National Academies

DOE Should Develop AI-Based Foundation Models Fused with Traditional Computational Methods to Bring Paradigm Shift to Scientific Discovery

Foundation models are AI systems trained on vast amounts of data — often trillions of individual data points — and they are capable of learning new ways of modeling information and performing a range ...
ascopubs.org

Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy

Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor ...
blockchain

PyTorch for Deep Learning Professional Certificate Launches: Advanced AI Skills and Deployment Training

According to DeepLearning.AI (@DeepLearningAI), the new PyTorch for Deep Learning Professional Certificate, led by Laurence Moroney, provides in-depth, practical training on building, optimizing, and ...
datacenterfrontier.com

Supermicro Unveils Data Center Building Blocks to Accelerate AI Factory Deployment

Supermicro’s new Data Center Building Block Solutions (DCBBS) unify servers, liquid cooling, power, networking, and automation into modular, factory-tested bundles that speed AI data center buildouts.
InfoWorld

How to deploy machine learning models with AWS Lambda

AWS Lambda provides a simple, scalable, and cost-effective solution for deploying AI models that eliminates the need for expensive licensing and tools. In the rapidly evolving landscape of artificial ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study ...
Frontiers

Machine learning pipeline for microparticle size classification in self-mixing interferometric signals for flow cytometry

Self-mixing interferometry (SMI) is an emerging optical sensing technique for detecting and classifying microparticles in non-contact and label-free flowmetry applications. High precision and ...
Microsoft

Procter & Gamble cuts model deployment time up to 90% with Azure IoT Operations

“To me, this technology is like moving to the cloud years ago—a prerequisite to doing a lot of the things we’ve been able to do since. And it’s the same with our Azure IoT Operations platform. It will ...
datacenterfrontier.com

AI at Scale: Switch Hosts CoreWeave’s Landmark NVIDIA GB300 Deployment

Switch’s EVO AI Factories are setting a new benchmark for rack-scale infrastructure, enabling CoreWeave to launch the world’s first cloud deployment of NVIDIA’s GB300 NVL72 platform. With support from ...
IEEE

Deployment and Optimization Strategy of Machine Learning Model Based on Cloud Computing

Abstract: This article aims to explore the deployment strategy and optimization method of ML (Machine Learning) model based on cloud computing, so as to improve the performance of the model in the ...
IEEE

Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...