PATENT CLAIM ANALYSIS

Application Number: 15995005
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-12
Patent Classification: ["700", "254000"]

Abstract:
One embodiment of the present invention sets forth a technique for controlling the execution of a physical process. The technique includes receiving, as input to a machine learning model that is configured to adapt a simulation of the physical process executing in a virtual environment to a physical world, simulated output for controlling how the physical process performs a task in the virtual environment and real-world data collected from the physical process performing the task in the physical world. The technique also includes performing, by the machine learning model, one or more operations on the simulated output and the real-world data to generate augmented output. The technique further includes transmitting the augmented output to the physical process to control how the physical process performs the task in the physical world.

Claim (Index 11):
A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform the steps of:\n receiving, as input to a machine learning model that is configured to adapt a simulation of the physical process executing in a virtual environment to a physical world, simulated output for controlling how the physical process performs a task in the virtual environment and real-world data collected from the physical process performing the task in the physical world; performing, by the machine learning model, one or more operations on the simulated output and the real-world data to generate augmented output; and transmitting the augmented output to the physical process to control how the physical process performs the task in the physical world.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.33898
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15614489', '15188932', '14638973', '15419451', '15972793']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.387827842858165
- 35 USC 102 Novelty (BERT): 0.4956537634373759
- Combined Prediction Score: 0.3986104349160861
- Mean Citation Score: 202.61235
- Max Citation Score: 220.5485
- Similarity Product: 153.14180876067283

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test