{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Tech on the Rocks","title":"Unifying structured and unstructured data for AI: Rethinking ML infrastructure with Nikhil Simha and Varant Zanoyan","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/ff7e5e8f\"></iframe>","width":"100%","height":180,"duration":3705,"description":"In this episode, we dive deep into the future of data infrastructure for AI and ML with Nikhil Simha and Varant Zanoyan, two seasoned engineers from Airbnb and Facebook. Nikhil and Varant share their journey from building real-time data systems and ML infrastructure at tech giants to launching their own venture.\nThe conversation explores the intricacies of designing developer-friendly APIs, the complexities of handling both batch and streaming data, and the delicate balance between customer needs and product vision in a startup environment.\nContacts & Links\nNikhil Simha\nVarant Zanoyan\nChronon project\n\nChapters\n00:00 Introduction and Past Experiences\n04:38 The Challenges of Building Data Infrastructure for Machine Learning\n08:01 Merging Real-Time Data Processing with Machine Learning\n14:08 Backfilling New Features in Data Infrastructure\n20:57 Defining Failure in Data Infrastructure\n26:45 The Choice Between SQL and Data Frame APIs\n34:31 The Vision for Future Improvements\n38:17 Introduction to Chrono and Open Source\n43:29 The Future of Chrono: New Computation Paradigms\n48:38 Balancing Customer Needs and Vision\n57:21 Engaging with Customers and the Open Source Community\n01:01:26 Potential Use Cases and Future Directions","thumbnail_url":"https://img.transistorcdn.com/UA-KG4zXoEeEh4XuiVMdD9yAhMnDJ2YVfAhHWI5inpc/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80ZWI0/YjY4MDc1YmU2MDI0/MTNkNjYwZWYwYzky/ZGEyNi5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}