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 .
Response to Arguments
Applicant's arguments filed 05/21/2025 have been fully considered but they are not persuasive. Regarding arguments on pages 8-9 of the Remarks, Examiner notes that certain of the recited steps are mental processes, while others are extrasolution activity. For example, extracting communication data objects from a communication channel and generating a summary of the communications can be performed mentally. Other limitations such as inputting information to a model, receiving information, and transmitting and displaying information are all extrasolution activity, and do not integrate the abstract idea into a practical application or constitute significantly more.
Regarding arguments on pages 9-11 of the Remarks, Examiner notes that Duran still appears to teach the amended limitations. Duran teaches determining that an incident severity level of an incident exceeds a severity level threshold, in col. 18 lines 10-36. Duran further teaches in the same cited segment providing a questionnaire to the devices in the queue to determine if the user is calling about the incident. Duran also teaches in col. 18 lines 37-54 determining that the caller is calling about the same incident. Hence, if the system determines that the user is calling regarding the incident with the high severity level, this is interpreted as a severity level assigned to the communication channel, thus teaching the limitations.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Using the subject matter eligibility test from page 74621 of the Federal Register Notice titled “2014 Interim Guidance on Patent Subject Matter Eligibility,” a two-step process is performed. Under step 1, the claims are analyzed to determine if the claim is directed to a process, machine, article of manufacture, or composition of matter. In this case, claims 1-7 are directed to an apparatus, which is a machine or article of manufacture; claims 8-14 are directed to a method, which is a process, and claims 15-20 are directed to a computer program product, which is a machine or an article of manufacture. Step 2A (part 1 of the Mayo test), using the guidance from pages 50-57 of the Federal Register Vol. 84 No. 4 from Monday, January 7, 2019, requires applying a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception, determining if the claim is directed to a law of nature, a natural phenomenon, or an abstract idea. In this case, claim 1 recites extracting communication data objects, and generating a summary, which are mental processes. In Prong Two, examiners evaluate whether the judicial exception is integrated into a practical application that imposes a meaningful limit on the judicial exception. In this case, sending, storing, and receiving data is mere extrasolution activity, while use of processor, memory, computer-readable media, and a machine learning model are generic computing components, and none of the above integrate the abstract ideas into a practical application.
Step 2B (part 2 of the Mayo test) requires analyzing the claims to determine if they recite additional elements that amount to significantly more than the judicial exception. In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea itself.
Regarding claims 1, 8, and 15, extracting communication data objects and generating a summary are mental processes, which is an abstract idea. For example, a human could review communications and identify channels with high severity levels, determine data objects, and generate a summary based on the objects. Additional limitations of sending, storing, and receiving data are mere extrasolution activity, while use of processor, memory, computer-readable media, and a machine learning model are generic computing components, and none of the above integrate the abstract ideas into a practical application, or constitute significantly more.
Regarding claims 2, 4-6, 9, 11-13, 16, and 18-20, the limitations are further clarifications of the above abstract ideas.
Regarding claims 3, 10, and 17, retrieving data is mere extrasolution activity, and does not integrate the abstract ideas into a practical application or constitute significantly more.
Regarding claims 7, and 14, preprocessing the data and generating the summary are mental processes, which is an abstract idea without integration into a practical application and without significantly more.
The limitations of the claims, taken alone, do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Applicable case law cited in the Federal Register includes, but is not limited to: Alice Corp., 134 S. Ct. at 2355-56, Digitech Image Tech., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344 (Fed. Cir. 2014), Benson, 409 U.S. at 63.
See "Preliminary Examination Instructions in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al.," dated June 25, 2014, and the Federal Register notice titled "2014 Interim Guidance on Patent Subject Matter Eligibility" (79 FR 74618).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 1-4, 6-11, 13-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanikella (US 2023/0376515 A1), in view of Duran et al. (US 10,931,759 B2), hereinafter referred to as Duran.
