Anima Anandkumar (California Institute of Technology)
AI at scale requires a perfect storm of data, algorithms and cloud infrastructure. Modern deep learning has relied on large labeled datasets for training. However, such datasets are not easily available in all domains, and are expensive/difficult to collect. By building intelligence into data collection and aggregation, we can drastically reduce data requirements. Additionally, algorithmic and infrastructure innovations now make it possible to train models at scale. In the future, we will see more integration of these three pillars to advance AI.
Light refreshments will be served before the lecture at 3:30 p.m.