There is less than a month left before the final conference of the Design Laboratory of the Intellect Foundation – on May 27, the teams will present their solutions with real industrial potential.
These solutions are not university tasks, but ready–made business tools: teams develop them from scratch based on empirical research, accompanied by experienced industry mentors.
The project laboratory has become a real platform for the synergy of technology, scientific solutions and an industrial approach: at the start, participants received case studies with a clearly defined request and expected result. Further work was carried out in the format of regular cross-sections with monitoring of key milestones and monthly recording of achieved indicators.
We talked with Sergey Stukalo, mentor of the project teams, about how participants manage to find effective solutions for complex cases, what criteria are used to evaluate the success of projects, and how completed projects will be integrated into the industry.
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– What criteria and metrics are used to evaluate the success of solving the case by the participants?
– The assessment is based on applied indicators using metrics used in international practice. The focus is on the unit economics of the solution and the speed of bringing the product to implementation, as well as its scalability and operational readiness. The quality of the data and the accuracy of the models are separately evaluated, including key sustainability indicators, as well as the architectural sophistication of the solution, the stability of the work and the correctness of integration with external systems. Additionally, the product value, the degree of meeting the real expectations of the business, the presence of a competitive advantage and the measurable effect of implementation are taken into account. We also pay attention to the dynamics of the team, the speed of iteration, the ability to adapt to changes, as well as interpersonal interaction and teamwork within the group.
– What technologies and tools are most often used in solving cases?
– It would not be entirely correct to name specific systems and metrics in this case, including taking into account our high requirements for confidentiality and protection of the solutions being developed, as well as the creative approaches used. In summary, I can say that data management and analytics tools, machine learning and forecasting methods, image and video processing technologies, recognition and classification algorithms, as well as integration solutions for embedding in business processes are used. At the same time, classical tools in the field of artificial intelligence are actively used.
– How actively do students work with real data from the industry? How is data quality and security ensured?
– Working with real data is a basic condition for most projects, because only in this case it is possible to get a clear applicable result. Due to direct interaction with the industry, a high group efficiency is formed, which often exceeds expectations. This is achieved through the synergy of business and students, when participants work not with abstract cases, but with real tasks and actual constraints, which fundamentally distinguishes the format from formal educational modeling. This format allows us to form a fundamentally new approach to the interaction of science and business, both in local solutions and for the economy and industry as a whole.
Data security is provided on the business side through its own systems and internal circuits within which teams work. Access to data is regulated, depersonalization of isolated environments is used, which allows you to simultaneously maintain confidentiality and ensure workflow.
– How can you assess the level of preparation of the participants? What key technical skills do students acquire or upgrade?
– The level of training of the participants is generally above average, but it varies depending on the initial experience, and everyone has an area for further growth. Within the laboratory, there is a rapid transition from theoretical knowledge to practical application, which creates a fundamentally different level of training for the market. The assessment of the participants is structured strictly and as impartially as possible, based on applied results, quality of solutions and contribution to teamwork. In the process of working with real business tasks, participants develop a range of skills, including working with data at all stages, building, configuring and testing models, designing solution architecture, integrating with existing systems, understanding business constraints and requirements, as well as analytical skills and willingness to work with businesses anywhere in the world.
As a result, participants begin to work not with individual tools, but with the task as a whole, from the formulation to the implementation of the solution, forming a systematic thinking and applied professional level.
The creation of the Design Laboratory became possible thanks to the support of the Oleg Deripaska Foundation "Volnoe Delo". You can find out more about the laboratory's activities on our website in the "Project Laboratory" section.
