The "quantum chandelier" that sits within a glass box in the chapel at Rensselaer Polytechnic Institute's campus in Troy, New York, is the symbolic centerpiece of an ambitious effort to turn upstate New York into an advanced technology center – what Silicon Valley is to social media or Cambridge, Massachusetts, is to biotech. The silver sci-fi object, named for interior gold lattices that suspend, cool and isolate its processor, is the heart of a "quantum computing system" that could herald a new age of computing. It's the centerpiece of the dream Curtis Priem, a co-founder of Nvidia, the 2.8tn artificial intelligence hardware and software company, has of turning Rensselaer, or RPI, into an advanced computing hub and refashioning this area of upstate New York into a new Silicon Valley. Priem has invested a sizable chunk of his fortune into building the Curtis Priem Quantum Constellation – a workshop for RPI students' vision of a quantum computing future. Just as his partners at Nvidia, where he was the company's first chief technology officer, gave him the freedom to imagine graphics chip architecture that powers the AI revolution, he hoped his investment will spark a new era of computer-powered innovation in the region.

Bioimaging technologies are the eyes that allow doctors to see inside the body in order to diagnose, treat, and monitor disease. Ge Wang, an endowed professor of biomedical engineering at Rensselaer Polytechnic Institute, has received significant recognition for devoting his research to coupling those imaging technologies with artificial intelligence in order to improve physicians' "vision." In research published today in Patterns, a team of engineers led by Wang demonstrated how a deep learning algorithm can be applied to a conventional computerized tomography (CT) scan in order to produce images that would typically require a higher level of imaging technology known as dual-energy CT. Wenxiang Cong, a research scientist at Rensselaer, is first author on this paper. Wang and Cong were also joined by coauthors from Shanghai First-Imaging Tech, and researchers from GE Research.

Bioimaging technologies are the eyes that allow doctors to see inside the body in order to diagnose, treat, and monitor disease. Ge Wang, an endowed professor of biomedical engineering at Rensselaer Polytechnic Institute, has received significant recognition for devoting his research to coupling those imaging technologies with artificial intelligence in order to improve physicians' "vision." In research published today in Patterns, a team of engineers led by Wang demonstrated how a deep learning algorithm can be applied to a conventional computerized tomography (CT) scan in order to produce images that would typically require a higher level of imaging technology known as dual-energy CT. Wenxiang Cong, a research scientist at Rensselaer, is first author on this paper. Wang and Cong were also joined by coauthors from Shanghai First-Imaging Tech, and researchers from GE Research.

In research published today in Patterns, a team of engineers led by Wang demonstrated how a deep learning algorithm can be applied to a conventional computerized tomography (CT) scan in order to produce images that would typically require a higher level of imaging technology known as dual-energy CT. Wenxiang Cong, a research scientist at Rensselaer, is first author on this paper. Wang and Cong were also joined by coauthors from Shanghai First-Imaging Tech, and researchers from GE Research. "We hope that this technique will help extract more information from a regular single-spectrum X-ray CT scan, make it more quantitative, and improve diagnosis," said Wang, who is also the director of the Biomedical Imaging Center within the Center for Biotechnology and Interdisciplinary Studies (CBIS) at Rensselaer. Conventional CT scans produce images that show the shape of tissues within the body, but they don't give doctors sufficient information about the composition of those tissues.

Part of a collaboration between IBM, Empire State Development (ESD), and NY CREATES, the eight petaflop IBM POWER9-equipped AI supercomputer is configured to help enable users to explore new AI applications and accelerate economic development from New York's smallest startups to its largest enterprises. Named AiMOS (short for Artificial Intelligence Multiprocessing Optimized System in honor of Rensselaer co-founder Amos Eaton, the machine will serve as a test bed for the New York State - IBM Research AI Hardware Center, which opened on the SUNY Polytechnic Institute (SUNY Poly) campus in Albany earlier this year. The AI Hardware Center aims to advance the development of computing chips and systems that are designed and optimized for AI workloads to push the boundaries of AI performance. AiMOS will provide the modeling, simulation, and computation necessary to support the development of this hardware. "Computer artificial intelligence, or more appropriately, human augmented intelligence (AI), will help solve pressing problems, from healthcare to security to climate change. In order to realize AI's full potential, special purpose computing hardware is emerging as the next big opportunity," said Dr. John E. Kelly III, IBM Executive Vice President.

Sophisticated machine learning applications require not only enormous amounts of training data, but powerful computer hardware on which to train.

Sophisticated machine learning applications require not only enormous amounts of training data, but powerful computer hardware on which to train. An analysis conducted by San Francisco research firm OpenAI found that since 2012, the amount of compute used in the largest training runs has been increasing exponentially with a 3.4-month doubling time, and that it's grown by more than 300,000 times over that same time period. The trend spurred the development of supercomputers like the U.S. Department of Energy's Sierra and Summit, which leverage dedicated accelerator chips to speed up AI computation. Now, IBM's Hardware Center, in collaboration with New York State, SUNY Polytechnic Institute, and other members of IBM's AI Hardware Center, has delivered a new machine for the Department of Computer Science at Rensselaer Polytechnic Institute (RPI) that's optimized for state-of-the-art machine learning workloads. It's dubbed Artificial Intelligence Multiprocessing Optimized System, or AiMOS (in honor of Rensselaer cofounder Amos Eaton), and it will principally tackle projects in biology, chemistry, the humanities, and related domains underway at the new IBM Research AI Hardware Center on the SUNY campus in Albany.

In partnership with local health insurer, CDPHP, researchers from the Institute for Data Exploration and Applications (IDEA) at Rensselaer Polytechnic Institute are using artificial intelligence to improve patient health by developing a better understanding of high needs patients and identifying aspects of care that lead to better outcomes. "It's not enough to just figure out who are the highest needs patients, you really need to know why and what approaches can help them," said Kristin Bennett, a Rensselaer math professor and associate director of IDEA. "Our approach develops explainable models that help us understand who these high needs patients are, why some people in this group do well, and some do not." The project builds on the "cadre" modeling technique developed by Bennett. As opposed to deep learning, in which a computer identifies a pattern but the path to its decision is not clear, cadre models bring another level of understanding into the equation.

Apple has just agreed to settle a long-running patent lawsuit for almost 25 million. The lawsuit, filed by a company called Dynamic Advances, claimed that Apple had infringed on a patent involving "user interfaces that recognize natural language." The patent describes a method for "providing, through a user interface, a result of [a] search" using natural language queries of a number of connected databases. The patent had been originally granted as far back as 2007 to the Rensselaer Polytechnic Institute in upstate New York. Rensselaer, an engineering-focused university, then licensed the patent to Dynamic Advances. When Apple came out with Siri in 2011, Dynamic Advances sued the tech giant the following year, saying it had infringed on the patent.