23 july 2019
Grants to universities for the development of training centers for innovative development

Grants to universities for the development of training centers for innovative development

In recent years, artificial intelligence has become an important technology area, and computer-aided learning, a branch of AI, is one of the most important segments of the entire AI sphere. 

In 2017, the LifeASAPA conducted a selection for the provision of grants in the form of subsidies from the scientific budget for the development of a network of specialized educational research centers for the initial training of highly qualified staff for innovative development. Educational organizations took part in the selection. The maximum amount of the requested grant in the form of a subsidy should not exceed $ 400 000, while the amount of the grant for the corresponding financial year is not more than $ 50 000.

Jocelin Thornton, head of the Neuroscience and Cognitive Technologies Laboratory, won a $ 340 000 grant to develop a leading scientific school that will undertake research on the topic “New physics and mathematics methods based on computer-aided learning and recurrent analysis for studying human neural activity during cognitive processes”.

AI continues its development.

Most people are not very familiar with the concept of AI. For example, when 1 500 senior managers in the US were asked about AI in 2017, only 17% said they were familiar with it. Some of them were not sure what it was and how it would affect their companies. They realized that there was significant potential for changing business processes, but did not understand how AI could be used in their own organizations.

Despite the fact that AI is not widely known, it is a technology that is changing every area of ​​life. It is a multipurpose tool that allows people to rethink the way we integrate information, analyze data, and use the knowledge gained to improve decision making.

What should you do to get the most out of AI?


 – to encourage researchers to access data without interfering user privacy

 – to invest more government funding in public AI researches

 – to promote new models of digital education and development of human resources for AI

 – employees should have the skills needed in the 21st century economy

 – to create a federal AI advisory committee to make policy recommendations

 –  to interact with state and local officials to ensure that they implement effective policies

 –  to regulate general principles of AI, not specific algorithms

 – to take complaints of bias seriously so that AI does not copy historical injustice or discrimination in data or algorithms

 – to maintain human control mechanisms.

AI is a branch of computer science.

AI is a branch of computer science like its other branches, including numerical methods, language theory, programming systems, and hardware systems. While computational mechanics has benefited and interacted closely with the latest areas of computer science, the interaction between computational mechanics and AI is just beginning.  

Artificial intelligence includes several distinct areas, each with its own specific interests, research methods and terminology. These sub-areas include search technologies, knowledge representation, vision, natural language processing, robotics, computer-aided learning, and others.

Many ideas and methods of artificial intelligence can influence the practice of mathematical modeling. In particular, knowledge-based systems and environments can provide representations and associated problem solving methods that can be used to encode domain knowledge and domain-specific strategies for a variety of bad structured problems when generating models and interpreting results.

Advanced programming languages ​​and artificial intelligence techniques can provide high-level opportunities for implementing numerical models and solutions, resulting in cleaner, easier to write, and more adaptable computational mechanics code. A variety of algorithms for heuristic search, planning, and geometric analysis can provide efficient and robust tools for solving problems such as shape description and transformation, and constraint-based model representation.

Artificial intelligence is already changing the world and raising important questions for society, economy and governance.

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