QS Investors Innovator Series with Caltech
The QS Investors Innovator Series with Caltech is a joint project that focuses on innovation, innovators and the disruption they are creating. The Series is a collaborative discussion bringing together our networks of people in different industries, business, arts, and academia to support the work that is being done in information, science, technology and engineering. It is a salon style presentation and discussion hosted by Janet Campagna (Chair, Board of QS Investors) at QS Investors New York City office. Leading minds from various backgrounds are invited to join the discussion with these disruptive forces from Caltech's impressive multi-disciplinary environment.
Trinity of Artificial Intelligence: Data + Algorithms + Cloud
Artificial Intelligence at scale requires a perfect storm of data, algorithms, and cloud infrastructure. Learn how Professor Anandkumar is innovating and integrating all three facets. She has developed efficient methods to drastically reduce data requirements for deep learning applications, while advancing scalable algorithms that can operate on a large number of dimensions and scale to multiple machines. As a principal scientist at Amazon Web Services, she has been building AI services at levels of the stack to make it easy for researchers and enterprises to deploy AI.
Caltech Professor Anima Anandkumar Presentation Video
The three ingredients for artificial intelligence are data, algorithms and computing. Many would believe that algorithms are the most crucial ingredient but its actually the data itself. Deep learning systems are usually powered by label data which requires humans to code vast amounts of data. Deep learning involves multiple layers of data processing to detemine relationships among different samples of data. The most successful deep learning application so far has been in computer vision and breakthroughs in applications such as face recognition to medical imaging are leading the way in impacting our lives.
Audience Q&A: Transparency Versus Complexity of Models?
Professor Anima Anandkumar and attendees discuss spurious correlations, data distributional shifts in natural image processing compared to financial data, and the need for extensive testing.
Audience Q&A: Can Robots Learn Ethics from Data Sets?
Professor Anima Anandkumar and attendees discuss autonomous systems like self driving cars and the ethics involved in simulating different scenarios for autonomous system decision making.
Important Information: The material is for informational purposes only and is not intended to be relied upon to make any investment decision.The opinions and views discussed in these videos are for educational purposes only and are not endorsed by QS Investors and/or meant as investment advice or guidance. The views expressed in these videos are soley the views of the individual speakers. Any company included in this presentation is mentioned for educational purposes only and is not an endorsement for or an offer or solicitation to purchase or sell any related security.
QSCR 18225 (August 2018)