AvaWatz Company, a technology company that supports collaboration among robots, is pleased to announce the filing of a patent application with the United States Patent and Trademark Office (USPTO).
The patent application, titled “System and Method for Labeling, Evaluation, and Improvement of Training and Testing for Machine Learning,” introduces the AvaWatz approach to the difficult issue of training data required to train deep learning and machine learning models. The AvaWatz approach not only saves time and reduces the cost associated with the training of such systems, it also makes for a more accurate model that a user can have more trust in.
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Machine learning software generally learns by example – the more examples an algorithm can examine, the better it learns. But feeding the system with tons of examples is laborious, boring, and time-consuming work, particularly with specialized data. Collecting and labeling a sufficiently large set of examples is often the biggest obstacle to the project’s success. That’s the problem the AvaWatz patent solution solves. It improves the model’s performance, by finding and correcting weaknesses in the training dataset, and retraining the model, until the model achieves higher performance.
“We originally developed these tools for our own use, because many of the use cases we tackle involve uncommon types of data like small fragments of debris or uncommon operating conditions like severe weather, off-road travel,” said Dr. Rajini Anachi, CEO of AvaWatz. “We make it available as part of our Trusted AI services to our customers and to others in the Artificial Intelligence community. We feel that adoption of this novel technology will help many who work with specialized use cases and need to build customized machine learning applications.”
SOURCE: PR Newswire