About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Conference paper
Neuromorphic technologies for next-generation cognitive computing
Abstract
We describe IBM's roadmap for Neuromorphic Technologies to drive next-generation cognitive computing, ranging from nanodevice-based hardware for accelerating well-known supervised-learning algorithms (which happen to rely on static, labeled data), to emerging, biologically-inspired algorithms capable of learning from temporal, unlabeled data. The various hardware-centric neuromorphic projects currently underway at IBM Research will be surveyed, with a focus on the use of Non-Volatile Memory (NVM) for on-chip acceleration of the training of Deep Neural Networks (DNNs).
Related
Conference paper
Inference of Deep Neural Networks with Analog Memory Devices
Conference paper