Prosecution Insights
Prosecution Insights
23 pending office actions • 18 art units • 23 examiners • 21 of 23 (91%) have an AI response strategy ready • 35 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 23 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 23 of the docket's apps have a known mailing date.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 4 (17%) |
| §103 only | 15 (65%) |
| §102 only | 2 (9%) |
| §112 only | 1 (4%) |
| No statute on record | 1 (4%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| JOHNSON, KYLE T | 1 | 85.1% | +15.5% |
| LUBIT, RYAN A | 1 | 63.2% | +38.3% |
| RAHAMAN, SHAHAN UR | 1 | 76.0% | +12.4% |
| TREHAN, AKSHAY | 1 | 71.2% | +23.8% |
| SUN, HAI TAO | 1 | 73.2% | +25.8% |
| CAO, CHUN | 1 | 84.6% | +12.6% |
| TABOR, AMARE F | 1 | 82.8% | +23.0% |
| ISHIZUKA, YOSHIHISA | 1 | 68.5% | +20.2% |
| WERNER, MARSHALL L | 1 | 65.9% | +45.3% |
| LE, JOHN H | 1 | 87.9% | +7.4% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18572914 | CONTROLLING A MAGNETIC FIELD OF A MAGNETIC CONFINEMENT DEVICE USING A NEURAL NETWORK | CAO, CHUN | 20d |
| 18981230 | DISPATCHER-EXECUTOR SYSTEMS FOR MULTI-TASK LEARNING | JOHNSON, KYLE T | 40d |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18025304 | CONTROLLING AGENTS USING RELATIVE VARIATIONAL INTRINSIC CONTROL | SIPPEL, MOLLY CLARKE | 44d overdue |
| 18275737 | GENERATING DIFFERENTIABLE ORDER STATISTICS USING SORTING NETWORKS | LE, JOHN H | 30d overdue |
| 18334112 | JOINTLY LEARNING EXPLORATORY AND NON-EXPLORATORY ACTION SELECTION POLICIES | LEE, MICHAEL CHRISTOPHER | 11d overdue |
| 18275933 | PREDICTING PROTEIN AMINO ACID SEQUENCES USING GENERATIVE MODELS CONDITIONED ON PROTEIN STRUCTURE EMBEDDINGS | WERNER, MARSHALL L | 28d |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18277729 | NOWCASTING USING GENERATIVE NEURAL NETWORKS | ISHIZUKA, YOSHIHISA | 38d overdue |
| 18864656 | VARIABLE RESOLUTION VARIABLE FRAME RATE VIDEO CODING USING NEURAL NETWORKS | RAHAMAN, SHAHAN UR | 10d overdue |
| 18967935 | LEARNED COMPUTER CONTROL USING POINTING DEVICE AND KEYBOARD ACTIONS | LUBIT, RYAN A | 3d overdue |
| 18852940 | ENHANCING IMAGES FROM A MOBILE DEVICE TO GIVE A PROFESSIONAL CAMERA EFFECT | TREHAN, AKSHAY | 5d |
| 18572914 | CONTROLLING A MAGNETIC FIELD OF A MAGNETIC CONFINEMENT DEVICE USING A NEURAL NETWORK | CAO, CHUN | 20d |
| 18275933 | PREDICTING PROTEIN AMINO ACID SEQUENCES USING GENERATIVE MODELS CONDITIONED ON PROTEIN STRUCTURE EMBEDDINGS | WERNER, MARSHALL L | 28d |
| 18367305 | RECURRENT NEURAL NETWORKS FOR DATA ITEM GENERATION | TABOR, AMARE F | 34d |
| 18981230 | DISPATCHER-EXECUTOR SYSTEMS FOR MULTI-TASK LEARNING | JOHNSON, KYLE T | 40d |
| Art Unit | Apps |
|---|---|
| 2125 | 4 |
| 2857 | 2 |
| 2148 | 2 |
| 3656 | 1 |
| 2626 | 1 |
| 2426 | 1 |
| 2639 | 1 |
| 2616 | 1 |
| 2115 | 1 |
| 2434 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18981230 | DISPATCHER-EXECUTOR SYSTEMS FOR MULTI-TASK LEARNING | JOHNSON, KYLE T | 3656 | §103 | Non-Final OA | 40d | Pending | Dec 13, 2024 |
| 18967935 | LEARNED COMPUTER CONTROL USING POINTING DEVICE AND KEYBOARD ACTIONS | LUBIT, RYAN A | 2626 | §103 | Final Rejection | 3d overdue | AI Ready | Dec 04, 2024 |
| 18864656 | VARIABLE RESOLUTION VARIABLE FRAME RATE VIDEO CODING USING NEURAL NETWORKS | RAHAMAN, SHAHAN UR | 2426 | §103 | Non-Final OA | 10d overdue | AI Ready | Nov 11, 2024 |