Regarding claim 1, Tanikella teaches:
An apparatus for generating abstractive context summaries of multi-party communication channels, the apparatus comprising at least one processor and at least one memory including program code (Fig. 1 elements 108, 134, 110, 136, para [0039-40], where processor and memory are used), the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based on the multi- party communication channel identifier (para [0156-157], where the summarization component receives messages posted by different users);
generate, based on the plurality of communication data objects and utilizing a text summarization machine learning model, an abstractive context summary for the selected multi- party communication channel by inputting the plurality of communication data objects into the text summarization machine learning model to obtain the abstractive context summary (para [0158], where an abstractive summary of the messages is generated using a machine learning model);
store the abstractive context summary in a summary storage location associated with the plurality of multi-party communication channels (para [0052], where the summary document is stored);
receive, from a server associated with the selected multi-party communication channel, a member event indication indicating a member event occurrence of one or more member event occurrences associated with the selected multi-party communication channel (para [0010], [0013], where the user returning and requesting a summary document of the channel communications is the member event indication, and para [0078], [0084], where the components are associated with the server), wherein the member event indication comprises a multi-party communication channel identifier associated with the selected multi-party communication channel and a member profile identifier associated with the member event indication (Fig. 3C, para [0130], where the user selects the document affordance, where the interface includes the user and the channel, and para [0095], where the summary is associated with the user and channel);
in response to receiving the member event indication, retrieve, from the summary storage location, the abstractive context summary for the selected multi-party communication channel (para [0130], [0134], where the summary document is downloaded according to the user’s return from work); and
transmit the abstractive context summary for display on a client computing device associated with the member profile identifier (Fig. 3D, para [0131], where the summary is displayed in a window).
Tanikella does not teach:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold;
Duran teaches:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold (col. 18 lines 10-54, where an incident severity level exceeds a threshold, and data is collected based on the communication channel being associated with the incident security level above a severity threshold, and col. 19 lines 25-52, where the communication channel is between multiple parties);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella by using the incident severity threshold of Duran (Duran col. 18 lines 10-36) for the communication channel of Tanikella (Tanikella para [0156-157]), in order to determine which data feeds in a queue may provide additional information with respect to the incident (Duran col. 18 lines 10-36).
Regarding claim 2, Tanikella in view of Duran teaches:
The apparatus of claim 1, wherein the selected multi-party communication channel comprises a multi-party communication channel of the plurality of multi-party communication channels that is associated with a priority indicator (Tanikella para [0094], where a HQ virtual space is associated with other virtual spaces that are important to the user or relevant, indicating priority).
Regarding claim 3, Tanikella in view of Duran teaches:
The apparatus of claim 1, wherein the abstractive context summary for the selected multi- party communication channel is retrieved from the summary storage location in response to the member event indication and based on whether the selected multi-party communication channel is associated with a priority indicator (Tanikella para [0099], [0130], where the documents are ranked, indicating priority, and where the summary is retrieved for the user).
Regarding claim 4, Tanikella in view of Duran teaches:
The apparatus of claim 1, wherein the member event indication is at least one of: (i) a member join event, (ii) a member rejoin event, or a (iii) delayed access event (Tanikella para [0010], [0013], [0134], [0142], where the user returns from being absent, and para [0095], where the user accesses the virtual space and the summary is presented).
Regarding claim 6, Tanikella in view of Duran teaches:
The apparatus of claim 1, wherein each multi-party communication channel of the plurality of multi-party communication channels is generated in response to an incident alert and is associated with an incident identifier (Tanikella para [0011], where a virtual space or channel is created to resolve an incident, such as a bug, and para [0121], where the reporting of the incident is the alert, and where the ticket ID is the incident identifier).
Regarding claim 7, Tanikella in view of Duran teaches:
The apparatus of claim 1, wherein inputting the plurality of communications data objects into the text summarization machine learning model to obtain the abstractive context summary comprises pre-processing the plurality of communication data objects to generate pre-processed communication data objects and providing the pre-processed communication data objects to the text summarization machine learning model, wherein the text summarization machine learning model is configured to generate the abstractive context summary based on the pre-processed communication data objects (Tanikella para [0048-49], where audio conversation data is processed to generate a transcript, and para [0052], where the transcripts are input to the machine learning model for summarization).
Regarding claim 8, Tanikella teaches:
A computer-implemented method for generating abstractive context summaries of multi- party communication channels, the computer-implemented method comprising:
extracting a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based on the multi- party communication channel identifier (para [0156-157], where the summarization component receives messages posted by different users);
generating, based on the plurality of communication data objects and utilizing a text summarization machine learning model, an abstractive context summary for the selected multi- party communication channel by inputting the plurality of communication data objects into the text summarization machine learning model to obtain the abstractive context summary (para [0158], where an abstractive summary of the messages is generated using a machine learning model);
storing the abstractive context summary in a summary storage location associated with the plurality of multi-party communication channels (para [0052], where the summary document is stored);
receiving, from a server associated with the selected multi-party communication channel, a member event indication indicating a member event occurrence of one or more member event occurrences associated with the selected multi-party communication channel (para [0010], [0013], where the user returning and requesting a summary document of the channel communications is the member event indication, and para [0078], [0084], where the components are associated with the server), wherein the member event indication comprises a multi-party communication channel identifier associated with the selected multi-party communication channel and a member profile identifier associated with the member event indication (Fig. 3C, para [0130], where the user selects the document affordance, where the interface includes the user and the channel, and para [0095], where the summary is associated with the user and channel);
in response to receiving the member event indication, retrieving, from the summary storage location, the abstractive context summary for the selected multi-party communication channel (para [0130], [0134], where the summary document is downloaded according to the user’s return from work); and
transmitting the abstractive context summary for display on a client computing device associated with the member profile identifier (Fig. 3D, para [0131], where the summary is displayed in a window).
