Prosecution Insights
Prosecution Insights
Technology area: Computing & Software
1 pending office actions • 1 art units • 1 examiners • 0 of 1 (0%) have an AI response strategy ready • 2 patents granted in the last 365 days
Substrate Artificial Intelligence SA is currently managing a patent portfolio within the Computing & Software technology area. The company has 1 pending office action, which represents the current focus of its prosecution efforts. This 1 pending office action indicates a specific engagement with the patent office to secure rights for its artificial intelligence innovations. In the Computing & Software sector, navigating the evolving standards for patentability is a critical task.
The prosecution of these assets is overseen by 1 distinct examiner and is located within 1 distinct art unit. This concentration suggests that the technical subject matter is specialized, requiring review by a specific group within the patent office. For practitioners, this means that the outcome of the current pending matter is tied to the expertise of 1 distinct art unit. This focused examination environment can lead to a more consistent application of technical standards for the 1 distinct examiner involved.
CHEN, KUANG FU is the busiest examiner for this portfolio, currently handling 1 busiest examiner pending office action. Because this examiner is responsible for the pending action, their individual examination style is a primary factor in the prosecution's progress. This concentration of work under 1 distinct examiner simplifies the communication path but centralizes the review process. Practitioners can focus on the specific requirements of CHEN, KUANG FU to move the 1 busiest examiner pending office action toward a resolution.
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 |
|---|---|
| Multi-statute (no §101) | 1 (100%) |
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 |
|---|---|---|---|
| CHEN, KUANG FU | 1 | 79.7% | +69.0% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17869493 | SYSTEMS AND METHODS FOR EFFICIENTLY IMPLEMENTING HIERARCHIAL STATES IN MACHINE LEARNING MODELS USING REINFORCEMENT LEARNING | CHEN, KUANG FU | — |
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 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17869493 | SYSTEMS AND METHODS FOR EFFICIENTLY IMPLEMENTING HIERARCHIAL STATES IN MACHINE LEARNING MODELS USING REINFORCEMENT LEARNING | CHEN, KUANG FU | — |
| Art Unit | Apps |
|---|---|
| 2143 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 17869493 | SYSTEMS AND METHODS FOR EFFICIENTLY IMPLEMENTING HIERARCHIAL STATES IN MACHINE LEARNING MODELS USING REINFORCEMENT LEARNING | CHEN, KUANG FU | 2143 | §102§103§112 | Final Rejection | — | Pending | Jul 20, 2022 |
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