm — Second speaker will take to the stage 8:00pm onwards — More networking at the venue and then at a nearby pub Timings can vary depending on the length of the Q&A after each talk! We are delighted to welcome three fantastic speakers to our event at Zilch, across two talks. SPEAKERS 1 & 2 – Nick Gilbert & Sean HedermanNick Gilbert – DevOps Engineer III at Zilch Nick Gilbert is a Senior DevOps Engineer with a decade of experience working across public and private cloud systems. He has worked extensively with CI/CD and immutable infrastructure, focusing on modernising on-premise solutions into cloud-native architectures. Since joining Zilch, Nick has enhanced system capabilities to shorten feedback loops, improve the developer experience, and increase the reliability of CI/CD pipelines. Sean Hederman – CTO at Zilch With nearly three decades of experience in technology delivery and leadership, Sean Hederman has been instrumental in shaping Zilch’s technological evolution as Chief Technology Officer. He previously held senior roles in technology and DevOps at leading organisations, gaining deep expertise in building and scaling enterprise-grade systems. At Zilch, Sean designed and built the company’s foundational technology and platforms, scaling the team from just a few engineers to more than 120 specialists across multiple disciplines and regions. Originally from South Africa and now based in London, Sean is a recognised thought leader in AI and a leading voice in software engineering, architecture, and DevSecOps. Talk Title: ZOE and Zephyrs: An Overview of Our Journey to Ephemeral Environments at ZilchNick and Sean will take us through the architecture, challenges, and triumphs of establishing ephemeral environments at Zilch. They’ll share insights into:
Expect a candid walkthrough of what it really takes to make ephemeral environments reliable, scalable, and developer-friendly. SPEAKER 3 – Dhruv ParekhSenior DevOps Engineer at EDF Dhruv Parekh is a Senior DevOps Engineer at EDF, specialising in cloud engineering and automation. With over 4 years of experience in building scalable DevOps solutions, Dhruv focuses on driving automation strategies that go beyond the basics of infrastructure as code, bringing a holistic approach to engineering efficiency and business value. Dhruv is also a valued member of our community, holding the "Ambassador for Terraform" title! Talk Title: Automating Beyond TerraformWhen people hear DevOps automation, many think of Terraform plans and YAML pipelines. While powerful, they’re only part of the picture. In this talk, Dhruv explores what it means to automate beyond Terraform:
By the end of this talk, you’ll see automation not just as code, but as a way to design the entire lifecycle of change, from idea to insight. Please RSVP to book your spot. Space is limited, so it’s first come, first served! We look forward to seeing you all there. Ben & Vytas – Co-organisers. |
DevOps Society London Event @Zilch
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Lessons from Two Decades of AI - Micheal Lanham
2025-09-26 · 17:20
Michael Lanham
– AI and software innovator
In this episode, we talk with Michael Lanham, an AI and software innovator with over two decades of experience spanning game development, fintech, oil and gas, and agricultural tech. Michael shares his journey from building neural network-based games and evolutionary algorithms to writing influential books on AI agents and deep learning. He offers insights into the evolving AI landscape, practical uses of AI agents, and the future of generative AI in gaming and beyond. TIMECODES 00:00 Micheal Lanham’s career journey and AI agent books 05:45 Publishing journey: AR, Pokémon Go, sound design, and reinforcement learning 10:00 Evolution of AI: evolutionary algorithms, deep learning, and agents 13:33 Evolutionary algorithms in prompt engineering and LLMs 18:13 AI agent books second edition and practical applications 20:57 AI agent workflows: minimalism, task breakdown, and collaboration 26:25 Collaboration and orchestration among AI agents 31:24 Tools and reasoning servers for agent communication 35:17 AI agents in game development and generative AI impact 38:57 Future of generative AI in gaming and immersive content 41:42 Coding agents, new LLMs, and local deployment 45:40 AI model trends and data scientist career advice 53:36 Cognitive testing, evaluation, and monitoring in AI 58:50 Publishing details and closing remarks Connect with Micheal Linkedin - https://www.linkedin.com/in/micheal-lanham-189693123/ Connect with DataTalks.Club: Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...Check other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn - / datatalks-club Twitter - / datatalksclub Website - https://datatalks.club/ |
DataTalks.Club |
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Keynote 1: Data & AI Strategy
2025-09-23 · 09:00
LIZ HENDERSON
– Digital Leader / NED / Board Advisor