Tanikella does not teach:
extracting a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold;
Duran teaches:
extracting a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold (col. 18 lines 10-54, where an incident severity level exceeds a threshold, and data is collected based on the communication channel being associated with the incident security level above a severity threshold,, and col. 19 lines 25-52, where the communication channel is between multiple parties);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella by using the incident severity threshold of Duran (Duran col. 18 lines 10-36) for the communication channel of Tanikella (Tanikella para [0156-157]), in order to determine which data feeds in a queue may provide additional information with respect to the incident (Duran col. 18 lines 10-36).
Regarding claim 9, Tanikella in view of Duran teaches:
The computer implemented method of claim 8, wherein the selected multi-party communication channel comprises a multi-party communication channel of the plurality of multi-party communication channels that is associated with a priority indicator (Tanikella para [0094], where a HQ virtual space is associated with other virtual spaces that are important to the user or relevant, indicating priority).
Regarding claim 10, Tanikella in view of Duran teaches:
The computer-implemented method of claim 8, wherein the abstractive context summary for the selected multi-party communication channel is retrieved from the summary storage location in response to the member event indication and based on whether the selected multi- party communication channel is associated with a priority indicator (Tanikella para [0099], [0130], where the documents are ranked, indicating priority, and where the summary is retrieved for the user).
Regarding claim 11, Tanikella in view of Duran teaches:
The computer-implemented method of claim 8, wherein the member event indication is at least one of (i) a member join event, (ii) a member rejoin event, or a (iii) delayed access event (Tanikella para [0010], [0013], [0134], [0142], where the user returns from being absent, and para [0095], where the user accesses the virtual space and the summary is presented).
Regarding claim 13, Tanikella in view of Duran teaches:
The computer-implemented method of claim 8, wherein each multi-party communication channel of the plurality of multi-party communication channels is generated in response to an incident alert and is associated with an incident identifier (Tanikella para [0011], where a virtual space or channel is created to resolve an incident, such as a bug, and para [0121], where the reporting of the incident is the alert, and where the ticket ID is the incident identifier).
Regarding claim 14, Tanikella in view of Duran teaches:
The computer-implemented method of claim 8, wherein inputting the plurality of communication data objects into the text summarization machine learning model to obtain the abstractive context summary comprises pre-processing the plurality of communication data objects to generate pre-processed communication data objects and providing the pre-processed communication data objects to the text summarization machine learning model, wherein the text summarization machine learning model is configured to generate the abstractive context summary based on the pre-processed communication data objects (Tanikella para [0048-49], where audio conversation data is processed to generate a transcript, and para [0052], where the transcripts are input to the machine learning model for summarization).
Regarding claim 15, Tanikella teaches:
A computer program product for generating context summaries of multi-party communication channels, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein (Fig. 1 elements 110, 136, para [0040], where computer readable media are used), the computer-readable program code portions configured to:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based on the multi- party communication channel identifier (para [0156-157], where the summarization component receives messages posted by different users);
generate, based on the plurality of communication data objects and utilizing a text summarization machine learning model, an abstractive context summary for the selected multi- party communication channel by inputting the plurality of communication data objects into the text summarization machine learning model to obtain the abstractive context summary (para [0158], where an abstractive summary of the messages is generated using a machine learning model);
store the abstractive context summary in a summary storage location associated with the plurality of multi-party communication channels (para [0052], where the summary document is stored);
receive, from a server associated with the selected multi-party communication channel, a member event indication indicating a member event occurrence of one or more member event occurrences associated with the selected multi-party communication channel (para [0010], [0013], where the user returning and requesting a summary document of the channel communications is the member event indication, and para [0078], [0084], where the components are associated with the server), wherein the member event indication comprises a multi-party communication channel identifier associated with the selected multi-party communication channel and a member profile identifier associated with the member event indication (Fig. 3C, para [0130], where the user selects the document affordance, where the interface includes the user and the channel, and para [0095], where the summary is associated with the user and channel);
in response to receiving the member event indication, retrieve, from the summary storage location, the abstractive context summary for the selected multi-party communication channel (para [0130], [0134], where the summary document is downloaded according to the user’s return from work); and
transmit the abstractive context summary for display on a client computing device associated with the member profile identifier (Fig. 3D, para [0131], where the summary is displayed in a window).
