anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

An expert Q&A on the legal, ethical, and practical considerations and emerging issues regarding judicial use of AI, including ...

In 2026, contextual memory will no longer be a novel technique; it will become table stakes for many operational agentic AI ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Abstract: Automated model generation (AMG) algorithms have become popular techniques for the systematic development of artificial neural network (ANN) models for microwave components. However, ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

This isn't really an issue (discussions are disabled) and it isn't exactly related to the Device model group, but since you, the Smart Data Model maintainers, have a lot of experience with JSON-LD and ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

R Symons Electric Vehicles, a U.K.-based electric vehicle dealer, drove two nearly identical Tesla Model 3s 200 miles for a range and efficiency test. Despite one car having 225,000 miles, it was just ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...