AI/ML
Chronon - Mixed-Workload Data Processing Framework
Tuesday Mar 17 / 02:45PM GMT
Chronon is a data processing framework open-sourced by Airbnb. It is adopted across organizations like Stripe, Netflix, OpenAI, and Uber. Chronon was originally built for ML applications.
Nikhil Simha
Co-Founder & CTO @zipline.ai, Author of "Chronon Feature Platform", Previously @Airbnb, @Meta, and @Walmartlabs
Behind Booking.com's AI Evolution: The Unpolished Story
Monday Mar 16 / 11:45AM GMT
It’s easy to look at a mature AI platform and imagine a grand blueprint. Ours began with none. What started as a few data scientists hacking on Perl scripts and Mysql queries has grown into an AI platform that impacts millions of travel decisions every day.
Jabez Eliezer Manuel
Principal Engineer @Booking.com - Building Next-Gen AI Platform
Your Multicloud Strategy Is a Product Problem - Treat It Like One
Monday Mar 16 / 11:45AM GMT
You can't really "opt out" of multicloud anymore. Between cloud concentration risk, SaaS sprawl, and increasing regulatory expectations, most enterprises end up operating across multiple clouds whether they planned to or not. The hard part isn't having two or three providers.
Luis Henrique Albinati Junior
Executive Director, Product Strategy @JP Morgan Chase, Previously @Microsoft, @Oracle, and @Red Hat
Surabhi Mahajan
Executive Director @JP Morgan Chase
Beyond Benchmarks: How Evaluations Ensure Safety at Scale in LLM Applications
Wednesday Mar 18 / 11:45AM GMT
As LLM systems move from prototypes to production, the gap between benchmark performance and real-world reliability becomes impossible to ignore. Models that score well on benchmarks can still fail unpredictably when facing the complexity, ambiguity, and edge cases of real users.
Clara Matos
Director of Applied AI @Sword Health, Focused on Building and Scaling Machine Learning Systems
Machine Learning at the Edge of Scale and Speed: Nanosecond Inference at the CERN Large Hadron Collider
Wednesday Mar 18 / 10:35AM GMT
The CERN Large Hadron Collider (LHC) produces O(10,000) exabytes of raw data annually from high-energy proton collisions. Handling this volume under strict compute and storage limits requires real-time event filtering capable of processing millions of collisions per second.
Thea Klaeboe Aarrestad
Particle Physics and Real-Time ML @CERN @ETH Zürich
The Rise of the Streamhouse: Idea, Trade-Offs, and Evolution
Tuesday Mar 17 / 03:55PM GMT
Over the last decade, streaming architectures have largely been built around topic-centric primitives—logs, streams, and event pipelines—then stitched together with databases, caches, OLAP engines, and (increasingly) new serving systems.
Giannis Polyzos
Principal Streaming Architect @Ververica
Anton Borisov
Principal Data Architect @Fresha
The Ladder Is Missing Rungs: Engineering Progression When AI Ate the Middle
Tuesday Mar 17 / 01:35PM GMT
Career progression in engineering has traditionally followed a predictable path: junior tasks teach fundamentals, mid-level work builds judgment, senior roles require synthesis across systems.
Alasdair Allan
Scientist, Author, Hacker, Maker, Journalist, CTO @Negroni Venture Studios, Interim CTO @Evaro
Refreshing Stale Code Intelligence
Tuesday Mar 17 / 01:35PM GMT
Coding models are helping software developers move faster than ever, but weirdly, the models themselves are not keeping up. They are trained on months-old snapshots of open source code. They have never seen your internal codebase, let alone the code you wrote yesterday.
Jeff Smith
CEO & Co-Founder @Neoteny AI, AI Engineer, Researcher, Author, Ex-Meta/FAIR