Large-scale machine learning at Facebook: Implications of platform design on developer productivity
AI plays a key role in achieving Facebook's mission of connecting people and building communities. Nearly every visible product is powered by machine learning algorithms at its core, from delivering relevant content to making the platform safe. Kim Hazelwood and Mohamed Fawzy explain how applied ML has continued to change the landscape of the platforms and infrastructure at Facebook.
| Talk Title | Large-scale machine learning at Facebook: Implications of platform design on developer productivity |
| Speakers | Kim Hazelwood (Facebook), Mohamed Fawzy (Facebook) |
| Conference | O’Reilly Artificial Intelligence Conference |
| Conf Tag | Put AI to Work |
| Location | London, United Kingdom |
| Date | October 15-17, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | Talk Video |
AI plays a key role in achieving Facebook’s mission of connecting people and building communities. Nearly every visible product is powered by machine learning algorithms at its core, from delivering relevant content to making the platform safe. Scaling these products to billions of global users has uncovered many fascinating challenges at every layer in the systems stack, such as uncovering computational and storage bottlenecks, making the ML platform efficient and productive for the ML engineers and tackling critical challenges such as privacy and environmental sustainability. Kim Hazelwood and Mohamed Fawzy offer an end-to-end look at how applied ML has continued to change the landscape of the platforms and infrastructure at Facebook.
