The Future Cognitive Workforce Part 1: Announcing the AI Nanodegree with Udacity - IBM Watson

#artificialintelligence

As artificial intelligence (AI) begins to power more technology across industries, it's been truly exciting to see what our community of developers can create with Watson. Developers are inspiring us to advance the technology that is transforming society, and they are the reason why such a wide variety of businesses are bringing cognitive solutions to market. With AI becoming more ubiquitous in the technology we use every day, developers need to continue to sharpen their cognitive computing skills. They are seeking ways to gain a competitive edge in a workforce that increasingly needs professionals who understand how to build AI solutions. It is for this reason that today at World of Watson in Las Vegas we announced with Udacity the introduction of a Nanodegree program that incorporates expertise from IBM Watson and covers the basics of artificial intelligence.


The Future Cognitive Workforce Part 1: Announcing the AI Nanodegree with Udacity - IBM Watson

#artificialintelligence

As artificial intelligence (AI) begins to power more technology across industries, it's been truly exciting to see what our community of developers can create with Watson. Developers are inspiring us to advance the technology that is transforming society, and they are the reason why such a wide variety of businesses are bringing cognitive solutions to market. With AI becoming more ubiquitous in the technology we use every day, developers need to continue to sharpen their cognitive computing skills. They are seeking ways to gain a competitive edge in a workforce that increasingly needs professionals who understand how to build AI solutions. It is for this reason that today at World of Watson in Las Vegas we announced with Udacity the introduction of a Nanodegree program that incorporates expertise from IBM Watson and covers the basics of artificial intelligence.


An Online Learning Method for Improving Over-subscription Planning

AAAI Conferences

Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we investigate the effectiveness of learning approaches for improving over-subscription planning, a problem that has received significant recent interest. Viewing over-subscription planning as a domain-independent optimization problem, we adapt the STAGE (Boyan and Moore 2000) approach to learn and improve the plan search. The key challenge in our study is how to automate the feature generation process. In our case, we developed and experimented with a relational feature set, based on Taxonomic syntax as well as a propositional feature set, based on ground-facts. The feature generation process and training data generation process are all automatic, making it a completely domain-independent optimization process that takes advantage of online learning. In empirical studies, our proposed approach improved upon the baseline planner for over-subscription planning on many of the benchmark problems.


Worst-Case Bounds for Gaussian Process Models

Neural Information Processing Systems

Dean P. Foster University of Pennsylvania We present a competitive analysis of some nonparametric Bayesian algorithms ina worst-case online learning setting, where no probabilistic assumptions about the generation of the data are made. We consider models which use a Gaussian process prior (over the space of all functions) andprovide bounds on the regret (under the log loss) for commonly usednon-parametric Bayesian algorithms -- including Gaussian regression and logistic regression -- which show how these algorithms can perform favorably under rather general conditions.


Artificial Intelligence and Risk Communication

AAAI Conferences

The challenges of effective health risk communication are well known. This paper provides pointers to the health communication literature that discuss these problems. Tailoring printed information, visual displays, and interactive multimedia have been proposed in the health communication literature as promising approaches. On-line risk communication applications are increasing on the internet. However, potential effectiveness of applications using conventional computer technology is limited. We propose that use of artificial intelligence, building upon research in Intelligent Tutoring Systems, might be able to overcome these limitations.