The method works in two stages: First, the weak points of the neural network are identified, then new data similar to the errors made are identified, which allows you to classify errors and improve learning. As a result, AI training efficiency increases by 40% and the time required to develop AI systems is significantly reduced.
This innovation is particularly important for industries that use AI, such as autonomous technology and agricultural farming. Analysts predict that this class of technology could create a multi-billion dollar market in the next five years. Cognitive Pilot CEO Olga Uskova noted that these achievements will provide users with access to cutting-edge solutions and enhance their functionality.
Source: Ferra
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