In today’s fast-moving global business environment, technological innovation, shifting consumer demands, and the growing imperative of sustainability are redefining how organizations operate and compete. To thrive in this dynamic landscape, businesses must place data at the core of their strategic and operational decisions, embracing digital tools, AI, and automation to unlock productivity and resilience. This engaging presentation offers a powerful framework for building a tailored data strategy aligned with organizational goals. Led by an expert with over two decades of strategic leadership experience across Fortune 500 companies, FTSE 100 firms, non-profits, and SMEs, this session combines real-world insights with actionable tools to help you navigate complexity and drive sustained growth. Whether you’re developing a data strategy from the ground up or enhancing an existing approach, this session will empower you to lead with clarity, drive innovation, and future-proof your business. Key Takeaways: • Emerging Trends: Discover how to integrate disruptive technologies, including AI, into your data strategy. • Innovation Blueprints: Learn to create a culture of creativity, confidence, and capability. • Strategic Foundations: Explore the essential building blocks of a successful data strategy. • Global Perspectives: Benefit from international case studies of both triumphs and lessons learned. • Interactive Q&A: Bring your challenges to the table and gain expert advice and fresh perspectives. If you’re serious about making smarter decisions, driving growth, and staying ahead of the curve — this session is for you. |
Data Driven LDN Conference
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Lessons from Two Decades of AI
2025-09-16 · 13:00
Micheal Lanham has been building intelligent systems since the early 2000s, starting with neural networks and evolutionary algorithms in games and moving through enterprise software, geoscience, AR/VR, and now AI agents. Over the years, he has written more than ten technical books and worked across industries as an architect, manager, and hands-on AI engineer. In this conversation, Micheal shares hard-earned lessons from two decades at the intersection of data, software, and AI. We’ll explore what games can teach us about intelligence, why evolutionary methods are resurfacing, and how to think about AI agents beyond the hype. We plan to cover:
About the speaker Micheal Lanham is a best-selling author, innovator, and AI engineer based in Calgary, Canada. His work spans games, graphics, GIS, enterprise software, and machine learning. He has published over ten technical books, including Evolutionary Deep Learning, Hands-On Reinforcement Learning for Games, and AI Agents in Action. Micheal has worked as a lead AI developer, architect, and manager across industries from oil and gas to fintech, and today focuses on building intelligent systems with deep reinforcement learning, evolutionary methods, and generative AI. Join our slack: https://datatalks.club/slack.html |
Lessons from Two Decades of AI
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Webinar on Operationalizing AI by Melissa Tondi
2025-08-12 · 16:00
We're excited to announce a Webinar for our North America community: "Operationalizing AI - Lessons Learned from our Journey from a Team of One to All-Company" by Melissa Tondi. When is it happening? 12th August 2025 \| Tuesday \| 12 PM EST\, 11 AM CST\, 10 AM MST\, 9 AM PST. What will Melissa speak about: Melissa will discuss the practical aspects of operationalizing AI, focusing on scaling solutions and building support with a lean team. She'll cover roadmapping, the "Lab vs. Crowd" method, and effective capacity and growth management to centralize and scale AI within an organization. About Melissa Tondi: Melissa Tondi is a highly experienced leader in Quality and Test Engineering, Enablement, and Agile methodologies. Currently, she leads Technology Enablement at CampMinder, focusing on Leadership, AI, Agile Enablement, and Quality and Test Engineering. With over two decades of experience, Melissa is a seasoned professional who actively shapes industry best practices. About The Test Tribe: The Test Tribe, established in 2018, is the world's largest software testing community and an EdTech startup. We empower testing professionals globally with expert courses, memberships, events, and community initiatives, fostering collaboration, learning, and growth. With over 430 events and a global reach of 120K+ testers from 130+ countries, our mission is to provide life-altering growth to every testing professional. By RSVPing to this event, you agree to our Terms and Conditions and Privacy Policy, and consent to be contacted by The Test Tribe and our event collaborators, BrowserStack. |
Webinar on Operationalizing AI by Melissa Tondi
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DevOps Society / GenAI UK Manchester Meetup @AccessPay
2024-04-18 · 17:00
