Prosecution Insights
Prosecution Insights
Tech Center 2100 • Art Units: 2122 2129
This examiner grants 75% of resolved cases
Wilbert L. Starks is a patent examiner in Tech Center 2100 and Art Unit 2122. He has managed 668 resolved cases. The examiner has an allowance rate of 74.7 percent, which indicates that a majority of applications reach issuance. This rate serves as a primary baseline for applicants to assess their chances of success when their cases are assigned to this specific art unit.
The median time to allowance is 1250 days. This timeframe indicates that the prosecution process typically spans several years for successful applications. Practitioners can use this 1250 day median to plan their intellectual property strategy and manage expectations regarding the speed of the process. The 668 resolved cases provide a robust foundation for this temporal metric.
The data also shows an interview lift of 3.3 percent. This metric indicates that while the base allowance rate is 74.7 percent, direct communication with the examiner provides a marginal increase in the likelihood of success. The 3.3 percent lift suggests that interviews are a secondary tactical option compared to written arguments. These combined statistics offer a data-grounded view of the examination environment in Art Unit 2122.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 17468819 | METHOD OF PREDICTING SEMICONDUCTOR MATERIAL PROPERTIES AND METHOD OF TESTING SEMICONDUCTOR DEVICE USING THE SAME | Final Rejection | Samsung Electronics Co., Ltd. |
| 18109340 | INFORMATION PROCESSING METHOD AND INFORMATION PROCESSING SYSTEM | Final Rejection | Panasonic Intellectual Property Corporation of America |
| 18696052 | Learning the Joint Distribution of Two Sequences Using Little or No Paired Data | Non-Final OA | Google LLC |
| 18417556 | Multi-Layer Perceptron Architecture For Times Series Forecasting | Non-Final OA | Google LLC |
| 18118061 | CONDITIONING GRAPH NEURAL NETWORKS ON GRAPH AFFINITY MEASURE FEATURES | Final Rejection | Google LLC |
| 17356186 | UNSUPERVISED METHOD FOR BASELINING AND ANOMALY DETECTION IN TIME-SERIES DATA FOR ENTERPRISE SYSTEMS | Non-Final OA | Oracle International Corporation |
| 18702382 | System, Method, and Computer Program Product for Denoising Sequential Machine Learning Models | Non-Final OA | Visa International Service Association |
| 18327763 | REASONING WITH CONDITIONAL INDEPENDENCE GRAPHS | Final Rejection | Microsoft Technology Licensing, LLC |
| 17508117 | INFORMATION EXTRACTION FROM DOCUMENT CORPORA | Final Rejection | International Business Machines Corporation |
| 17449116 | DYNAMICALLY GENERATED KNOWLEDGE GRAPHS | Final Rejection | INTERNATIONAL BUSINESS MACHINES CORPORATION |
| 17590677 | METHOD AND APPARATUS FOR ENTERING INFORMATION, ELECTRONIC DEVICE, COMPUTER READABLE STORAGE MEDIUM | Final Rejection | Beijing Baidu Netcom Science Technology Co., Ltd. |
| 18102798 | RULES DETERMINATION VIA KNOWLEDGE GRAPH | Non-Final OA | SAP SE |
| 18573793 | FEDERATED REPRESENTATION LEARNING WITH CONSISTENCY REGULARIZATION | Non-Final OA | Bayer Aktiengesellschaft |
| 18163603 | LARGE SCALE MASK OPTIMIZATION WITH CONVOLUTIONAL FOURIER NEURAL OPERATOR AND LITHO-GUIDED SELF LEARNING | Final Rejection | NVIDIA Corp. |
| 18757832 | METHOD AND APPARATUS FOR LEARNNING LANGUAGE MODEL FROM STYLISTIC POINT OF VIEW, AND RECORDING MEDIUM FOR RECORDING THE SAME | Non-Final OA | Research & Business Foundation Sungkyunkwan University |
| 18304251 | SYSTEMS, APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR DATA-DRIVEN PREDICTIONS WITHIN A PROCESS SIMULATION SYSTEM | Final Rejection | Honeywell International Inc. |
| 18565510 | METHOD AND APPARATUS FOR DEEP LEARNING | Non-Final OA | TSINGHUA UNIVERSITY |
| 18301921 | NEURAL NETWORK ARCHITECTURE | Final Rejection | Arm Limited |
| 17500310 | MODEL-AGNOSTIC APPROACH TO INTERPRETING SEQUENCE PREDICTIONS | Non-Final OA | Feedzai - Consultadoria e Inovação Tecnológica, S.A. |
| 17219699 | MACHINE LEARNING MODEL GENERATION PLATFORM | Final Rejection | Aixplain, Inc. |
| 18488903 | Incremental Sparsification of Machine Learning Model | Final Rejection | Numenta, Inc. |
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