SYSTEM AND METHOD OF FIRMWARE-LEVEL ARTIFICIAL INTELLIGENCE PRODUCTIVITY TOOL FOR ADJUSTING PERFORMANCE OF HARDWARE IN RESPONSE TO A RECEIVED USER QUERY INPUT

Smart overview of the Invention

A system is introduced that utilizes a firmware-level artificial intelligence (AI) productivity tool to adjust hardware performance based on user queries. This system includes a microphone for capturing user inputs, and an embedded controller that processes these inputs to match them with the most relevant firmware or hardware capabilities. The matching process relies on comparing the natural language of the user query with stored descriptions of hardware capabilities, allowing the system to execute the appropriate action directly at the firmware level without involving the operating system.

Field of the Disclosure

The disclosure pertains to an AI productivity tool embedded within information handling systems, aimed at enhancing user productivity and system performance. This tool operates independently of the operating system by identifying and adjusting firmware or hardware capabilities in response to user inputs. By executing at the firmware level, it provides a streamlined method for adjusting hardware settings without invoking the operating system.

Background

Information handling systems are crucial for processing, storing, and communicating data across various industries. These systems can be tailored for specific applications and may include diverse hardware and software components. The integration of AI productivity tools within these systems helps optimize their performance by executing user queries through machine learning models, enhancing both personal and business operations.

Implementation Details

The AI productivity tool functions by receiving user queries and matching them with known firmware or hardware capabilities using natural language processing models. The tool operates at both the firmware and operating system levels, with each level performing its own type of comparison to identify the best response to a user query. The firmware-level tool uses a lexical similarity search, which is less processor-intensive, to match queries with hardware capabilities, while the operating system level tool uses more complex semantic comparisons for software applications.

Functionality

Upon receiving a user query, the system can translate audio or image inputs into text and perform a lexical similarity search to find the best matching hardware capability. This search method, such as term frequency-inverse document frequency (TF-IDF), focuses on identifying key terms within the query to efficiently match them with stored hardware capabilities. This approach allows the system to respond to user requests, like optimizing battery power, directly at the firmware level, enhancing system efficiency without engaging higher-level operating system processes.