Over the past month, the Chalk team has actively engaged in a national tour, both in-person and virtually, to discuss their latest technological advancements and insights in the fintech and machine learning ecosystems. At the NexGen Banking Summit in NYC, they tackled major challenges in fraud detection, highlighting innovations in inference architectures that enable rapid decision-making, and emphasized the importance of robust infrastructure for competitive advantage in fintech. In Menlo Park at VeloxCon, they showcased their Symbolic Python Interpreter, focusing on optimizing performance for complex queries and reducing CPU usage, while also exploring the balance between established and modern ML tools. At the virtual Agents & GenAI Infrastructure & Tooling Summit, they demonstrated sophisticated fraud detection techniques that integrate structured data with large language model outputs. Meanwhile, Elvis represented Chalk at both the OptimizedAI Conference in Atlanta and the Data Council in San Francisco, where discussions centered on the complexities introduced by new interoperability standards like Apache Arrow and Iceberg, underscoring Chalk's commitment to maintaining simplicity and accessibility within the modern data stack. Throughout these events, a recurring theme was the shared industry challenge of developing AI-native machine learning systems that balance speed and user-friendliness, aligning with Chalk's mission to enhance existing tools to meet contemporary needs without abandoning proven solutions.