The project for which Hulsebos received the grant is called DataLibra, which runs from 2024 to 2029. Over those five years, ...

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence ...

Abstract: This article introduces a novel approach that combines a multimodel technique with model-free adaptive control (MFAC) to address the limitations of the full-form dynamic linearization (FFDL) ...

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 ...

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 ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Artificial intelligence systems ...

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...

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 ...