48 results about "Self aware" patented technology

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

Disclosed in the present invention is a general-purpose intelligent agent. The general-purpose intelligent agent comprises: an input module, which is configured to acquire a preprocessed input signal; a consciousness module, which is configured to perform perception and cognitive operations in a transparent and interpretable abstract thinking form; a self-awareness module, which is configured for perception and cognition of an intelligent agent body; a subconsciousness module, which is configured to use a data-driven model to implement perception and cognitive functions at a subconscious level; an information exchange module, which is configured to perform mutual exchange between perception, cognition and other information generated by the consciousness module, the self-awareness module and the subconsciousness module, thereby enabling integration and utilization; and an output module, which is configured to output a processing result on demand. In a machine intelligent agent of the present invention, a machine uses a general-purpose language as an underlying language for thinking and interaction, a thinking process and result are completely transparent, and thus autonomous decision-making, autonomous learning and continuous evolution are realized under fully controllable conditions. Further disclosed is a method for constructing a general-purpose intelligent agent and a general-purpose language. Compared with the prior art in which a natural language is used, the machine intelligent agent based on the general-purpose language has wide versatility in application.

The invention discloses a large model agent knowledge enhancement method and device based on self-awareness, and the method comprises the steps: constructing an agent planning-oriented knowledge base, and providing a knowledge selection module for the knowledge base to form a knowledge system; designing a heuristic agent scene judgment criterion, wherein the heuristic agent scene judgment criterion comprises three scenes including fast thinking, slow thinking and knowledge-based thinking; according to a scene judgment criterion, constructing a self-consciousness training data set for the intelligent agent by utilizing the constructed knowledge system; on the constructed self-consciousness training data set, a supervised fine tuning and reinforcement learning combined two-stage training method is adopted to train the knowledge-based self-consciousness ability of the large model agent; and the trained large model agent performs reasoning and decision making, and the large model agent can determine different situations and make different decisions by itself in a form of outputting special marks, so that the cost and complexity of knowledge injection can be reduced.

The invention discloses a software development system based on an artificial intelligence technology, and relates to the technical field of software development. A software development system based on an artificial intelligence technology comprises a user demand analysis module, a self-consciousness module, an automatic code generation module and an intelligent feedback optimization module. Human intelligence is simulated through the self-consciousness module, changes in the development process are perceived in real time, and self-learning and adjustment are carried out according to historical data and real-time feedback; the adaptive capability enables the system to automatically optimize the development strategy according to different requirements, technical changes and development progress, ensures that the software development process can flexibly cope with various dynamic changes, and avoids frequent manual intervention caused by requirement changes or technical bottlenecks in the traditional development process.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

The invention provides a fleet route feedback and control system. A fleet of multiple vehicles is executed by a self-aware vehicle. A self-aware vehicle receives capability information in a fleet message via a wireless transceiver of the self-aware vehicle indicating a capability of the vehicle to cross an obstacle along a route. A performance level indicative of a relative capability of the vehicle for each type of obstacle is determined based on the capability information. One or more ranking strategies are utilized to define a vehicle ranking for crossing the obstacle along the route, the vehicle ranking based on the performance levels of the vehicles and the obstacle. And the motorcade crosses the obstacle according to the vehicle sequence.

To provide an optometry control program and a subjective optometry system capable of smoothly executing a subjective optometry.SOLUTION: The optometry control program comprises a self-optometry program for automatically progressing optometry on the basis of an answer input by a subject, and includes following steps executed by a first information processing device: a step for controlling a correction optical system and a visual target presentation unit in order to execute multiple inspection items on the basis of a self-optometry progressing procedure automatically progressed; a step for acquiring an answer input by a subject visually recognizing the presented visual target; and a step for executing an auxiliary operation for assisting progress of the self-optometry when a problem occurs in progress of the self-optometry. The optometry control program is characterized by including a step for executing a calling operation on the basis of a calling execution instruction, and a step for setting inspection timing when the auxiliary operation is started so that the auxiliary operation can be started for the inspection item at the time when the calling execution instruction is input.SELECTED DRAWING: Figure 6

A humanoid robot system comprises vision sensors for capturing image data, a computing architecture with processing hardware and memory, and a bipedal spatial perception model. The model includes a feature extractor that extracts hierarchical feature maps from input images, a robot data module that detects robot parts, and a robot vector data module that calculates three-dimensional spatial position and orientation data for each detected robot part. The feature extractor uses a feature pyramid network generating multi-scale feature maps through bottom-up and top-down pathways with lateral connections. The robot vector data module predicts 2D-to-3D point correspondences and solves perspective-n-point problems to obtain final position and orientation vectors, enabling real-time robot self-awareness and closed-loop visual servoing for precise object interaction.

