In our recent paper, "Optimal periodic closure for minimizing risk in emerging disease outbreaks," published in PLoS One, we developed a technique to calculate the optimal duration of a periodic lockdown during an outbreak of an infectious disease where there is no cure or vaccine. Our findings are different from the lockdown duration being widely applied, today.
In our latest paper, “Unassisted Noise Reduction of Chemical Reaction Data Sets” in Nature Machine Intelligence, we explore the application of NLP techniques to automate the identification of “language outliers” or the noise in chemical datasets.
IBM is excited to announce the world's first ever developer certification for programming a quantum computer.
The Consortium for Sequencing the Food Supply Chain and consulting professor Dr. Bart Weimer published the results of their hypothesis that the microbiome can indicate when there is a potential issue or deviation from normal in the supply chain and help predict outbreaks or issues before they take place.
Today, we honor the one-year anniversary of the formation of the COVID-19 High Performance Computing Consortium, a ground-breaking public-private initiative that gives researchers around the globe unprecedented access to the world’s most powerful computing resources. The Consortium brings together 43 organizations from around the world, uniting academia, government, and technology companies – many of whom are typically rivals - to tackle COVID-19, sharing their knowledge in ways not possible if they were acting alone.
In a newly published paper “Quantitative language features identify placebo responders in chronic back pain” in the peer-reviewed journal PAIN, we report the first proof-of-concept that uses AI to analyze patients’ clinical trial experiences. The AI quantifies a placebo response in patients with chronic pain and distinguishes those who respond to placebo from those who do not.
In a new paper published in The Lancet’s EBioMedicine journal, “Evaluation of an Artificial Intelligence System for Assisting Neurologists with Fast and Accurate Annotation of Scalp Electroencephalography Data,” we describe the design and implementation of a new open hybrid cloud platform to manage and analyze secured epilepsy patient data.
In our recent paper “AutoAI-TS: AutoAI for Time Series Forecasting,” which we’ll present at ACM SIGMOD 2021, AutoAI Time Series for Watson Studio incorporates the best-performing models from all possible classes — as often there is no single technique that performs best across all datasets.
In our recent paper “An autonomous debating system,” published in Nature, we describe Project Debater’s architecture and evaluate its performance. We also offer free access for academic use to 12 of Project Debater’s underlying technologies as cloud APIs, as well as trial and licensing options for developers.
Our team has turned to AI to accelerate the design and discovery of better polymer membranes to efficiently separate carbon dioxide from flue gases — the results that we will present at the upcoming 2021 Meeting of the American Physical Society.
We're excited to once again host the QC40: Physics of Computation Conference with the MIT Endicott House in order to take a look back at the past 40 years of progress, review the state of the field today, and even look into the future to imagine where we'd like this field to go. We invite you to submit talks, watch panels, and engage with experts of quantum computing from then and now. We hope that, together, we can begin writing the next chapter of the history of quantum computing.