To help the developers that update legacy applications, our team has created Mono2Micro (monolith-to-microservice) – an AI assistant that modernizes legacy applications to help move them to the cloud as microservices. Our tool simplifies and speeds up the often error-prone “application refactoring” process of partitioning and preserving the original semantics of the legacy, monolith applications.
IBM researchers have created an AI-powered software to help doctors develop personalized treatments for different patients with the exact same diagnosis.
Our latest breakthrough in AI training, detailed in a paper presented at this year’s NeurIPS conference, is expected to dramatically cut AI training time and cost. So considerably in fact that it could help completely erase the blurry border between cloud and edge — offering a key technological upgrade for hybrid cloud infrastructures.
Researchers from our IBM Research labs around the world and from IBM Watson Health have contributed a total of 47 workshops, papers, posters and panels that will be presented at AMIA 2020. These contributions cover a wide range of topics but reflect our overarching goal of driving the usefulness of AI in Healthcare.
The Rensselaer-IBM Artificial Intelligence Research Collaboration advances breakthroughs in more robust and secure AI
Launched in 2018, the Rensselaer-IBM Artificial Intelligence Research Collaboration (AIRC) is a multi-year, multi-million dollar joint venture boasting dozens of ongoing projects in 2020-2021 involving more than 80 IBM and RPI researchers working to advance AI.
The International Semantic Web Conference (ISWC) 2020, the premier international forum for the Semantic Web and Linked Data Community, is being held November 1 - 6, 2020. IBM Research AI is proud to participate in this conference as a platinum sponsor.
Our team of researchers based at the IBM Research-Almaden lab in California have been pursuing an ambitious challenge of building machines that can perform a preliminary read of chest X-rays provably at the level of at least entry-level radiologists.
IBM Research is developing new ways to use AI to assure clients are moving their mission-critical workloads to a secure cloud environment and can manage those workloads across multiple clouds.
A new AI model, developed by IBM Research and Pfizer, has used short, non-invasive and standardized speech tests to help predict the eventual onset of Alzheimer’s disease within healthy people with an accuracy of 0.7 and an AUC of 0.74 (area under the curve).
AI’s unprecedented demand for data, power and system resources poses the greatest challenge to realizing this optimistic vision of the future. To meet that demand, we’re developing a new class of inherently energy-efficient AI hardware accelerators that will increase compute power by orders of magnitude, in hybrid cloud environments, without the demand for increased energy.
I believe one of the most promising areas for AI to make an impact is in the field of medical imaging. Through advancements in AI that allow for more intelligent and accurate analysis of video and still images, there is hope that clinicians will soon be able to widely augment the data and information they […]
Today we make a great move on AI research in Brazil by announcing that IBM, University of São Paulo (USP) and FAPESP (São Paulo State Research Foundation) are inaugurating the Center for Artificial Intelligence (C4AI) in Brazil, dedicated to developing cutting-edge studies and research on AI to address topics of great social and economic impact. […]