IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19
IBM Research is making available multiple novel, free resources to help healthcare researchers, doctors and scientists around the world accelerate COVID-19 drug discovery.
This month, we are highlighting the work of four women researchers at IBM who are pushing the frontiers of AI technology. Their efforts extend from work process automation to the design of ever more intelligent chatbots to the discovery of new, more effective antibiotics.
Researchers from the IBM AI Hardware Center will showcase at IEDM and NeurIPS new analog devices, algorithmic and architectural solutions, a novel model training technique, and a full custom design.
IBM researchers from our labs around the world will present more than 100 papers across regular sessions and workshops at NeurIPS. They are all focused on different core technologies and use cases of AI. And a number of them will be on display in booth #111 with demos scientists will be presenting throughout the week.
IBM Research is the first founding corporate partner of the Stanford Institute for Human-Centered Artificial Intelligence.
IBM Research AI's contributions at CSCW 2019 reflect its participation in defining the emerging academic sub-discipline of Human-Centered Data Science (HCDS).
New empirical work from the MIT-IBM Watson AI Lab uncovers how jobs will transform as AI and new technologies continue to scale across business and industries. We created a novel dataset using machine learning techniques on 170 million U.S. job postings. The dataset and research, The Future of Work: How New Technologies Are Transforming Tasks, allow us to extract key insights into how AI is shaping the future of work.
IBM researchers are extending IBM RXN for Chemistry, a cloud-based app that takes the idea of relating organic chemistry to a language, by training the model to determine the chemicals needed to create a target molecule.
In a recently published paper in this year’s INTERSPEECH, we were able to achieve additional improvement on the efficiency of Asynchronous Decentralized Parallel Stochastic Gradient Descent, reducing the training time from 11.5 hours to 5.2 hours using 64 NVIDIA V100 GPUs.
IBM scientists presented three papers at INTERSPEECH 2019 that address the shortcomings of End-to-end automatic approaches for speech recognition - an emerging paradigm in the field of neural network-based speech recognition that offers multiple benefits.
As more bikes take to the city streets than ever, researchers at RMIT have designed Ari, a smart e-bike that could help riders cruise the ‘green wave’.