After uncovering a new Nasca Line formation with IBM Watson Machine Learning Accelerator on IBM Power Systems, Yamagata University will deploy IBM PAIRS in the hopes of further discoveries with AI.
IBM Research is embarking on a multi-year, collaborative effort with Wells Fargo focused on research and learning that is intended to enhance the company’s artificial intelligence and quantum computing capabilities. Together with IBM Research, Wells Fargo plans to accelerate its learnings to inform innovation initiatives that reimagine the future of financial services in a way that is designed to deliver customer experiences that are simple, fast, safe and convenient.
IBM Research is the first founding corporate partner of the Stanford Institute for Human-Centered Artificial Intelligence.
The research and development of machine learning (ML) across various domains, such as computer vision, natural language processing, and speech transcription has been growing rapidly. ML is important in many enterprise applications across industries such as manufacturing, finance, healthcare, and marketing. With the growing adoption of ML, it is increasingly challenging to design or choose […]
The fourth-quarter issue of the IBM Journal of Research & Development is dedicated to the exploration and deployment of hardware for AI systems. It contains 10 contributions from leading authorities in the fields that summarize the latest state of the art and share new research results.
IBM Research and its university partners including: UC Santa Cruz; Cornell University and Cornell Tech; University of Illinois at Urbana Champagne; Oregon State University are collaborating on new programming systems and languages to build secure cryptographic applications.
Starting this month, experts at IBM Research, Wits University, University of the Western Cape, Umvoto Africa and Delta-H, who know how to deploy these technologies in South Africa, are starting a new pilot to develop news techniques, which are more user-friendly in the regional context.
IBM Research AI's contributions at CSCW 2019 reflect its participation in defining the emerging academic sub-discipline of Human-Centered Data Science (HCDS).
Qiskit has the flexibility to target different underlying quantum hardware with minimal additions to its code base. To demonstrate this, we have recently added support in Qiskit for trapped ion-based quantum computing devices, and enabled access to the five-qubit trapped ion device at the University of Innsbruck, hosted by Alpine Quantum Technologies.
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.
At ICCV 2019, IBM researchers propose a new “Moment Matching” method that learns implicit generative models by matching statistics from perceptual features extracted from pre-trained convolutional neural networks.