The AIP Institute is an interdisciplinary research center that was founded in 2019 in Shenzhen, China. It develops principles and methods for classifying information, assessing its applicability, and transferring it.
History of the Institute
The Institute was founded by Aleksandr Yuryev in 2019 to research and implement the theory of Adaptive Information Potential (AIP) as a universal unit for structuring knowledge, abilities, and skills to allow them to be assessed using a binary score.
A format for storing adaptive, non-linear scenarios and tools for evaluation and teaching using the AIP methodology was developed at the end of 2019.
The active phase of AIP application began in 2020.
Mission and vision
To explore how intelligence comes to be, and to define the elements of information exchange between humans.
We aim to define aspects of information exchange between humans. People’s understanding of their own potential is currently limited. We literally consist of information that is laid down as part of our biological processes.
Our approach focuses on identifying forms of information flow and methods for information exchange between humans. Our work helps companies and governmental institutions to create both biological and artificial tools to improve the brain’s performance.
To launch the widescale application of the Adaptive Information Potential (AIP) as a unit for structuring information and as a mechanism for learning in both educational systems and occupational activity evaluation systems.
At the AIP Institute, we aim to make continuous evaluation and self-improvement possible in an era of complete automation, by breaking down your abilities and knowledge.
Founder of AIP Institute, Aleksandr Yuryev
- Cognigraphic data ontology – The cognigraphic data ontology is a dynamic ontological system that evolves to suit users’ needs and goals. The cognigraphic data ontology is designed to structure an individual’s theoretical and practical knowledge and psychomotor, cognitive, and other physiological capabilities by presenting them as development and information transfer processes and through mechanisms influencing functions and physical activity.
- Cognigraph – a personal dynamic potential map that takes the form of a set of interlinked AIP units. Cognigraphs are created on the basis of binary assessments of theoretical and practical knowledge and of psychomotor, cognitive and other physiological capabilities. This dynamic map can stand in for résumés, qualification passports, and other types of digital personal record.
- AIP Qualification Framework – a set of tools and methods that allow a binary evaluation system to be created for employees’ work activities and for personalized training to fill occupational skills gaps based on learners’ information perception profiles. AIP-based evaluation and learning enables personalized horizontal and vertical career paths to be created, incentive systems to be set up for employees on the basis of their potential, and staff to be rapidly assessed for their ability to perform certain tasks and, if. necessary, trained.
- Competency Digital Imprint – a practical educational project based on the Adaptive Information Potential. It aims to create a digital impression of a specific individual as a model for managing information collected during the course of the individual’s life, enabling this information to be passed on to future generations.
- ADANEC Format – a format for the creation of non-linear, adaptive scenarios for human-machine interaction in educational systems.
Research and development
The AIP Institute team carries out interdisciplinary research aimed at developing mechanisms for personalizing and coding information for practical use in AIP-based adaptive learning and evaluation systems.
Our research spans three main areas:
- Modeling human activity based on the consolidated results of research into brain function, cognitive processes, genetics, biology, medicine, psychology, and other fields concerned with interconnected bodily processes that involve organizing and transferring information and executing commands.
- Developing ways of adapting content and presenting information, taking into account the nature of human perception in specific contexts, making information transfer in the educational context more effective. When effective, the methods developed will decrease the amount of time spent on the process of information absorption and lead to a reduction in the amount of information transferred, with no reduction in the quality of the result achieved.
- Developing new methods for holistic evaluation of activity and training results based on AIPs. By developing interfaces for human-machine cooperation and technologies for collecting data on a person’s activity (brain activity, physiological activity, etc.) in real and near-real time, we make new approaches to the learning process possible and create more precise methods for evaluating learning outcomes, including the acquisition of implicit knowledge, skills, and abilities.