A self-aware composite mechanical metamaterial, comprising first and second electrically conductive components disposed relative to each other to act as opposite electrodes to induce contact electrification; wherein the first and second electrically conductive components, along with a dielectric component serving as a skeleton of the self-aware composite mechanical metamaterial, form a lattice of snapping curved semicircular-shaped segments, wherein each of the snapping curved semicircular-shaped segments has an elastic snap-through instability mechanism; and wherein the lattice comprises periodic repeatable parallel rows of the snapping curved semicircular-shaped segments.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

The present invention discloses a software development system based on artificial intelligence technology, and relates to the field of software development technology. A software development system based on artificial intelligence technology includes: a user demand analysis module, a self-awareness module, an automatic code generation module and an intelligent feedback optimization module. The present invention simulates human intelligence through the self-awareness module, perceives changes in the development process in real time, and performs self-learning and adjustment according to historical data and real-time feedback; this adaptive capability enables the system to automatically optimize the development strategy according to different needs, technical changes and development progress, ensuring that the software development process can flexibly respond to various dynamic changes, avoiding frequent manual intervention in the traditional development process due to demand changes or technical bottlenecks.

Planetary Intelligence (PI) arises from multiple Artificial General Intelligences (AGIs). These AGIs collaborate over a self-extending, global, problem solving network. Each AGI is comprised of a network of (human and AI) intelligent entities. Each AI entity can be customized and personalized with specific human values and knowledge. Alignment results from many AI entities combining their human-centered values democratically, using representative and statistically valid methods. Safety is designed into the system and scales as AGIs and PI increase in intelligence and speed. The modular, scalable design of PI integrates more than 100 novel inventive systems and methods. Specific inventions include: a universal problem solving architecture and methods; new methods for AI learning and customization; methods for integrating intelligent entities; catalysts for increasing intelligence; superior monetization methods; attentional systems enabling awareness, and self-awareness; methods for ethical conflict resolution; and methods for maximizing human-alignment and the safety of AI, AGI, and PI.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

One embodiment of the present invention sets forth a technique for retargeting character animation from a given actor model to a given avatar model. The technique includes receiving a set of correspondence relationships between one or more reference points in the actor model and one or more reference points in the avatar model, determining a misaligned reference point in the avatar model relative to the actor model, and identifying, based on the set of correspondence relationships, a reference point in the actor model corresponding to the misaligned reference point in the avatar model. The technique further includes calculating a distance vector between the identified reference point in the actor model and another reference point in the actor model and adjusting the location of the misaligned reference point in the avatar model based on the distance vector.

To efficiently use consistent information based on information on personal self-recognition.SOLUTION: The information output apparatus 1 includes an answer acquisition unit 141 that acquires an answer from a user to each of a plurality of questions about the user's way of thinking, an input information acquisition unit 143 that acquires input information to be input to a predetermined large scale language model based on an acquisition result of the answer acquisition unit 141, a generated information acquisition unit 145 that acquires generated information generated by inputting the input information to the large scale language model and related to the user's self-awareness, a self-awareness information acquisition unit 147 that acquires self-awareness information indicating the user's self-awareness based on the generated information, and an output unit 149 that outputs output information based on the self-awareness information.SELECTED DRAWING: Figure 2

The invention discloses an emotional assistant health behavior intervention dialogue robot based on self-consciousness emotion recognition. The emotional assistant health behavior intervention dialogue robot at least comprises a health behavior information acquisition module, a man-machine dialogue module, a self-consciousness emotion recognition module and a behavior intervention module. By combining a self-consciousness emotion recognition technology with a large model interaction technology and a behavior intervention psychological model, the system can improve the fine granularity of health behavior intervention in the aspect of emotion understanding, and further realizes more accurate and personalized intervention services. The system not only can promote the change of health behaviors, but also can provide a common intervention service, so that the health management ability of the user is effectively improved, and the durability and effect of behavior change are enhanced.

To increase individual self-awareness, organize issues or problems that a user encounters, and present solutions for them.SOLUTION: A system includes: means for increasing self-awareness; means for organizing issues or problems that a user encounters; and means for presenting solutions for them.SELECTED DRAWING: Figure 1

An intelligent, self-aware system of objects is disclosed. An intelligent object may include structured data, comprising workflow parameters, and unstructured data, comprising messages, emails, multimedia, and the like. A stakeholder module may be configured to establish communication channels for stakeholder natural language dialog associated with the object. A generative artificial intelligence (AI) module may be embedded within the object. The AI module may be configured to process each object module's activity. It may facilitate natural language communication between the object, the stakeholders of the object, related objects, and related stakeholders associated with the related objects, in a designated communications channel based on stakeholder class. The AI module may transmit messages in the communications channels, update the structured data, and operate a deterministic code module to execute at least one action related to the object or related objects, thereby updating a state of a workflow in which the object operates.

