The future of machine learning at Pinterest
One of the key ways we provide relevant and scalable solutions is through building distributed systems using machine learning. To accelerate our work in discovery and monetization, today we’re announcing the acquisition of Kosei, which includes some of the best minds in machine learning and data science.
Over the past year, Kosei has been building a unique technology stack that drives commerce by making highly personalized and powerful product recommendations, as well as creating a system that contains more than 400 million relationships between products. As we build a discovery engine for all objects, Kosei is a perfect fit for our team. Welcome, Kosei!
Today, machine learning is used across Pinterest in areas such as:
- The Black Ops team uses classification to detect spam content and users
- The Discovery team (which includes search and recommendations) provides recommendations, related content, and predicts the likelihood that a person will Pin content
- Our Visual Discovery team is working with cutting-edge deep learning algorithms to do object recognition and related object recommendations
- The Monetization team does ad performance and relevance prediction
- The Growth team has begun to move into the realm of using intelligence models to determine which emails to send and prevent churn
- The Data team is building out a distributed system for machine learning using Spark, so the learning can be efficient and potentially real-time
As people use Pinterest to save and discover the things they want to do in the future, we have a unique and growing data set of more than 30 billion Pins that will only get more powerful over time. With the addition of the Kosei team, we can supercharge our existing graph to help brands reach people at the right moments, and improve content for Pinners.
If you’re interested in tackling machine learning challenges, join us!
Michael Lopp is head of engineering at Pinterest