Low-Resource Languages as Stress Tests for NLP Data
Low-resource languages expose weaknesses in NLP systems that are often hidden by benchmark data. Drawing on experience annotating fieldwork data, this talk shows how ambiguity and annotation decisions reveal fundamental data quality issues relevant to real-world NLP pipelines.
Apache Spark Declarative Pipelines in Action
Learn Spark 4.1’s brand-new Declarative Pipelines, a paradigm shift replacing imperative code with simple declarations. We’ll build a real-time data pipeline together, processing streaming ADS-B flight data from tens of thousands of aircraft overhead.
Kafi Streams: Complex Stream Processing Made Simple
You can finally stop caring about co-partitioning, state stores and eventual consistency. Kafi Streams, built on (Py)DBSP, treats streaming like batch — strongly consistent, no special concepts. An Open Source Python library for the 80% of use cases that don’t need extreme scale. Fully incremental stream processing for everyone, from day one.
AI in the physical world: from observation to discovery
In 2026, AI is moving beyond digital tasks into the physical world. It increasingly interacts with instruments, experiments, and real-world data. Physicists stand at this frontier, using deep learning, LLMs, and agents to analyze nature itself. What have we learned about AI when it meets reality?