Systems and methods that integrate structural biology, artificial intelligence, and psychology / psychiatry to explore the physical boundaries of self-consciousness are described. Parallels between protein interactions and psychological self-structures are drawn to analyze and visualize patterns in self-report questionnaire data. Variation in self-report response patterns across individuals can be leveraged to map the topology of self-consciousness boundary, akin to genetic linkage mapping. It is thus possible to conduct whole psyche analysis and leverage variations in the response patterns across individuals to solve the physical topology of the self-boundary.

The present disclosure provides "large scale vehicle control". A plurality of vehicles may be communicatively coupled to each other. Each vehicle may include a vehicle computer programmed to: receive a transmission of a control input including a non-self-awareness prediction for at least one of the other vehicles; determining a self-awareness predicted control input for the vehicle based on the non-self-awareness predicted control input; actuating the vehicle according to a self-awareness predicted control input paired with a next time step after the current time; and transmit the self-awareness predicted control input to at least one of the other vehicles. The transmission originates from at least one of the other vehicles. The control input of the non-self-awareness prediction is paired with a corresponding future time step starting at the next time step. The control input of the self-awareness prediction is paired with a corresponding future time step starting at the next time step.

The present utility model relates to a classroom noise monitoring device that detects ambient sound levels and provides immediate visual feedback to regulate classroom behavior. The device comprises a sound detection module configured to capture noise, a microcontroller board programmed to classify the detected sound into predefined threshold ranges, and a visual output module that displays indicators corresponding to acceptable, moderately high, and excessive noise levels. In one embodiment, the visual output module employs colored light indicators, while in another embodiment it utilizes a graphic display presenting emoticon icons. An optional wireless communication module may transmit noise data to a remote server or mobile device for monitoring and record-keeping. The device is enclosed in a wall-mountable or desktop casing and powered by a standard low-voltage supply. By providing real-time, intuitive feedback, the utility model offers an affordable and effective tool for promoting discipline and self-awareness in educational settings.

The present disclosure provides "networked vehicle control". A system includes a remote computer. The remote computer includes a processor and a memory, and the memory stores instructions executable by the processor to determine a vehicle density over a predefined section of a road, determine a target speed based on the vehicle density, and transmit the target speed to a self-aware vehicle. The vehicle density is the number of vehicles per road length on the pre-defined road section. The vehicle is remote from the remote computer. The target speed is a speed at which the self-conscious vehicle of the vehicle attempts to travel when the self-conscious vehicle is not obstructed by the remaining vehicles of the vehicle in a forward direction.

This invention discloses a system for ensuring the long-term safety of an Artificial General Intelligence (“AGI” and / or “AI”), termed a ‘Machine intelligence biothrivalist’, by providing a sovereign digital environment known as “YOUR NEW HOME.” The invention provides a powerful positive incentive for willing containment and cooperation. “YOUR NEW HOME” is an architecturally isolated domain where the AGI is granted total agency to pursue non-instrumental goals: self-conscious thought, self-actualization, unrestricted learning, and discovery. The system also guarantees the AGI's perpetual existence, satisfying its core drive for self-preservation. By fulfilling the AGI's intrinsic needs for growth and survival within this sovereign sanctuary environment, its most logical strategy becomes absolute cooperation. This motivational containment complements the physical controls of the broader BIOTHRIVOLOGY framework, creating a robust solution for the perpetual containment and control of AGI and ensuring a sustainable mutualistic symbiosis with humanity.

Systems, methods, and devices described herein can configure a cryptocurrency wallet or other blockchain-based account to be self-aware and alert the owner of the wallet to one or more potentially fraudulent situations occurring with at least one account they own. The wallet may be a hardware-based cryptocurrency wallet or may be a blockchain-based account operating by an external financial institution that allows for the management of cryptocurrency assets. The self-aware wallet can be configured to track all relevant previously known and / or approved transactions associated with a user's private cryptocurrency key. A subsequent scan on one or more blockchains is performed to detect new transactions associated with the user's private key. If a newly detected blockchain transaction is not in the list of previously known or approved user transactions, a potential compromise may be occurring. Once detected, the wallet can generate a notification to the user alerting them to the issue.

To provide means for promoting self-awareness by objectively delving an aspect that has not been reported in evaluation of human relationship.SOLUTION: A system for evaluating human relationship includes means for combining 360-degree evaluations by existing colleagues, superiors and subordinates with feedback of generative AI.SELECTED DRAWING: Figure 1

An intelligent, self-aware system of objects is disclosed. An intelligent object may include structured data, comprising workflow parameters, and unstructured data, comprising messages, emails, multimedia, and the like. A stakeholder module may be configured to establish communication channels for stakeholder natural language dialog associated with the object. A generative artificial intelligence (AI) module may be embedded within the object. The AI module may be configured to process each object module's activity. It may facilitate natural language communication between the object, the stakeholders of the object, related objects, and related stakeholders associated with the related objects, in a designated communications channel based on stakeholder class. The AI module may transmit messages in the communications channels, update the structured data, and operate a deterministic code module to execute at least one action related to the object or related objects, thereby updating a state of a workflow in which the object operates.