Details: Our first Manchester DevOps Society event has arrived! We are delighted to be partnered with our hosts AccessPay, and our co-organisers Generative AI UK Community. In this event, we will be hearing from Auto Trader and Microsoft. Format of the meetup event will be as follows: 6pm – 6:30pm - Networking on arrival coupled with pizza and drinks provided by ReVybe IT. 6:30pm – 6:55pm – First speaker will take to the stage to talk about Auto Trader’s journey from a traditional environment into the cloud. 6:55pm – 7:15pm – Break for refreshments and networking 7:15pm – 7:40pm – Second speaker will take to the stage to talk about Microsoft Azure’s AI services. 7:40pm – 8:30pm – Networking and event close. We are delighted to welcome 2 speakers to our first Manchester event. #1 – Dave Whyte – Operations Lead – Auto Trader Dave Whyte is the Operations Lead at Auto Trader UK, the premier digital automotive marketplace in the UK. With over two decades of experience, Dave has been instrumental in shaping the evolution of the IT Operations department, driving remarkable levels of stability, availability, and performance. His expertise lies in implementing robust support processes, harnessing the advantages of the Public Cloud, and fostering organizational agility to adapt to dynamic industry demands. Title – Auto Trader’s Journey to the Cloud Join us as we delve into Auto Trader's journey from a traditional environment to the cloud. We'll explore the pre-migration landscape, highlighting its constraints and challenges. Discover the compelling motivations that drove the transition to the cloud and gain valuable insights into the lessons gleaned throughout the transformation process. Finally, we'll glimpse the present-day landscape, showcasing the tangible outcomes of embracing cloud technology. #2 – Ethan Jones – Cloud Solutions Architect (AI) – Microsoft Ethan is a certified data scientist, community co-founder, and Microsoft advocate who has experience leading machine learning and data science projects for numerous FTSE 100 companies, from ideation to production. He is a rising star at Microsoft, who works with engineering teams and customers to accelerate adoption of their machine learning stack on Azure, driving digital transformation forwards to new heights. Title – Discussing how Microsoft utilise Azure AI Services Ethan will be speaking on how Microsoft utilise AI services within the Azure sphere, and how AI is driving digital transformation forward in businesses as machine learning and data science leads the charge on innovation in tech. |
DevOps Society / GenAI UK Manchester Meetup @AccessPay
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Defining A Strategy For Your Data Products
2023-10-23
Ranjith Raghunath
– guest
,
Tobias Macey
– host
Summary The primary application of data has moved beyond analytics. With the broader audience comes the need to present data in a more approachable format. This has led to the broad adoption of data products being the delivery mechanism for information. In this episode Ranjith Raghunath shares his thoughts on how to build a strategy for the development, delivery, and evolution of data products. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. Whether it’s real-time dashboarding and analytics, personalization and segmentation or automation and alerting, Materialize gives you the ability to work with fresh, correct, and scalable results — all in a familiar SQL interface. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free! As more people start using AI for projects, two things are clear: It’s a rapidly advancing field, but it’s tough to navigate. How can you get the best results for your use case? Instead of being subjected to a bunch of buzzword bingo, hear directly from pioneers in the developer and data science space on how they use graph tech to build AI-powered apps. . Attend the dev and ML talks at NODES 2023, a free online conference on October 26 featuring some of the brightest minds in tech. Check out the agenda and register today at Neo4j.com/NODES. This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. Datafold leverages data-diffing to compare production and development environments and column-level lineage to show you the exact impact of every code change on data, metrics, and BI tools, keeping your team productive and stakeholders happy. Datafold integrates with dbt, the modern data stack, and seamlessly plugs in your data CI for team-wide and automated testing. If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Your host is Tobias Macey and today I'm interviewing Ranjith Raghunath about tactical elements of a data product strategy Interview Introduction How did you get involved in the area of data management? Can you describe what is encompassed by the idea of a data product strategy? Which roles in an organization need to be involved in the planning and implementation of that strategy? order of operations: strategy -> platform design -> implementation/adoption platform implementation -> product strategy -> interface development managing grain of data in products team organization to support product development/deployment customer communications - what questions to ask? requirements gathering, helping to understand "the art of the possible" What are the most interesting, innovative, or unexpected ways that you have seen organizations approach data product strategies? What are the most interesting, unexpected, or challenging lessons that you have learned while working on |
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Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable
2023-10-15 · 23:00
Eric Sammer
– Founder
@ Decodable
,
Tobias Macey
– host
