Benefits of artificial intelligence: Risks, trends and more

Artificial intelligence is transforming how we live and work, from personalized recommendations to health care innovation.
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
USA Today

Building Large-Scale Machine Learning/AI Systems with Niloy Gupta

Machine Learning (ML) and Artificial Intelligence (AI) have become essential technologies across industries, automating tasks at a speed and scale far beyond human capabilities. However, building ...
EurekAlert!

Generative AI may cut costs in machine-learning systems, but it increases risks of cyberattacks and data leaks, computer scientist says

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press journal ...
InfoQ

Beyond Notebook: Building Observable Machine Learning Systems

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...
techtimes

Param Popat Leads the Way in Transforming Machine Learning Systems

The ability to shape machine learning systems (MLS) that seamlessly integrate into everyday life is both a science and an art. Param Popat, a machine learning engineer at Apple, is a master integrator ...
Nature

Active Learning Strategies in Machine Learning Systems

Active learning encompasses a suite of iterative sampling methodologies that seek to maximise predictive performance while minimising the burden of manual annotation. By identifying and labelling only ...
Aerospace and Mechanical Insider on MSN

AI and machine learning transform materials testing

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...
Nature

Privileged Information Learning in Machine Learning Systems

Privileged Information Learning introduces auxiliary data available only at training time to enhance model performance without altering the testing procedure. Drawing inspiration from human teaching, ...
National Academies of Sciences%2c Engineering%2c and Medicine

Using Machine Learning in Safety-Critical Applications: Setting a Research Agenda

Machine learning components are enabling advances in self-driving cars, the power grid, and robotic medicine, but what are the implications for safety? Decades of research and practice in safety ...
techtimes

AI Cyberattacks Rising: How Hackers Use Machine Learning to Launch Smarter Attacks

AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented speed. Through machine learning hacking, adversaries can ...