Скачать или смотреть Revolutionizing Retail: Vision-Language AI for Style Filters & Attribution

Join us for the USF Data Science Speaker Series featuring Shubham Shukla, a seasoned Data Scientist specializing in large-scale AI solutions across retail, healthcare, and finance. Currently at Nordstrom, he leads the development of AI applications using vision-language models, with a strong focus on fine-tuning large language models, computer vision, and generative AI. Previously, he held ML engineering roles at Amazon and HealthTap. Passionate about democratizing AI, Shubham actively works on establishing best practices and mentoring future data scientists.

In this session, Shubham will explore how digital shopping experiences can be transformed using vision-language models at scale. He will share insights from his work fine-tuning OpenAI’s CLIP and FLAVA models to power two impactful applications: an AI-driven Style Filters platform, which significantly boosted customer engagement, and an Automated Attribute Correction system, improving product discovery accuracy.
He will also dive into the technical challenges of fine-tuning models for retail-specific tasks, strategies for prompt engineering, and scaling AI solutions to serve millions of customers. Attendees will gain practical knowledge on:

Fine-tuning vision-language models for retail applications
Implementing automated product attribution systems
Scaling AI solutions in large retail environments
Measuring and maximizing the business impact of AI implementations

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