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A Fireside Chat with Hugo Bowne-Anderson and Alex Filipchik (Head of Infrastructure, Cloud Kitchens) on how machine learning (ML) and AI are evolving from niche specializations into essential engineering disciplines. Topics include engineering ML and AI at scale, the shift from specialist roles to core engineering, practical infrastructure decisions, generative AI use cases, simplifying ML adoption for engineers, and the future of data and ML engineering.

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Description: ​Join Hugo Bowne-Anderson and Alex Filipchik (Head of Infrastructure, Cloud Kitchens) for a Fireside Chat on how machine learning (ML) and AI are evolving from niche specializations into essential engineering disciplines. Alex will share his experience in transforming Cloud Kitchens' data and ML infrastructure to empower engineers, support real-time and batch processing, and ensure seamless deployment of data-driven applications.

​Key Topics of Discussion:

• Engineering ML and AI at Scale: An exploration of how Cloud Kitchens designs and manages data and ML systems, making them accessible to engineers while handling the complexities of large-scale integration.
• The Shift from Specialist Roles to Core Engineering: Why ML and AI are increasingly seen as part of the broader software engineering toolkit, and how this shift is reshaping teams and skill sets.
• ​Practical Infrastructure Decisions: Insights into the build vs. buy dilemma and how Cloud Kitchens navigates decisions around custom solutions versus leveraging external platforms. *
• Generative AI Use Cases: A look at how Cloud Kitchens applies generative AI to improve operations, automate tasks, and enhance productivity, along with the challenges and learnings from these implementations.
• ​Simplifying ML Adoption for Engineers: Discussion on lowering the barriers for engineers to adopt ML tools and practices, from intuitive tooling to better integration with existing workflows. *
• The Future of Data and ML Engineering: Alex’s thoughts on the next decade, including trends, emerging best practices, and how companies can prepare for the continuous evolution of data-powered engineering.

​This session is perfect for data engineers, software engineers, and AI/ML practitioners who are interested in making ML and AI an integral part of the software development lifecycle.

--------------------------- Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

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