The landscape for video training data and multimodal foundation models in 2026 is defined by a shift from quantity to highly ...

Effective data modeling enables value creation, efficiency gains, risk reduction, and strategic alignment in an environment of uncertainty and disruption. At Data Summit 2026, Pascal ...

Why modern observability systems fail during incidents, and how new architectures fix them.

Stanford's 2026 AI Index: frontier models fail one in three attempts, lab transparency is declining, and benchmarks are ...

Cardinality estimation (CardEst) plays a crucial role in the optimization of query execution plans. Over the past decade, a number of methods have been proposed to address this issue, but limitations ...

We study two classes of summary-based cardinality estima tors that use statistics about input relations and joins of a small number of input relations: (i) optimistic estimators, which were defined in ...

Abstract: In recent years, deep learning-based approaches have been increasingly adopted for cardinality estimation to enhance the accuracy of query optimization. However, there are still some ...

This view of NASA’s Ingenuity Mars Helicopter was generated using data collected by the Mastcam-Z instrument aboard the agency’s Perseverance Mars rover on Aug. 2, 2023, the 871st Martian day, or sol, ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.