The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...
TMCnet

Artificial Intelligence (AI) Tools Market Driven by Rapid Enterprise Automation, Advanced Analytics Adoption, and Expanding Digital Transformation Initiatives: - Market ...

Tools Market is primarily driven by rapid digital transformation across industries, increasing adoption of generative AI, and the growing need for intelligent automation to enhance operational ...

You Must Address These 4 Concerns To Deploy Predictive AI

Predictive AI routinely fails to deploy, so data scientists are spearheading a movement to focus on its business value. But ...
Machine Design

Physical AI in Motion: How Machine Learning Drives Next-Gen Industrial Automation

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control.
IEEE

An Exploratory Study of Security Vulnerabilities in Machine Learning Deployment Projects

Abstract: Machine learning (ML) deployment projects are used by practitioners to automatically deploy ML models. While ML deployment projects aid practitioners, security vulnerabilities in these ...
IEEE

Updating Machine Learning Models in Real-World Applications: Finding Best Deployment Settings

Abstract: Effective deployment and updating of machine learning models are crucial for maintaining operational efficiency in industrial environments. Model performance often degrades over time due to ...
WDAF-TV

AgiBot Achieves First Real-World Deployment of Reinforcement Learning in Industrial Robotics

SHANGHAI, Nov. 2, 2025 /PRNewswire/ -- AgiBot, a robotics company specializing in embodied intelligence, announced a key milestone with the successful deployment of its Real-World Reinforcement ...