Nvidia Corporation

Marc E Davis

Ryan Kelsey Albright

Tahir Cader

Benjamin Goska

Michael Thompson

William Andrew Mecham

Aaron Richard Carkin

William Ryan Weese

Jordan Levy

Ben Goska

Mike Gemelke

Siddardha Naraharisetti

Ankita Garg

A method includes determining, using a processing device, a set of observations from coolant data, the coolant data being received from one or more sensors in an environment associated with a coolant. The method further includes determining, using a machine learning model and the set of observations, a contamination level of the coolant. The method also includes initiating an operation, using the processing device, responsive to determining the coolant contamination level.

Fluid inspection using machine learning

Systems and methods for cooling a datacenter are disclosed. In at least one embodiment, a server tray or box includes a surface with a flow-through fixture or manifold that extends on both sides of the surface, that includes an inward coupling, an outward coupling, a flow controller, and a state sensor, the state sensor to monitor a flow-through fixture or manifold, where a flow controller of a flow-through fixture or manifold can change a flow of a coolant through a flow-through fixture or manifold and can selectively trap a portion of a coolant within a flow-through fixture or manifold.

Integrated server flow-through fixture with state sensor for datacenter cooling systems

Haptic effects have long been provided to enhance content, such as by providing vibrations, rumbles, etc. in a remote controller or other device being used by a user while watching or listening to the content. To date, haptic effects have either been provided by programming controls for the haptic effects within the content itself, or by providing an interface to audio that simply maps certain haptic effects with certain audio frequencies. The present disclosure provides a haptic control interface that intelligently induces haptic effects for content, in particular by using machine learning to detect specific features in content and then induce certain haptic effects for those features.

Haptic control interface for detecting content features using machine learning to induce haptic effects

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Hillsboro, OR, United States of America

Marc E Davis