Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Federated learning (FL) has emerged as a popular machine learning paradigm which allows multiple data owners to train models collaboratively with out sharing their raw datasets. It holds potential for ...

A Cornell research group led by Prof. Peter McMahon, applied and engineering physics,has successfully trained various physical systems to perform machine learning computations in the same way as a ...

OXFORD, England--(BUSINESS WIRE)--Arctoris Ltd, a tech-enabled biopharma platform company, has appointed three globally recognized experts in Alzheimer’s disease, Machine Learning applied to closed ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Google’s Cloud Tensor Processing Units are ...

Neuromorphic engineering draws inspiration from biological neural systems, which operate robustly despite significant variability, noise, and heterogeneity ...

A major challenge to developing better neural prostheses is sensory encoding: transforming information captured from the environment by sensors into neural signals that can be interpreted by the ...

A new technical paper titled “Scaling Deep Learning Computation over the Inter-Core Connected Intelligence Processor” was published by researchers at UIUC and Microsoft Research. “As AI chips ...

The Texas Learning & Computation Center is seeking a Senior Researcher in our Job of the Week. The Senior Researcher consults with university research faculty on research design, parallelization and ...