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Erik Bernhardsson, the CEO and co-founder of Modal Labs, joins Tristan to talk about Gen AI, the lack of GPUs, the future of cloud computing, and egress fees. They also discuss whether the job title of data engineer is something we should want more or less of in the future. Erik's not afraid of a spicy take, so this is a fun one.  For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

Join PyData NYC at 11 Times Square (Microsoft) on May 8th at 6:30 pm for a talk night with Jim Dowling (CEO of Hopsworks) and Eric Bernhardsson (CEO of Modal Labs). Please bring your 💻 to code along and sign up with your government official name!

🍕 Pizza, drinks & venue sponsored by Microsoft Reactor - thank you!

Agenda: Modular AI Systems with Feature, Training, Inference Pipelines on Hopsworks - a LLMOps Tutorial Speaker: Jim Dowling In this tutorial, we will introduce a unified architecture for Batch, Real-Time, and LLM AI Systems based around three independent ML pipelines - * a feature pipeline to create feature data, * a training pipeline to train your model, * and an inference pipeline to make predictions with new data on your trained model. We will use this FTI architecture to walk through a tutorial of building a LLM system that uses RAG and function calling to access structured data and a model.

Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform and the organizer of the annual feature store summit. He is writing a book for O'Reilly on Building AI systems with a Feature Store - batch, real-time, and LLMs.

Introduction to Modal Speaker: Erik Bernhardsson Modal's platform empowers data/AI/ML teams to develop faster at lower cost, while scaling production workloads to thousands of CPUs and GPUs.

Networking Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations.

---------------------------------------------------------------- RSVP is required; please note that walk-ins will not be accepted. Note: Per building policy, RSVPs will close at 12 pm on May 6th. Doors @ 6 pm Event @ 6:30 - 8:30 pm Venue provided by MSFT: 11 Times Square ---------------------------------------------------------------- The building requires a government-issued photo ID for entrance. This, and all PyData NYC events, is an all-level event. Newcomers and beginners are welcome. This, and all NumFOCUS-affiliated events and spaces, both in-person and online, are governed by a Code of Conduct. ---------------------------------------------------------------- This event may be recorded.

ABOUT THE TALK: In this talk, Erik Bernhardsson will share how Modal starts 1000s of large containers in seconds, and what they had to do under the surface to build this. This includes a custom file system written in Rust, their own container runtime, and their own container image builder. This talk will give you an idea of how containers work along with some of the low-level Linux details underneath. We'll also talk about many infrastructure tools hold data teams back, and why they deserve faster and better tools.

ABOUT THE SPEAKER: Erik Bernhardsson is the founder and CEO of Modal, which is an infrastructure provider for data teams. Before Modal, Erik was the CTO at Better for six years, and previously spent seven years at Spotify, building the music recommendation system and running data teams.

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Erik Bernhardsson spent six years at Spotify, where he contributed to the first version of the music recommendation system. After a stint as CTO at Better.com, he's now working on building new infrastructure tooling for data teams. In this wide-ranging conversation with Tristan & Julia, Erik dives into the nuts and bolts of Spotify's recommendation algorithm, (paradoxically) why you should rarely need to use ML, and the fundamental infrastructure challenges that drag down the productivity of data teams. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.