Juan M. Lavista Ferres, the chief data scientist at Microsoft's AI for Good Lab, discusses how artificial intelligence might ...

Reuters, the news and media division of Thomson Reuters, is the world’s largest multimedia news provider, reaching billions ...

In smart grid management, ML enables dynamic control of distributed energy sources, managing real-time energy flows and ...

Insights from data and machine learning algorithms can be invaluable, but be warned — mistakes can be irreversible. These recent high-profile AI blunders illustrate the damage done when things ...

Data Science Agent uses Anthropic PBC’s Claude large language model to dissect machine learning projects into logical steps and deliver executable pipeline components that can be run inside ...

Hammerspace isn’t alone in trying to unlock the performance potential of distributed data for AI and HPC environments. The category of data orchestration and global namespace solutions has grown ...

Anaconda is a popular open-source distribution of Python and R programming languages for data science, machine learning, and large-scale data processing. It aims to simplify package management and ...

For those needing robust ELT, data science, and machine learning features within a data lake/data warehouse framework, Databricks is the winner. Azure ML wins for those just wanting to add ML to ...

The learning curve for implementing machine learning solutions is generally steep, so you’ll need a solid understanding of statistics, data science, and algorithm development.

Keywords: spiking neural networks, neuromorphic computing, neuromorphic hardware, artificial neural networks, machine learning. Citation: Deng L, Tang H and Roy K (2024) Editorial: Understanding and ...