Samsung electronics co., ltd. (20240187687). SMART HOME AUTOMATION USING MULTI-MODAL CONTEXTUAL INFORMATION simplified abstract

SMART HOME AUTOMATION USING MULTI-MODAL CONTEXTUAL INFORMATION

Organization Name

samsung electronics co., ltd.

Inventor(s)

Andres Leonardo de Jesus Ortega Pena of San Jose CA (US)

Ashwin Chandra of Santa Clara CA (US)

Suk-Un Yoon of Suwon-si (KR)

David Ho Suk Chung of Rancho Palos Verdes CA (US)

SMART HOME AUTOMATION USING MULTI-MODAL CONTEXTUAL INFORMATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240187687 titled 'SMART HOME AUTOMATION USING MULTI-MODAL CONTEXTUAL INFORMATION

Simplified Explanation

The abstract describes a method involving a first electronic device with a multi-task dynamic machine learning model, dynamically controlling sub-models, generating contextual information, and sharing it with a second electronic device.

• The method involves obtaining inputs at a first electronic device with a multi-task dynamic machine learning model.
• The machine learning model includes multiple sub-models for different functions.
• The sub-models are dynamically controlled based on available inputs or outputs to be generated.
• Contextual information is generated and associated with at least one user of the first electronic device.
• The contextual information can be shared with a second electronic device in a specified environment.

Potential Applications of this Technology

This technology could be applied in personalized recommendation systems, adaptive user interfaces, and context-aware computing.

Problems Solved by this Technology

This technology helps in optimizing machine learning processes, enhancing user experience, and improving data sharing between devices.

Benefits of this Technology

The benefits include improved efficiency in processing inputs, personalized user experiences, and enhanced collaboration between electronic devices.

Potential Commercial Applications of this Technology

Potential commercial applications include smart home systems, personalized digital assistants, and collaborative work environments.

Possible Prior Art

One possible prior art could be the use of dynamic machine learning models in personalized recommendation systems.

How does this method handle privacy concerns related to sharing contextual information between devices?

The method does not specify how privacy concerns are addressed when sharing contextual information between devices. Additional measures may be needed to ensure data security and user privacy.

What are the limitations of dynamically controlling sub-models based on available inputs or outputs?

The abstract does not mention any limitations of dynamically controlling sub-models based on available inputs or outputs. Further research may be needed to understand potential drawbacks or challenges in this approach.

Original Abstract Submitted

a method includes obtaining one or more inputs at a first electronic device. the first electronic device includes a multi-task dynamic machine learning model that includes multiple sub-models configured to perform different machine learning functions. the method also includes dynamically controlling the sub-models used to process the one or more inputs based on at least one of: (i) the one or more inputs that are available for use or (ii) one or more outputs to be generated. the method further includes generating a set of contextual information associated with the first electronic device. at least a portion of the set of contextual information is associated with at least one user of the first electronic device. the method may additionally include sharing the set of contextual information with at least a second electronic device in a specified environment.