Autonomous and continuously self-improving learning system
US11684241B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 20, 2021 |
| Grant date | Jun 27, 2023 |
| Priority date | — |
| Expiry date | Aug 26, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and methods are provided in which an artificial intelligence inference module identifies targeted information in large-scale unlabeled data, wherein the artificial intelligence inference module autonomously learns hierarchical representations from large-scale unlabeled data and continually self-improves from self-labeled data points using a teacher model trained to detect known targets from combined inputs of a small hand labeled curated dataset prepared by a domain expert together with self-generated intermediate and global context features derived from the unlabeled dataset by unsupervised and self-supervised processes. The trained teacher model processes further unlabeled data to self-generate new weakly-supervised training samples that are self-refined and self-corrected, without human supervision, and then used as inputs to a noisy student model trained in a semi-supervised learning process on a combination of the teacher model training set and new weakly-supervised training samples. With each iteration, the noisy student model continually self-optimizes its learned parameters against a set of configurable validation criteria such that the learned parameters of the no…
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