Andrej Nikonov, CEO at Cognostics AG (cognostics.de), discusses the science of thinking and the many ways AI can expand human knowledge and capability.
Andrej Nikonov, as CEO, is driven to discover new ways to apply physics and mathematics to real-world problems. Nikonov has a particular interest in stochastic processes and differential equations, evolving networks, and network theory-based models of physical systems. Regarding stochastic processes, in probability theory and other related fields, a stochastic process is a mathematical object typically defined as a collection of random variables.
Nikonov earned a bachelor’s (equivalent) in physics from Universität Hamburg and a master’s degree in applied mathematics and theoretical physics from University of Cambridge. Nikonov continued his advanced studies of physics and mathematics at Ludwig-Maximilians Universität München.
Nikonov discusses the ways his company combines technologies, cognitive sciences, and artificial intelligence. Essentially, Cognostics is the science of thinking. Nikonov states that we live in an age of exploding complexity with change happening at an ever-increasing pace. Nikonov stresses that their goal is not to replace human thinking but to evolve it further. Nikonov’s company, Cognostics’ primary goal is to expand the limits of human thought. Cognostics seeks to create products and develop technologies that will enhance human cognitive ability and the human experience.
Nikonov talks about the areas in which they are highly involved, such as healthcare, education/universities, finance, government democracy, etc.
He discusses their thorough e-learning environments that assist many businesses and entities to create AI-supported learning. He cites examples of how the system works within the healthcare space, giving an overview of patient diagnostics, communication, and how learning is applied in regard to patient treatment success and options. And he explains how doctors interact with their systems and tools.
Cognostics offers multiple products. Their Atlas product offers a unique approach that integrates advancements in learning methodology with the most current machine learning capabilities to create an abundant, interactive and intelligently structured specific knowledge space. Its machine intelligence proactively and freely seeks out developing areas of knowledge from the public as well as private sources. And Atlas exhaustively researches valued publications and databases or the open web to regularly update its knowledge graph.
Their Logos product delivers businesses, governments, and NGOs an opportunity to make more thoroughly sound decisions. The Cognostics structure pulls from decades of viable neuroscientific research regarding how the brain copes with complexity, to get to the root of problem-solving and to develop a visual reasoning architecture that can enhance basic thinking skills, assisting users to make better, meaningful decisions. Through the use of machine intelligence, the Logos suite of cognitive tools can significantly enhance the depth with which even the most diverse and complex issues can be examined cognitively.
Nikonov provides some insight into the new areas that Cognostics has branched into and hopes to further develop, from private projects to projects developed in tandem with the German government. From allocation of resources to long-term planning, the Cognostics’ system can provide many ways to assist companies and organizations with their growth and structure via the use of tools and technologies. Additionally, Nikonov expounds upon the other areas that he is enthusiastic about, specifically regarding machine learning that will transform human decision-making, deep learning, and knowledge management.