Summary Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. Decodable was built with a mission of eliminating all of the painful aspects of developing and deploying stream processing systems for engineering teams. In this episode Eric Sammer discusses why more companies are including real-time capabilities in their products and the ways that Decodable makes it faster and easier. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. Datafold leverages data-diffing to compare production and development environments and column-level lineage to show you the exact impact of every code change on data, metrics, and BI tools, keeping your team productive and stakeholders happy. Datafold integrates with dbt, the modern data stack, and seamlessly plugs in your data CI for team-wide and automated testing. If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold You shouldn't have to throw away the database to build with fast-changing data. You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. Whether it’s real-time dashboarding and analytics, personalization and segmentation or automation and alerting, Materialize gives you the ability to work with fresh, correct, and scalable results — all in a familiar SQL interface. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free! As more people start using AI for projects, two things are clear: It’s a rapidly advancing field, but it’s tough to navigate. How can you get the best results for your use case? Instead of being subjected to a bunch of buzzword bingo, hear directly from pioneers in the developer and data science space on how they use graph tech to build AI-powered apps. . Attend the dev and ML talks at NODES 2023, a free online conference on October 26 featuring some of the brightest minds in tech. Check out the agenda and register today at Neo4j.com/NODES. Your host is Tobias Macey and today I'm interviewing Eric Sammer about starting your stream processing journey with Decodable Interview Introduction How did you get involved in the area of data management? Can you describe what Decodable is and the story behind it? What are the notable changes to the Decodable platform since we last spoke? (October 2021) What are the industry shifts that have influenced the product direction? What are the problems that customers are trying to solve when they come to Decodable? When you launched your focus was on SQL transformations of streaming data. What was the process for adding full Java support in addition to SQL? What are the developer experience challenges that are particular to working with streaming data? How have you worked to address that in the Decodable platform and interfaces? As you evolve the technical and product direction, what is your heuristic for balancing the unification of interfaces and system integration against the ability to swap different components or interfaces as new technologies are introduced? What are the most interesting, innovative, or unexpected ways that you have seen Decodable used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Decodable? When is Decodable the wrong choice? What do you have planned for the future of Decodable? Contact Info esammer on GitHub LinkedIn Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers Links Decodable Podcast Episode Understanding the Apache Flink Journey Flink Podcast Episode Debezium Podcast Episode Kafka Redpanda Podcast Episode Kinesis PostgreSQL Podcast Episode Snowflake Podcast Episode Databricks Startree Pinot Podcast Episode Rockset Podcast Episode Druid InfluxDB Samza Storm Pulsar Podcast Episode ksqlDB Podcast Episode dbt GitHub Actions Airbyte Singer Splunk Outbox Pattern The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Sponsored By:
Neo4J: NODES 2023 is a free online conference focused on graph-driven innovations with content for all skill levels. Its 24 hours are packed with 90 interactive technical sessions from top developers and data scientists across the world covering a broad range of topics and use cases. The event tracks: - Intelligent Applications: APIs, Libraries, and Frameworks – Tools and best practices for creating graph-powered applications and APIs with any software stack and programming language, including Java, Python, and JavaScript - Machine Learning and AI – How graph technology provides context for your data and enhances the accuracy of your AI and ML projects (e.g.: graph neural networks, responsible AI) - Visualization: Tools, Techniques, and Best Practices – Techniques and tools for exploring hidden and unknown patterns in your data and presenting complex relationships (knowledge graphs, ethical data practices, and data representation) Don’t miss your chance to hear about the latest graph-powered implementations and best practices for free on October 26 at NODES 2023. Go to Neo4j.com/NODES today to see the full agenda and register!Rudderstack: Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstackMaterialize: You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. That is Materialize, the only true SQL streaming database built from the ground up to meet the needs of modern data products: Fresh, Correct, Scalable — all in a familiar SQL UI. Built on Timely Dataflow and Differential Dataflow, open source frameworks created by cofounder Frank McSherry at Microsoft Research, Materialize is trusted by data and engineering teams at Ramp, Pluralsight, Onward and more to build real-time data products without the cost, complexity, and development time of stream processing. Go to materialize.com today and get 2 weeks free!Datafold: This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. Datafold leverages data-diffing to compare… |
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