GBT Technologies Inc., a company specializing in the development of Internet of Things (IoT) and Artificial Intelligence (AI) enabled networking and tracking technologies, including its GopherInsight global mesh network technology platform for both mobile and fixed solutions, is pleased to announce that it has successfully completed another milestone in its AI development.
In this milestone, using a complex robot, GBT has achieved the goal of a “self-learning” machine. Typical machine learning needs humans to tell it how to make accurate predictions using specific data that it is given. GBT’s Avant! AI System is designed to function like a human brain using deep learning algorithms, based on RNN (Recurrent Neural Network) to process the information resulting in self-learning without specific direction from humans.
In a successful proof of concept trial, GBT’s Avant! AI technology was implemented in a robot to enable it to process information and reach conclusions on its own (making it a self-learning system). This is the first step in GBT’s Avant! AI implementation to enable an autonomous machine. With further development, GBT believes it can be implemented in any type of robotic, unmanned or automated system with the goal of enabling a wide variety of intelligent applications in our daily lives.
“We call this stage the self-learning stage. Here, we successfully gave a complex machine the ability to learn without being explicitly programmed. The robot can be trained to perform tasks. It will learn from its performance in order to improve on it over time, exactly as a human would do. In addition, the robot will continuously improve its knowledge through online data research and other data resources for ways to improve task performance using GBT’s knowledge extraction technology,” stated Danny Rittman, GBT’s CTO.
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Douglas Davis, the Company’s CEO added: “This robot is not a rules-based system but a true learning entity. It can learn by being trained (being given information) or on its own (researching its own information). It can educate itself and adapt to rapidly changing conditions in real time. It can be trained to carry out complex tasks that require thought and adaptation. As an example, let’s look at a simple task, like lifting an object and placing it in another location. This task can be done in few ways. The machine analyzes all possibilities virtually instantaneously and chooses the most efficient way to complete the task. In addition, it will research and learn about even better ways to carry out the same task, continuously trying for higher performance and efficiency. We are excited to continue our AI-based development and testing programs to explore many additional use cases, including to develop intelligent applications using GBT’s Avant! AI technology.”