Garbage Detection, from Space

Updated: Apr 15, 2021


This is the eighth in a series of interviews with members of the Machine Commons supplier Collective. Subscribe to the site to be alerted about future posts, or become a partner today!



Sergey Sukhanov runs AI Superior, a machine learning and data science consultancy whom pride themselves on rapid prototyping and a research heavy company ethos.



How has business been through the pandemic?


“In the beginning and after the first lockdown, people were sceptical."


"Investors were slowing investments, businesses unwilling to invest in new projects and technologies."

"New customers were still happening, but we could feel the market became silent for a few months. Nobody knew what to expect.”


“There were so many uncertainties with the virus. Then, once scientists clarified a few things about our future, the market really started up again. Investment in tools and analytics came back.”



What did you use the down time for?


“We used this time to strengthen our competence in promising areas and developed several analytical products/components."


"We were certain, even if the world changes, people will still require data analysis.”

“Machine learning is already impacting so many domains. There’s huge potential for the future.”



Working on anything interesting?


“Generally speaking, we work across many verticals so we try to make sure the analytics we develop are transferable across business domains.”

“We developed a platform that extracts entities and message aspects, i.e. For restaurant aspects like food there are multiple components to an experience: people can like the food but think the service was poor. This enables a much deeper understanding of any customer review.”


“We adapted it to other businesses. So, airlines for example, or any company that deals with customers can use this analytical platform.”


“We also built a computer vision system that can track different road entities – like cars, bicycles and pedestrians – to perform behaviour analysis. It can also capture more granular information, like the make and model of the car. i.e., BMW 3.”


“We noticed that these analytics were required by different businesses, like retail companies, or a shopping mall: it helps them to understand the cars that pass by and therefore estimate the income of the neighbourhood; or ad companies can understand the customers that walk by."


“Additionally, we see interest from companies that are dealing with security and access control.”



Is developing reusable code a deliberate business strategy?


"We’re always trying to increase the production speed of the development team.”


“Whilst it’s not our business model to create reusable modules, there are generic components to every business."

“Once we approach a new use case, we see how its KPIs and data fit to pre-developed modules and then adjust the system, or develop components from scratch if it is something unique and new.”



With two years of core modules developed, are you getting noticeably more efficient?


“Yes and no! Yes, because obviously more problems to tackle, more use cases available for us to unroll existing packages and integrate.”