Tanikella does not teach:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold;
Duran teaches:
extract a plurality of communication data objects from a selected multi-party communication channel of a plurality of multi-party communication channels based at least in part on determining that an incident security level assigned to the selected multi- party communication channel exceeds an incident severity threshold (col. 18 lines 10-54, where an incident severity level exceeds a threshold, and data is collected based on the communication channel being associated with the incident security level above a severity threshold,, and col. 19 lines 25-52, where the communication channel is between multiple parties);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella by using the incident severity threshold of Duran (Duran col. 18 lines 10-36) for the communication channel of Tanikella (Tanikella para [0156-157]), in order to determine which data feeds in a queue may provide additional information with respect to the incident (Duran col. 18 lines 10-36).
Regarding claim 16, Tanikella in view of Duran teaches:
The computer program product of claim 15, wherein the selected multi-party communication channel comprises a multi-party communication channel of the plurality of multi-party communication channels that is associated with a priority indicator (Tanikella para [0094], where a HQ virtual space is associated with other virtual spaces that are important to the user or relevant, indicating priority).
Regarding claim 17, Tanikella in view of Duran teaches:
The computer program product of claim 15, wherein the abstractive context summary for the selected multi-party communication channel is retrieved from the summary storage location in response to the member event indication and based on whether the selected multi-party communication channel is associated with a priority indicator (Tanikella para [0099], [0130], where the documents are ranked, indicating priority, and where the summary is retrieved for the user).
Regarding claim 18, Tanikella in view of Duran teaches:
The computer program product of claim 15, wherein the member event indication is at least one of: (i) a member join event, (ii) a member rejoin event, or a (iii) delayed access event (Tanikella para [0010], [0013], [0134], [0142], where the user returns from being absent, and para [0095], where the user accesses the virtual space and the summary is presented).
Regarding claim 20, Tanikella in view of Duran teaches:
The computer program product of claim 15, wherein each multi-party communication channel of the plurality of multi-party communication channels is generated in response to an incident alert and is associated with an incident identifier (Tanikella para [0011], where a virtual space or channel is created to resolve an incident, such as a bug, and para [0121], where the reporting of the incident is the alert, and where the ticket ID is the incident identifier).
Claim(s) 5, 12, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanikella, in view of Duran, and further in view of Sotudeh Gharebagh et al. (US 2023/0259544 A1), hereinafter referred to as Sotudeh.
Regarding claim 5, Tanikella in view of Duran teaches:
The apparatus of claim 1,
Tanikella in view of Duran does not teach:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform.
Sotudeh teaches:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform (Sotudeh para [0027-28], where a language model having a transformer with attention is used for abstractive summarization, and para [0032], [0035], where self-attention is used to relate words with respect to other words).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella in view of Duran by using the attention of Sotudeh (Sotudeh para [0032]) on the text tokens of Tanikella in view of Duran (Tanikella para [0159]) to enable the model to relate a word to other words (Sotudeh para [0035]).
Regarding claim 12, Tanikella in view of Duran teaches:
The computer-implemented method of claim 8,
Tanikella in view of Duran does not teach:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform.
Sotudeh teaches:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform (Sotudeh para [0027-28], where a language model having a transformer with attention is used for abstractive summarization, and para [0032], [0035], where self-attention is used to relate words with respect to other words).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella in view of Duran by using the attention of Sotudeh (Sotudeh para [0032]) on the text tokens of Tanikella in view of Duran (Tanikella para [0159]) to enable the model to relate a word to other words (Sotudeh para [0035]).
Regarding claim 19, Tanikella in view of Duran teaches:
The computer program product of claim 15,
Tanikella in view of Duran does not teach:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform.
Sotudeh teaches:
wherein the text summarization machine learning model is an attention-based transformer text summarization machine learning model configured for an incident management platform to provide at least context of a multi-party communication channel associated with the incident management platform (Sotudeh para [0027-28], where a language model having a transformer with attention is used for abstractive summarization, and para [0032], [0035], where self-attention is used to relate words with respect to other words).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Tanikella in view of Duran by using the attention of Sotudeh (Sotudeh para [0032]) on the text tokens of Tanikella in view of Duran (Tanikella para [0159]) to enable the model to relate a word to other words (Sotudeh para [0035]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2014/0067377 A1 para [0064] teaches channels with importance levels above a threshold, as well as providing event summaries; US 7,034,691 B1 col. 82 line 58 – col. 83 line 11 teaches providing alert summaries based on priority thresholds.
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 BRYAN S BLANKENAGEL whose telephone number is (571)270-0685. The examiner can normally be reached 8:00am-5:30pm.
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, Richemond Dorvil can be reached at 571-272-7602. 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.
/BRYAN S BLANKENAGEL/Primary Examiner, Art Unit 2658