More than 80 Amazon scientists and engineers will attend this year's International Conference on Machine Learning (ICML) in Stockholm, Sweden, with 11 papers co-authored by Amazonians being presented. "ICML is one of the leading outlets for machine learning research," says Neil Lawrence, director of machine learning for Amazon's Supply Chain Optimization Technologies program. "It's a great opportunity to find out what other researchers have been up to and share some of our own learnings." At ICML, members of Lawrence's team will present a paper titled "Structured Variationally Auto-encoded Optimization," which describes a machine-learning approach to optimization, or choosing the values for variables in some process that maximize a particular outcome. The first author on the paper is Xiaoyu Lu, a graduate student at the University of Oxford who worked on the project as an intern at Amazon last summer, then returned in January to do some follow-up work.
Assuming the decision maker behaves according to the EU model, we investigate the elicitation of generalized additively decomposable utility functions on a product set (GAI-decomposable utilities). We propose a general elicitation procedure based on a new graphical model called a GAI-network. The latter is used to represent and manage independences between attributes, as junction graphs model independences between random variables in Bayesian networks. It is used to design an elicitation questionnaire based on simple lotteries involving completely specified outcomes. Our elicitation procedure is convenient for any GAI-decomposable utility function, thus enhancing the possibilities offered by UCP-networks.
The first time I met Alexa, the A.I. robot voice inside the wine-bottle-size speaker known as the Amazon Echo, I was at my friends' house, in rural New England. "Currently, it is seventy-five degrees," she told us, and assured us that it would not rain. This was a year ago, and I'd never encountered a talking speaker before. When I razzed my friend for his love of gadgetry, he showed me some of Alexa's other tricks: telling us the weather, keeping a shopping list, ordering products from Amazon. This summer, Alexa decided again and again who the tickle monster's next victim was, saying their children's adorable nicknames in her strange A.I. accent.
Reasoning about preferences is a major issue in many decision making problems. Recently, a new logic for handling preferences, called Qualitative Choice Logic (QCL), was presented. This logic adds to classical propositional logic a new connective, called ordered disjunction symbolized by . That new connective is used to express preferences between alternatives. QCL was not designed to handle conditional preferences, even if it is possible to express an implication with a preference on the left hand side, for instance "(Air France Virgin) Hotel Package".
"Alexa, help me find a job at McDonald's." That's how interested job seekers can start an application with the global fast-food company, McDonald's recently announced. Claiming it to be the world's first voice-initiated job application process, the company has launched McDonald's Apply Thru, which works on Amazon Alexa and Google Assistant. The app is currently available in the United States, Australia, Canada, France, Germany, Ireland, Italy, Spain and the United Kingdom and is expected to roll out to other countries in the coming months. Once Alexa or Google Assistant responds, users are asked to provide basic information, such as their name, contact information, job area of interest and location. Potential applicants then receive a text message with a link to the McDonald's careers site to continue their application process.