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Google has open sourced CEL-expr-python, a Python implementation of the Common Expression Language (CEL), a non-Turing complete embedded policy and expression language designed for simplicity, speed, safety, and portability.
Form3 runs UK bank payments across three clouds simultaneously. At QCon London, their engineers explained how they built their custom Kubernetes operators, cross-cloud DNS tricks, and distributed databases, and what happened when they tried to sell them in America. Spoiler: US customers wanted East/West failover, not triple-active multi-cloud.
At QCon London 2026, Yinka Omole, Lead Software Engineer at Personio, presented a session exploring a recurring dilemma engineers face, whether to spend time mastering the newest technologies and frameworks or to invest in deeper, foundational problems that may appear less exciting but deliver long-term value.
DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared embedding space. Trained on 32 million labeled query-product pairs using contrastive learning, the system improves semantic search, product ranking, and advertising relevance. Embeddings also support other machine learning tasks across the marketplace.
Stefan Dirnstorfer discusses the shift from DOM-based testing to visual UI agents. He explains why LLMs often fail at precision tasks - like spotting one-pixel shifts or broken road networks - and shares how advanced image registration and "Chain-of-Thought" vision processing are essential for reliable QA. Learn why combining generative AI with classical algorithms is the future of automation.
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Google Open-Sources the Common Expression Language for Python
Google has open sourced CEL-expr-python, a Python implementation of the Common Expression Language (CEL), a non-Turing complete embedded policy and expression language designed for simplicity, speed, safety, and portability.
By Sergio De SimoneQCon London 2026: How To Run on Three Clouds at Once, and When Not To
Form3 runs UK bank payments across three clouds simultaneously. At QCon London, their engineers explained how they built their custom Kubernetes operators, cross-cloud DNS tricks, and distributed databases, and what happened when they tried to sell them in America. Spoiler: US customers wanted East/West failover, not triple-active multi-cloud.
By Steef-Jan WiggersQCon London 2026: The Hidden Power of Boring Problems
At QCon London 2026, Yinka Omole, Lead Software Engineer at Personio, presented a session exploring a recurring dilemma engineers face, whether to spend time mastering the newest technologies and frameworks or to invest in deeper, foundational problems that may appear less exciting but deliver long-term value.
By Daniel DominguezDoorDash Builds DashCLIP to Align Images, Text, and Queries for Semantic Search Using 32M Labels
DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared embedding space. Trained on 32 million labeled query-product pairs using contrastive learning, the system improves semantic search, product ranking, and advertising relevance. Embeddings also support other machine learning tasks across the marketplace.
By Leela KumiliPresentation: Image Processing for Automated Tests
Stefan Dirnstorfer discusses the shift from DOM-based testing to visual UI agents. He explains why LLMs often fail at precision tasks - like spotting one-pixel shifts or broken road networks - and shares how advanced image registration and "Chain-of-Thought" vision processing are essential for reliable QA. Learn why combining generative AI with classical algorithms is the future of automation.
By Stefan Dirnstorfer