Co-founder / CTO

To succeed today, individuals must be able to use technology efficiently, be proficient in the application of work skills, manage relationships effectively and apply knowledge of the cultural domain in which their organizations operate in an integrative manner.

Our vision at Skills4Industry is to use computing and artificial intelligence to continuously improve human and machine absorptive capacity to develop the competencies to make decisions with data and technology. Thereby, ensuring every individual can tell connected devices what to do and intelligently combine human and machine competencies to achieve anticipated productivity goals.

In anticipation of increasing materials capabilities in storing, converting information to usable data, getting data to those who need it for decision making, and the realization that our current system of education is not equipped to provide people the needed integrative competencies. I embarked on massive data collection, curating, cleansing and fitting for artificial intelligence algorithms to deliver learning from the Internet of Things (IoT) to address individuals specific needs at home, work, school, play and sports grounds.

Current artificial intelligence is weak and employs some human level intelligence, but are based on rules, patterns, and heuristics without a deep understanding of the human meaning of concepts. These services run on cloud servers where the artificial intelligence capabilities are located, while the connected devices used by individuals only serve as input and output devices.

Superior artificial intelligence in strength, often called General Intelligence is beyond the current state of the art, although its human-level application will not be around soon, we have prepared our infrastructure for its eventual availability.

With these considerations, we implemented a rules-based intelligence system with a set of performance benchmarks serving as boundaries to work tasks within a job role and functional group. They are designed to feed machine learning training data, while a chunk of the data is used for testing predictive models. Building the occupational and competency discrete rules-based data through painstaking human effort eliminate bias, provides artificial intelligence the ability to learn from heterogeneous competency (work, academic, relational and domain context) data, ability to explain learning information to users and allows faster humanistic concepts learning accuracy from users and continuous IoT data by our AI / ML. General artificial intelligence capabilities will eventually be achieved by feeding the machine learning with more humanistic concepts resulting in improved accuracy and intelligence.

Artificial intelligence now runs on devices and we use a distributed learning framework to ensure all learning data and capabilities reside on user devices. Only a scoring update to the cloud server is required at a time chosen by users, this will result in an environment in which personal data is secured by users on their devices, with low internet bandwidth and electricity consumption.

Success in working with leading laboratories in North America has resulted in our many firsts and with you, this work will now include Asian institutions and practical test beds in the most vibrantly ambitious young populations of the world. At the heart of these institutional partnerships, is Skills4Industry’s goal of becoming the global reference architecture that facilitates the interoperability of IoT connected devices and human competencies. The envisaged standardized framework for the global economy will provide a climbing frame for all individuals into the world of work, no matter their birth circumstances. Currently, our AI predictive models reveal a dynamic generative physical and non-physical (thinking) work activities across workflow tasks in a business value chain, from connected nodes of transactional and relational activities. These nodes may establish future protocols for the interoperability of connected IoT and human competency standards, important in determining the actual learning for a given pathway, improving pedagogy, matching people to jobs and reporting by workforce organizations. Standardization has been a critical requirement for the development of new industries in the past and we want to lead this change with AI.

Skills4Industry will lead the delivery of human and machine learning by incorporating 3D, augmented reality, virtual reality, smart glasses or headsets, and videos to the user interface for the delivery of learning objects beyond Disney proportion.

What is Skills4Industry?

Skills4Industry is a rules-based heterogeneous competency data containing over 3.6 million work tasks, each describing a set of work tools, relational, academic knowledge and contextual cultural domain for the performance of tasks within a job role. As a map linking job roles to business value chains, Skills4Industry represent business relational nodes containing interesting training data for artificial intelligence predictive models. Skills4Industry predictive models measure abilities and engagement of individuals and provide incrementally appropriate integrative competencies important to the performance of complex tasks. Skills4Industry offer two products with global applications, they are: (1) Pathways Dashboards; and (2) Connected Digital Business Assistants.

  1. Pathways Dashboards: Skills4Industry pathways solutions represent a climbing frame for navigating the world of work, through the determination of individuals' abilities for employability and recommendation of the course taking required to link abilities to potentials. Skills4Industry rules-based competency data is fully mapped to core academic curricula and relational standards from 5th grade to Ph.D. and continuously updated by IoT and personal learning data. Thus ensuring all exit credentials are embedded with the integrative competencies required by employers today and in the future. Skills4Industry may serve as a standalone curriculum and pedagogy for education or as a work-based curricular.
  2. Connected Digital Business Assistants: Skills4Industry help businesses identify and quantify workflow (tangible and intangible) processes from the thinking, planning, and implementation through problem-solving, the continuous reconciliation of activities by learning and the self-management required for improvement.

Occupational (x) and competency (y) mapping across industry, sectors, trades, and domains (ISTD) through ten levels for humans and four stages for machine learning represent a map with quantifiable nodes of humans and machine task activities across an organizations’ value chain. Each node within our task activities map, act as a stimulus to a series of proactive reactions to problems.

Please complete and submit the application form here!