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.
Watch the replay of the virtual roundtable, “Talking in Code: The New Frontier for AI and Hybrid Cloud,” with researchers from IBM, Columbia University and North Carolina State University discussing how AI can simplify and streamline hybrid cloud environments as well as make them more secure for mission-critical workloads.
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).
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 […]
State-of-the-Art Results in Conversational Telephony Speech Recognition with a Single-Headed Attention-Based Sequence-to-Sequence Model
Powerful neural networks have enabled the use of “end-to-end” speech recognition models that directly map a sequence of acoustic features to a sequence of words. It is generally believed that direct sequence-to-sequence speech recognition models are competitive with traditional hybrid models only when a large amount of training data is used. However, in our recent […]