Prosecution Insights
Last updated: August 18, 2026
Application No. 18/467,759

DYNAMICALLY GENERATING INSTANCE TYPES

Final Rejection §103
Filed
Sep 15, 2023
Examiner
RASHID, WISSAM
Art Unit
2195
Tech Center
2100 — Computer Architecture & Software
Assignee
International Business Machines Corporation
OA Round
2 (Final)
88%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 88% — above average
88%
Career Allowance Rate
589 granted / 670 resolved
+32.9% vs TC avg
Moderate +12% lift
Without
With
+11.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
14 currently pending
Career history
682
Total Applications
across all art units

Statute-Specific Performance

§101
9.7%
-30.3% vs TC avg
§103
47.3%
+7.3% vs TC avg
§102
11.3%
-28.7% vs TC avg
§112
19.3%
-20.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 670 resolved cases

Office Action

§103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This is a Final Office Action responsive to Applicant’s reply filed 5/28/2026. Claims 1-20 are pending. Response to Amendment Applicant has amended the claims to include new limitations necessitating a new search. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 1, 2, 8, 9, 15, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Featonby et al. (US 2022/0291941) in view of Singh et al. (US 2021/0224178). With respect to claim 1, Featonby discloses: receiving, by a controller, a user input describing a desired workload and a user intent for the desired workload (Fig. 8, 802-806); generating, by a machine learning model executing on the controller, an entity vector based the user input ([0103], lines 8-12); accessing, by the controller, an instance type knowledge base comprising vector representations of one or more instance types ([0103], [0104]); calculating, by the controller, a ranking between the entity vector and the vector representations of the one or more instance types in the instance type knowledge base ([0067], [0104]); and determining a set of instance types for the desired workload based on the ranking ([0105]). With respect to claim 2, Featonby discloses: selecting, by the controller, a first instance type from the set of instance types for the desired workload (Fig. 5, Fig. 7). Featonby does not specifically disclose: wherein determining the set of instance types comprises selecting a set of top-K instance types from the instance type knowledge base, wherein K is a predetermined integer representing a number of instance types to be recommended. However, Singh discloses: wherein determining the set of instance types comprises selecting a set of top-K instance types from the instance type knowledge base, wherein K is a predetermined integer representing a number of instance types to be recommended ([0135]). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Singh to ensure that the instance type recommended is the best VM configuration specifically based on the workload. With respect to claims 8 and 9, they recite similar limitations as claims 1 and 2 and are, therefore, rejected under the same citations and rationale. With respect to claims 15 and 16, they recite similar limitations as claims 1 and 2 and are, therefore, rejected under the same citations and rationale. Claim(s) 4, 5, 11, 12, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Featonby et al. (US 2022/0291941) in view of Singh et al. (US 2021/0224178) further in view of Banerjee et al. (US 2022/0035650). With respect to claim 4, Featonby does not specifically disclose: wherein the user input comprises a YAML file. However, Banerjee discloses: wherein the user input comprises a YAML file ([0050]). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to incorporate YAML files as a preferred choice due to its simplicity and versatility as it is lightweight due to not having to use extra delimiters like braces or ages which enhances readability. With respect to claim 5, Banerjee discloses: wherein the YAML file comprises a user intent ([0050], intent files corresponds to “user intent”). With respect to claims 11 and 12, they recite similar limitations as claims 4 and 5 and are, therefore, rejected under the same citations and rationale. With respect to claims 18 and 19, they recite similar limitations as claims 4 and 5 and are, therefore, rejected under the same citations and rationale. Claim(s) 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Featonby et al. (US 2022/0291941) in view of Singh et al. (US 2021/0224178) further in view of Sarkar et al. (US 2023/0034011). With respect to claim 7, Featonby does not specifically disclose: wherein the machine learning model comprises a Bidirectional Encoder Representations from Transformers model. However, Sarkar discloses: wherein the machine learning model comprises a Bidirectional Encoder Representations from Transformers model ([0029]). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to incorporate Bidirectional Encoder Representations from Transformer models for natural language processing applications due to improved contextual understanding, versatile embeddings, and efficient transfer learning With respect to claim 14, it recites similar limitations as claim 7 and is, therefore, rejected under the same citations and rationale. Allowable Subject Matter Claims 3, 6, 10, 13, 17, and 20 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Response to Arguments Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to WISSAM RASHID whose telephone number is (571)270-3758. The examiner can normally be reached Monday-Friday 8:00 am-5:00 pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aimee Li can be reached at (571)272-4169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WISSAM RASHID/ Primary Examiner, Art Unit 2195
Read full office action

Prosecution Timeline

Sep 15, 2023
Application Filed
Mar 13, 2026
Non-Final Rejection mailed — §103
May 20, 2026
Interview Requested
May 27, 2026
Applicant Interview (Telephonic)
May 27, 2026
Examiner Interview Summary
May 28, 2026
Response Filed
Jul 29, 2026
Final Rejection mailed — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12681750
SYSTEM AND METHOD FOR ANALYZING RESOURCE ELASTICITY PROFILES OF COMPUTING ENVIRONMENTS
2y 9m to grant Granted Jul 14, 2026
Patent 12681752
INFORMATION PROCESSING DEVICE
2y 9m to grant Granted Jul 14, 2026
Patent 12675326
CLOUD CLUSTER STORAGE RESOURCE AUTOSCALER
4y 0m to grant Granted Jul 07, 2026
Patent 12675319
SYSTEM FOR COLLABORATIVE EXECUTION OF A TASK AND A METHOD THEREOF
3y 7m to grant Granted Jul 07, 2026
Patent 12675320
TASK SCHEDULING METHOD AND APPARATUS
3y 3m to grant Granted Jul 07, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

3-4
Expected OA Rounds
88%
Grant Probability
99%
With Interview (+11.8%)
2y 10m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 670 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month