The global energy grid is undergoing a profound transformation. Moving from traditional centralized control systems to more dynamic, distributed structures, thi ...

Climate volatility and rising energy demand have resulted in unprecedented challenges throughout the world. Unfortunat ...

This distributed ledger-based system not only offers financial benefits ... to Overcome the Need of Labeled Data for Agricultural Machine Learning Tasks?, Plant Phenomics (2023).

By integrating LoRa technology with distributed machine learning, the network connectivity of green intelligent transportation systems can be optimized. Applying LoRa technology to the monitoring ...

Learn More Artificial intelligence (AI) and machine learning (ML ... s Transform 2022 conference. Distributed computing allows components of software systems to be shared among multiple ...

Pratik Mayur Parekh is an accomplished engineering leader specializing in machine learning and distributed systems, based in San Francisco, California. With a strong educational foundation ...

A machine-learning algorithm ... large data sets efficiently." The distributed algorithm for modern and heterogeneous high-performance computer systems can be useful on hardware as small as ...

This open-source contribution bridges the gap between distributed S3-compatible object storage systems and machine learning compute platforms, eliminating the dependency on a dedicated parallel ...

Intelligent organizations prioritize investments in machine learning and real-time data ... slower-moving peers still relying on legacy systems and outdated processes. 5G and other recent ...

The focus of this funding opportunity is on basic research and development at the intersection of uncertainty quantification (UQ) and scientific machine learning (SciML) applied to the modeling and ...