talk-data.com

Abstract: In this talk, Claire will share how she went from a career in data science to founding an AI startup backed by Y Combinator: what are the steps along this path? How do you find "the idea," how do you find a co-founder, how do you get your first clients and funding? How do you get into Y Combinator? She will also share her vision on the next data skills to acquire: how to go from data science to AI engineering, and how to build and evaluate agentic AI.

Abstract: In this talk, we explore how to choose the most suitable image embedding models for real-world e-commerce applications such as visual search, product clustering, or duplicate detection. Based on a large-scale benchmark conducted at Adevinta (Leboncoin), we compare 20 state-of-the-art models (CLIP, DINOv2, ViT, etc.) across multiple domains and tasks. Full results are available in our paper: https://arxiv.org/abs/2504.07567, and we’ll share key insights to help practitioners make informed, task-specific model choices.