Senthil Padmanabhan, VP of Platform and Infrastructure at eBay, discusses how eBay’s use of fine-tuning is improving their operational workflows. He explains why fine-tuning existing models can often be more cost-effective than training from scratch, and how methods like low-ranking adaptation (LoRa) are pivotal in improving AI performance.
Key Takeaways:
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The impact of strategic fine tuning on achieving peak performance
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AI's broader impact on eBay's infrastructure, fraud detection, and customer-facing experiences
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The challenges of tech debt and software upgrades
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Case studies from eBay that illustrate productivity gains via fine-tuning
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Considerations for choosing between open and proprietary AI models
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The importance of data quality over quantity in fine-tuning processes
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Predictions for the future of AI development and fine-tuning techniques
Guest Bio: Senthil Padmanabhan is a Vice President and Technical Fellow at eBay, where he runs Platform and Infra (private cloud) Engineering for the global eCommerce marketplace, providing infrastructure for 4000+ engineers to deliver products at scale. Before this role, he was in the Product engineering space, building consumer-facing applications at eBay and Yahoo.
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About this Show:
The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all!
Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together.
The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API.
Music by: Ari Dvorin
Produced by: Sam Laliberte
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