For bionic underwater robots, it is a great challenge for depth control due to model uncertainty and strong nonlinearity. To this end, we propose a data-driven model predictive control (MPC) approach ...

Amid growing controversy over how tech giants harvest user data for AI, the Allen Institute for AI (AI2) has introduced a ...

As companies deploy agentic AI, CIOs and data leaders face a critical mandate: deliver governed, trusted data that AI systems can understand.

Severe weather events, such as heavy rainfall, are on the rise worldwide. Reliable assessments of these events can save lives ...

Experts from General Motors, Zoom and IBM discuss how their companies and customers consider AI model selection.

In Part 1, we explored the challenges of implementing machine learning and real-time analytics in semiconductor ...

Dynamic is one of the main bottlenecks in the industrial soft sensor application, due to the difficulties in representing and extracting dynamic data features. Meanwhile, an end-to-end deep network ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

Pegasystems PEGA is seeing accelerated momentum as its cloud segment increasingly drives subscription-based revenues. In the ...