| 18852940 | ENHANCING IMAGES FROM A MOBILE DEVICE TO GIVE A PROFESSIONAL CAMERA EFFECT | TREHAN, AKSHAY | 2639 | §103 | Non-Final OA | 5d | AI Ready | Sep 30, 2024 |
| 18600552 | ANIMATING IMAGES USING POINT TRAJECTORIES | SUN, HAI TAO | 2616 | §103 | Final Rejection | 53d | AI Ready | Mar 08, 2024 |
| 18572914 | CONTROLLING A MAGNETIC FIELD OF A MAGNETIC CONFINEMENT DEVICE USING A NEURAL NETWORK | CAO, CHUN | 2115 | §102 | Non-Final OA | 20d | AI Ready | Dec 21, 2023 |
| 18367305 | RECURRENT NEURAL NETWORKS FOR DATA ITEM GENERATION | TABOR, AMARE F | 2434 | Other | Non-Final OA | 34d | AI Ready | Sep 12, 2023 |
| 18277729 | NOWCASTING USING GENERATIVE NEURAL NETWORKS | ISHIZUKA, YOSHIHISA | 2857 | §103 | Non-Final OA | 38d overdue | AI Ready | Aug 17, 2023 |
| 18275933 | PREDICTING PROTEIN AMINO ACID SEQUENCES USING GENERATIVE MODELS CONDITIONED ON PROTEIN STRUCTURE EMBEDDINGS | WERNER, MARSHALL L | 2125 | §101 | Non-Final OA | 28d | AI Ready | Aug 04, 2023 |
| 18275737 | GENERATING DIFFERENTIABLE ORDER STATISTICS USING SORTING NETWORKS | LE, JOHN H | 2857 | §101 | Non-Final OA | 30d overdue | AI Ready | Aug 03, 2023 |
| 18230056 | CONTROLLING AGENTS USING AUXILIARY PREDICTION NEURAL NETWORKS THAT GENERATE STATE VALUE ESTIMATES | CHEN, KUANG FU | 2143 | §103 | Non-Final OA | 50d | AI Ready | Aug 03, 2023 |
| 18275332 | RENDERING NEW IMAGES OF SCENES USING GEOMETRY-AWARE NEURAL NETWORKS CONDITIONED ON LATENT VARIABLES | AHN, CHRISTINE YERA | 2615 | §103 | Non-Final OA | 39d | AI Ready | Aug 01, 2023 |
| 18275045 | DETERMINING PRINCIPAL COMPONENTS USING MULTI-AGENT INTERACTION | HINCKLEY, CHASE PAUL | 2124 | §103 | Non-Final OA | 13d | AI Ready | Jul 31, 2023 |
| 18334112 | JOINTLY LEARNING EXPLORATORY AND NON-EXPLORATORY ACTION SELECTION POLICIES | LEE, MICHAEL CHRISTOPHER | 2128 | §101 | Non-Final OA | 11d overdue | AI Ready | Jun 13, 2023 |
| 18127551 | ALLOCATING COMPUTING RESOURCES BETWEEN MODEL SIZE AND TRAINING DATA DURING TRAINING OF A MACHINE LEARNING MODEL | TAN, DAVID H | 2145 | §103 | Non-Final OA | 38d overdue | AI Ready | Mar 28, 2023 |
| 18025304 | CONTROLLING AGENTS USING RELATIVE VARIATIONAL INTRINSIC CONTROL | SIPPEL, MOLLY CLARKE | 2122 | §101 | Non-Final OA | 44d overdue | AI Ready | Mar 08, 2023 |
| 18105180 | CONTROLLING COMPUTING DEVICES USING HIERARCHICAL AGENTS | LAU, KAITLYN RENEE | 2148 | §103 | Final Rejection | 54d | Pending | Feb 02, 2023 |
| 18072175 | ACTION SELECTION FOR REINFORCEMENT LEARNING USING A MANAGER NEURAL NETWORK THAT GENERATES GOAL VECTORS DEFINING AGENT OBJECTIVES | VAUGHN, RYAN C | 2125 | §103 | Non-Final OA | 42d | AI Ready | Nov 30, 2022 |
| 17959232 | NEURAL NETWORKS WITH TRANSFORMED ACTIVATION FUNCTION LAYERS | HADDAD, MAJD MAHER | 2125 | §103 | Non-Final OA | 31d overdue | AI Ready | Oct 03, 2022 |
| 17797203 | TRAINING MULTI-OBJECTIVE NEURAL NETWORK REINFORCEMENT LEARNING SYSTEMS | PRESSLY, KURT NICHOLAS | 2125 | §102 | Final Rejection | 31d overdue | AI Ready | Aug 03, 2022 |
| 17625361 | TRAINING A NEURAL NETWORK TO CONTROL AN AGENT USING TASK-RELEVANT ADVERSARIAL IMITATION LEARNING | KAPOOR, DEVAN | 2126 | §103 | Non-Final OA | 26d | AI Ready | Jan 07, 2022 |
| 17359427 | REINFORCEMENT LEARNING USING TARGET NEURAL NETWORKS | PELLETT, DANIEL T | 2121 | §112 | Final Rejection | 5d | AI Ready | Jun 25, 2021 |
| 16818932 | SCHEDULING COMPUTATION GRAPHS USING NEURAL NETWORKS | BEJCEK II, ROBERT H | 2148 | §103 | Final Rejection | 156d overdue | AI Ready | Mar 13, 2020 |
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