If you were to interview a baseball player, you would not ask him how he holds the bat, and how far apart he keeps his feet. Yet, these are the kind of questions people get asked on the interviews – theoretical.
Let us access their mind and help you to choose best-fit talent – a natural way!
Our brain is a decision making engine. It takes less than a second to process millions of information, sorts what is deems as relevant or irrelevant information to move forward. From how a person think, it translates into behaviors & actions. Everything in the universe conforms to mathematical rules and ratios. So if we understand the “mathematical patterns”, we come to understand the structure of how things work.
We use advanced algorithm technology to extract “mathematical patterns” of human decision making, access deep truth of a person and predict their chemistry level with people around them. We are here to address challenges in today’s talent management and acquisition using Chemistry Indicator to support businesses to perform better.
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You might presume, or at least hope, that humans are better at understanding fellow humans than machines are. But a new MIT study suggests an algorithm can predict someone’s behavior faster and more reliably than humans can.
Max Kanter, a master’s student in computer science at MIT, and his advisor, Kalyan Veeramachaneni, a research scientist at MIT’s computer science and artificial intelligence laboratory, created the Data Science Machine to search for patterns and choose which variables are the most relevant. Their paper on the project results (pdf) was presented at the IEEE Data Science and Advanced Analytics conference in Paris.
Calculating collective behavioral patterns
Professor Fornasier from Technical University of Munich and his team have recently proven mathematical statements that demonstrate how surprisingly easy it is to automatically generate precise models for specific, relatively simple group interactions based on observed dynamics data.
Using computer simulations, the mathematicians can describe potential collective behavioral patterns of a large number of individuals who mutually influence each other in a given situation. “In the next step we can then also make predictions about future behavior,” says Fornasier. “And once we can calculate the behavior of a group of interacting agents in advance, we are only one small step away from controlling them.”
Watch consciousness is a mathematical pattern