A new initiative designed to revolutionize seismic monitoring and forecasting using real time, advanced machine learning (ML) technologies is coming to the West Texas/New Mexico area. The U.S. Department of Energy (DOE) Technology Commercialization Fund awarded $1.8 million in funding to Lawrence Livermore National Laboratory (LLNL). The project is known as RECONNECT, or the Real-time […]
Search Results for: machine learning
National Lab’s Machine Learning Project to Advance Seismic Monitoring Across Energy Industries
June 30, 2025 by
Why Mathematics is Essential for Data Science and Machine Learning
November 12, 2024 by
In this feature article, Daniel D. Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, explores why mathematics is so integral to data science and machine learning, with a special focus on the areas most crucial for these disciplines, including the foundation needed to understand generative AI.
The AI Revolution: How Machine Learning has Changed the World in Two Years
October 30, 2024 by
In this contributed article, Ashley Marron, CEO of MindGenius, observes that as we approach the second anniversary of the launch of ChatGPT, it’s important to look at the impact AI has had on business technology, radically changing how companies and industries work, in that short time.
‘Physics-Informed Machine Learning’: New Technique at PNNL Corrects Remote Sensing Data
July 30, 2024 by
Turbulence, temperature changes, water vapor, carbon dioxide, ozone, methane, and other gases absorb, reflect, and scatter sunlight as it passes through the atmosphere, bounces off the Earth’s surface, and is collected ….
IOP Publishing Launches Series of Open Access Journals Dedicated to Machine Learning and AI for the Sciences
July 19, 2024 by
IOP Publishing (IOPP) launched a series of open access journals dedicated to the application and development of machine learning (ML) and artificial intelligence (AI) for the sciences. The new multidisciplinary Machine Learning series will collectively cover applications of ML and AI across the physical sciences, engineering, biomedicine and health, and environmental and earth science.
Deploying Machine Learning Models at Scale: Strategies for Efficient Production
May 17, 2024 by
In this contributed article, freelance writer Ainsley Lawrence briefly explores deploying machine learning models, showing you how to manage multiple models, establish robust monitoring protocols, and efficiently prepare to scale.
The Data Disconnect: A Key Challenge for Machine Learning Deployment
March 25, 2024 by
This article is excerpted from the book, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment,” by Eric Siegel, Ph.D., with permission from the publisher, MIT Press. It is a product of the author’s work while he held a one-year position as the Bodily Bicentennial Professor in Analytics at the UVA Darden School of Business.
Book Review: A Hands-on Introduction to Machine Learning
January 22, 2024 by
I was pleased to receive a review copy of this new title from Cambridge University Press, “A Hands-on Introduction to Machine Learning.” The hardcover book is very attractive, well-produced and solid! It will weigh down your backpack for sure. As a university instructor myself, I immediately appreciated author and University of Washington professor Chirag Shah’s pedagogical approach.
Nuvoton Unveils Endpoint AI Platform for Machine Learning
January 5, 2024 by
Hsinchu, Taiwan, January 5, 2024 – Nuvoton has announced the Endpoint AI Platform designed to accelerate the development of fully-featured microcontroller (MCU) AI products. These solutions are enabled by Nuvoton’s new MCU and MPU silicon, including the NuMicro M55M1 equipped with Ethos U55 NPU, NuMicro MA35D1, and NuMicro M467 series. These MCUs are a valuable […]
2023 ML Pulse Report: The Latest Trends and Challenges in Machine Learning
November 9, 2023 by
Our friends over at Sama recently published a comprehensive report on the potential and challenges of AI as reported by Machine Learning professionals.
