Главная
Study mode:
on
1
Intro
2
Outline
3
AI Foundation
4
The Fountainhead
5
Scaling AI
6
Fountainhead
7
Customer AI
8
Reference Architecture
9
ML Code
10
Release Strategy
11
Content Personalization
12
Teasers
13
Slot Containers
14
Contextual bandits
15
Recommendations
16
Rewards
17
Conclusion
Description:
Explore a 28-minute conference talk that delves into H&M's evolving AI platform, focusing on democratizing and accelerating AI usage across the entire H&M group. Learn about their advancements in speed to production, data abstraction, feature store, and pipeline orchestration. Discover how H&M's reference architecture has been adopted by multiple product teams, managing hundreds of models across the entire value chain. Gain insights into how this architecture enables data scientists to develop models in a highly interactive environment while allowing engineers to manage large-scale model training and serving pipelines with full traceability. Understand H&M's current efforts to reduce time-to-market for new features and shorten the learning feedback loop through AI democratization and adherence to MLOps principles. The talk covers topics such as AI Foundation, Scaling AI, Customer AI, Reference Architecture, ML Code, Release Strategy, Content Personalization, Contextual bandits, Recommendations, and Rewards. Read more

Scaling AI at H&M - Democratizing and Accelerating AI Usage

Databricks
Add to list