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8 results about "Utility system" patented technology
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In video game AI, a utility system, or utility AI, is a simple but effective way to model behaviors for non-player characters, by assigning utilities to each action based on some heuristics, and by choosing to perform an action with a high utility. Either the action with the highest utility is chosen, or an action is randomly chosen based on some given probability distribution. In The Sims 3, a modified version of the Boltzmann distribution is used to choose an action for a Sim, using a temperature that is low when the Sim is happy, and high when the Sim is doing badly to make it more likely that an action with a low utility is chosen.
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Use of irrelevant filters to facilitate efficient RUL analysis of utility system assets
To provide a method and system for improving the reliability of a utility system asset.SOLUTION: The method includes receiving a time series signal collected from a sensor in a utility system asset, using an inference model to generate an estimated value of the time series signal, performing a pairwise difference operation between the actual value and the estimated value of the time series signal to generate a residual, and performing a sequential probability ratio test (SPRT) on the residuals to generate an SPRT alarm, applying an irrelevance filter that removes SPRT alarm for a signal that does not correlate with previous failures of similar utility system assets to the SPRT alarm to generate a filtered SPRT alarm, using a logistic regression model to calculate an RUL-based risk indicator for the utility system asset on the basis of the filtered SPRT alarm, and generating a notification indicating that the utility system asset needs to be replaced when the risk indicator exceeds a threshold value.SELECTED DRAWING: Figure 2
Owner:ORACLE INT CORP
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Utility system for automated code generation and execution
Methods, systems, and computer programs are presented for implementing a tool that generates and executes the code in a controlled environment to satisfy user requests entered as text prompts. One method includes receiving a user prompt with a user request received in a user interface (UI), generating a first Large Language Model (LLM) prompt to create a plan, and receiving the plan from an LLM, the plan comprising text describing a sequence of operations. The method further includes generating a second LLM prompt, to create code, specifying which code instructions are permitted in the created code. Further, the method receives the code from the LLM that received the second LLM prompt, and executes the code in a controlled environment. Further, the results generated by executing the code are presented in the UI.
Owner:DEPENDABLE AI INC
Artificial-intelligence modeling utility system
Owner:MICROSOFT TECHNOLOGY LICENSING LLC