Prosecution Insights
Prosecution Insights
Tech Center 4100 • Art Units: 2145 2148 2166 2171 2175 4100
This examiner grants 66% of resolved cases
Ryan S. Barrett serves in Tech Center 4100 and Art Unit 2145. He has 429 resolved cases. His allowance rate is 65.5 percent. The median days to allowance for his granted patents is 1209. This 1209-day figure provides a timeline for applicants to expect when their cases are granted.
The interview lift for this examiner is 41.2 percent. This 41.2 percent lift is an increase when compared to the 65.5 percent baseline. It suggests that cases involving an interview have a higher probability of allowance than those that do not. For practitioners in Art Unit 2145, this data point indicates that direct communication is an effective strategy.
With 429 resolved cases, the data for this examiner is established. The allowance rate and median pendency describe the typical outcome and timing for his docket. The interview lift is a significant metric, showing a statistical benefit to conducting an interview during the prosecution process.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 18351417 | TRAINING AND APPLICATION METHOD AND APPARATUS FOR NEURAL NETWORK MODEL, AND STORAGE MEDIUM | Final Rejection | CANON KABUSHIKI KAISHA |
| 18274531 | DISTRIBUTED MACHINE LEARNING WITH NEW LABELS USING HETEROGENEOUS LABEL DISTRIBUTION | Non-Final OA | Telefonaktiebolaget LM Ericsson (publ) |
| 18382029 | OPTIMIZING DEVELOPMENT OF A QUANTUM CIRCUIT OR A QUANTUM MODEL | Non-Final OA | International Business Machines Corporation |
| 18473217 | ARTIFICIAL INTELLIGENCE PREDICTION SUPERVISION | Non-Final OA | INTERNATIONAL BUSINESS MACHINES CORPORATION |
| 18123710 | CROSSOVER SIMULATION AND CAUSATION DETECTION USING SIMULATION ENVIRONMENTS | Non-Final OA | International Business Machines Corporation |
| 18429072 | AUTOMATICALLY GENERATING METRIC OBJECTS USING A MACHINE LEARNING MODEL | Non-Final OA | Salesforce, Inc. |
| 18571196 | FINE-TUNING METHOD, DEVICE AND APPLICATION FOR CLASSIFICATION MODEL OF KNOWLEDGE REPRESENTATION DECOUPLING | Non-Final OA | ZHEJIANG UNIVERSITY |
| 18308473 | INTELLIGENT SELF-ADJUSTING METRIC COLLECTION | Final Rejection | NetApp, Inc. |
| 18640851 | BATCH SELECTION POLICIES FOR TRAINING MACHINE LEARNING MODELS USING ACTIVE LEARNING | Non-Final OA | Sanofi |
| 18185281 | FRAMEWORK FOR SIMULATING GENERAL MULTI-SCALE PROBLEMS | Final Rejection | Brown University |
IP Author analyzes examiner patterns and generates tailored response strategies with the highest chance of allowance.
Build Your Strategy