[VDZ22] Optimizing Speed and Scale of User-Facing Analytics w Kafka and Pinot by K Wolok, T Berglund

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[VDZ22] Trojan Source: Bad Characters Are Coming for Your Code by Nicholas Boucher

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Introduction to Hyper-Optimization

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[VDZ22] Achieving an evolutionary architecture through simplicity by Urs Enzler

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Configuring \u0026 Running Large-Scale Optimization Problems with rsopt

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[VDZ22] Startup Architecture – How much “it depends”? by Michael Malcharek

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[VDZ22] Taming the event chaos with a workflow engine by Filip Hrisafov, Joram Barrez

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[VDZ22] The Call of Ctooling: The Secrets Behind Native Image Building by Edoardo Vacchi

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[VDZ22] Developer Productivity Engineering – The Next Big Thing in SW Development by Etienne Studer

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[VDZ22] Cost-effective Simulation-based Test Selection in Self-driving Cars SW by Christian Birchler

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Optimizing Speed \u0026 Scale of User-Facing Analytics Using Apache Kafka \u0026 Apache Pinot by Mark, Karin

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Westley Hennigh: Who optimizes the optimizers

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[VDZ22] Can you trust your AI? by Daniele Zonca

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[VDZ22] Vertex AI: Pipelines for your MLOps workflows by Marton Kodok

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Optimize Your Kotlin Performance - Profiling, Micro-optimizations and Precomputing

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8.2) How to deal with Erratic Results \u0026 Outliers in Optimization Profiles | Algorithmic Backtesting

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