Intelligent Business Assistants
Skills4Industry heterogeneous data framework uses a rules-based Syntactic Map to provide artificial intelligence a deep understanding of labels and patterns beyond heuristic algorithmic inference-based approaches. Our systemization framework ensures that artificial intelligence develops an understanding of concepts of human abilities and applies the know-how in collaborating with humans across all spectrums of society. Feeding artificial intelligence machine learning with rules-based data enables machine understanding of how human ability concepts based on relational hierarchies in business and social structures can be used to close the gap between abilities and potentials. AI transition to general intelligence lies in its understanding of human concepts, systemizing the work done by humans and the competencies to perform all tasks offer an approach to achieving more knowledge.
Skills4Industry Digital Assistants uses Natural Language Processing AI capabilities based on data containing over 3.6 million tasks concepts, rolled into over 200,000 functional groups and scaled through ten work levels. With Skills4Industry data and AI, businesses with no data and poorly formatted big data can plug our system into their workflow to capture continuous work tasks and connected things data for various applications. With which predictive models can answer queries and take action on behalf of employees, with daily improvements based on continuous data and data learned from users.
Skills4Industry Digital Assistant help users proactively make decisions using the work concepts to learn from the continuous data captured from interactions with people, machines and devices.
These automated actions may, for example, include finding, training, and retaining the right talent. Providing engineers with visual cues on assembling and disassembling equipment or products in a 3D space using AR, and viewing equipment schematics in the field while being connected with specialists via a face-time call. Skills4Industry improves service times by a factor of nine while extending apprenticeships to high school students, the level 1 focus exit credentials increase productivity by a factor of six using 3D and AR digital training assistants.
Courtroom application of Skills4Industry include deciding disability, and compensation based on knowledge of all tasks an employee's competencies can be applied.
Skills4Industry distributed on-device machine learning ensure user requests are secure and private, while AI improved assistance is as a result of continuous learning from users' cross-functional collaboration with team members and others. The resulting enriched content captured by the device from collaborative work establish personal user preferences for improving task performance.
Skills4Industry digital assistant general features offer a link between continuously improved abilities and work activities across industry, sectors, trades, and domain (ISTD) through ten levels for humans and four stages for machines using artificial intelligence features, based on classification and regression problem-sets.
With Skills4Industry, intelligence is not centralized but distributed with higher ethical standards for personal data handling, more flexibility and better operational transparency with the opportunity to revisit working from home or other remote locations. Connecting the physical processes with services and customers through the Internet with distributed embedded intelligence offer flexibility and autonomy, while the enhanced cross-functional collaboration provides the needed resources to respond to market restrictions and demand.
Skills4Industry’s connected intelligence services are decoupled from cloud servers using on-device machine learning approach that ensures all AI functions take place on user’s devices. This deployment model provides privacy, security, and ownership of personal data, as well as the ability to explain the inner thinking of the artificial intelligence algorithm.