Hybrid Cloud is rapidly becoming the go-to IT strategy for organizations seeking the perfect mix of scalability, performance and security. As a result, it is now common for an organization to rely on a mix of on-premise and cloud solutions, or “data-sources”, from different providers to store and manage their data. It doesn’t really sound […]
It is no surprise that following the massive success of deep learning technology in solving complicated tasks, there is a growing demand for automated deep learning. Even though deep learning is a highly effective technology, there is a tremendous amount of human effort that goes into designing a deep learning algorithm.
An interactive career goal recommender framework that uses dialogue to incorporate user feedback and interactively improve the recommendations.
Biophysics-inspired AI tools would provide a richer amount of information to support intraoperative decisions of surgeons during removal of cancerous tissue.
IBM Research understands data privacy for a modern business and has developed state-of-the-art solutions for protecting data in the GDPR era.
A forecasting method that is applicable to arbitrary sequences and comes with a regret bound competing against a class of methods, which includes Kalman filters.
IBM and the Danish Refugee Council developed a machine learning system to help understand migration via strategic forecasts and scenario analysis.
NeuNetS uses AI to automatically synthesize deep neural networks faster and more easily than ever before, scaling up the deployment and adoption of AI.
The Algebraic Gradient-based Solver (AGS), a novel solver for approximate marginal MAP inference, shows how ideas from planning can be used for inference.