Amazon’s annual machine learning conference focuses on community and connections

Amazon’s annual internal science conference occurred recently, featuring keynote and oral presentations, workshops and tutorials aimed at highlighting the high-quality science behind many of the company’s businesses, and creating connections among scientists and engineers working on similar challenges within different businesses, or among scientists with similar research interests.

This year’s Amazon Machine Learning Conference (AMLC) was a hybrid event featuring an in-person component in Dallas, TX, and a virtual experience open to Amazon employees worldwide. Joseph Sirosh, vice president of Alexa Shopping, opened the in-person event by telling attendees, “Together, we are building culture, community and shared context for the transformational technology of our generation.”

Other internal speakers included Yoelle Maarek, Alexa Shopping vice president of research and science, who defined what the company means by customer-obsessed science; Alex Smola, vice president and distinguished scientist, Amazon Web Services Deep Learning, whose talk focused on AWS AutoML for text and images; and Trishul Chilimbi, vice president and distinguished scientist, Amazon Search Science, who provided a description of the company’s artificial intelligence (AI) flywheel, and how AI models are fueled with data.

“Since its inception in 2013, AMLC has focused on providing learning and teaching opportunities primarily for our science and engineering communities,” said Muthu Muthukrishnan, the event’s executive sponsor, and vice president of sponsored products, Performance Advertising Technology. “Our goal is to create community and connections that allow us to continually raise the bar on scientific and engineering inventions on behalf of our customers.”

The event also included five keynote presentations by members of the global academic community: Pascale Fung, chair professor of the Hong Kong University of Science and Technology (HKUST) Department of Electronic and Computer Engineering; Fei-Fei Li, the inaugural Sequoia Professor in the Stanford University Computer Science Department, and co-director of Stanford’s Human-Center AI Institute; Linda Smith, distinguished professor and chancellor’s professor within the Indiana University Department of Psychological and Brain Sciences; Eric Topol, Gary and Mary West Endowed Chair of Innovative Medicine at Scripps Research Institute, and professor of molecular medicine and director and founders of Scripps Research Translational Institute; and Antonio Torralba, the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science at MIT, and investigator at MIT’s Computer Science and Artificial Intelligence Laboratory.

Several of the external presenters’ talks have been made publicly available; each is provided below.