Posted in | Consumer Robotics

GBT Technologies Commences R&D Activities for Machine Learning and Analog Computing

GBT Technologies Inc., September 23rd , 2019, 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, today announced that it commenced R&D activities for machine learning and analog computing, specifically targeting the area of robotics.

GBT plans to further research analog computing to drive more improvements in computational efficiency. One of the main aims of this new research and development effort is to provide machine learning algorithms with better resilience to noise and uncertainty, while avoiding a trade-off between accuracy and numerical precision. Analog computing is an innovative emerging field which GBT intends to invest in, in order to enable its AI technology with analog features.

GBT will base this new R&D effort on software to be integrated with its existing platforms and hardware. GBT analog computing plans to use arrays of nonvolatile memory to perform sets of matrix operations, enabling robots and autonomous machines with analog features; for example, robots will be able to identify noises and sounds very similar to a human, and therefore make decisions based on wider range of information. Another example would be enabling robots to recognize human body language and voice inflection, and respond appropriately.

"With this new research activity we are laying the foundation of a true human-like learning system. Analog computing for machine learning enables robots to interact with humans, not only based on visual cues, but also according to tone of speech and body language. Our AI technology plans to incorporate both high and low-level computing, which we believe is a more accurate model of human intelligence” stated Danny Rittman, GBT’s CTO.

Humans do most things automatically, meaning at a low level of instinctive decision making, and only perform specific actions at a higher level of consciousness. GBT’s robotics systems are planned to include the inherent features and benefits of analog technology, combined with our machine learning algorithms, providing them broader spectrum of data. Our goal is enable true human behavior with a system can that better hear and analyze sounds, visual imaging, thermal, and additional physical phenomenon. These efforts are a mix between the physics of AI and data science" added Douglas Davis, GBT’s CEO.


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