Prosecution Insights
Prosecution Insights
Tech Center 2100 • Art Units: 2121 2122 2127 2148 2165
This examiner grants 50% of resolved cases
Tewodros E. Mengistu examines cases in Art Unit 2121 of Tech Center 2100. With 147 resolved cases, the allowance rate is 49.7%. The interview lift is 30.7%, which is a key strategy for overcoming the moderate allowance rate. This 30.7% lift indicates that interviews are highly effective in this docket. The median days to allowance is 1616, indicating a very long prosecution process.
Practitioners should use interviews early to navigate the 1616-day pendency and improve the 49.7% chance of allowance. With 147 resolved cases, the data set is sufficient to show the significant impact of direct examiner engagement. In Art Unit 2121, the long duration of prosecution makes the 30.7% lift a vital tool for efficiency. Applicants should be prepared for a multi-year commitment but can use interviews to significantly boost their odds of success.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 17388919 | AUTOMATICALLY REDUCING MACHINE LEARNING MODEL INPUTS | Non-Final OA | Capital One Services, LLC |
| 18318143 | Use of a Training Framework of a Multi-Class Model to Train a Multi-Label Model | Non-Final OA | PayPal, Inc. |
| 18571740 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM | Non-Final OA | Sony Group Corporation |
| 18043623 | MEDICAL ARM CONTROL SYSTEM, MEDICAL ARM DEVICE, MEDICAL ARM CONTROL METHOD, AND PROGRAM | Final Rejection | SONY GROUP CORPORATION |
| 18437118 | DATA PROCESSING METHOD AND APPARATUS, PROGRAM PRODUCT, COMPUTER DEVICE, AND MEDIUM | Non-Final OA | Tencent Technology (Shenzhen) Company Limited |
| 18498257 | SYSTEMS AND METHODS FOR LANGUAGE AGENT OPTIMIZATION | Non-Final OA | Salesforce, Inc. |
| 18392877 | HYBRID MACHINE LEARNING CLASSIFIERS FOR MANAGING USER REPORTS | Final Rejection | Roku, Inc. |
| 18204048 | HYBRID MACHINE LEARNING CLASSIFIERS FOR USER RESPONSE STATEMENTS | Final Rejection | Roku, Inc. |
| 18230311 | BATCH SCHEDULING FOR EFFICIENT EXECUTION OF MULTIPLE MACHINE LEARNING MODELS | Final Rejection | NVIDIA Corporation |
| 18139016 | MULTI-TRACK MACHINE LEARNING MODEL TRAINING USING EARLY TERMINATION IN CLOUD-SUPPORTED PLATFORMS | Final Rejection | NVIDIA Corporation |
| 18685966 | LABEL GENERATION METHOD, MODEL GENERATION METHOD, LABEL GENERATION DEVICE, LABEL GENERATION PROGRAM, MODEL GENERATION DEVICE, AND MODEL GENERATION PROGRAM | Non-Final OA | The University of Tokyo |
| 17850517 | IMPLEMENTATION OF POOLING AND UNPOOLING OR REVERSE POOLING IN HARDWARE | Final Rejection | Imagination Technologies Limited |
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