Recommendation systems challenges at Twitter scale
Twitter has amazing and unique content generated at an enormous velocity internationally in multiple languages. Ashish Bansal provides you with insight into the unique recommendation system challenges at Twitters scale and what makes this a fun and challenging task.
| Talk Title | Recommendation systems challenges at Twitter scale |
| Speakers | Ashish Bansal (Twitter) |
| Conference | O’Reilly Artificial Intelligence Conference |
| Conf Tag | Put AI to Work |
| Location | San Jose, California |
| Date | September 10-12, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Twitter has amazing and unique content generated at an enormous velocity internationally in multiple languages. A constant challenge is how to find the relevant content for users so that they can engage in the conversation. Many traditional recommendation systems approaches don’t work directly at the scale. Ashish Bansal provides a window into the world of fast-moving recommendations at massive scale and shares practical ideas on why this is such a fun problem to work on.
