Prosecution Insights
Last updated: October 25, 2026
Application No. 18/755,221

CONTENT DELIVERY USING DISTRIBUTED LEDGER AND AI-BASED TRANSCODING TECHNOLOGIES

Non-Final OA §103
Filed
Jun 26, 2024
Priority
Sep 24, 2020 — provisional 63/082,704 +1 more
Examiner
PHAM, KHANH B
Art Unit
2166
Tech Center
2100 — Computer Architecture & Software
Assignee
CenturyLink Intellectual Property LLC
OA Round
3 (Non-Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
11m
Est. Remaining
88%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
621 granted / 858 resolved
+17.4% vs TC avg
Strong +16% interview lift
Without
With
+15.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
27 currently pending
Career history
897
Total Applications
across all art units

Statute-Specific Performance

§101
9.3%
-30.7% vs TC avg
§103
40.4%
+0.4% vs TC avg
§102
30.5%
-9.5% vs TC avg
§112
9.3%
-30.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 858 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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114 was filed in this application after a decision by the Patent Trial and Appeal Board, but before the filing of a Notice of Appeal to the Court of Appeals for the Federal Circuit or the commencement of a civil action. Since this application is eligible for continued examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 9/30/2026 has been entered. 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. Claims 1-2, 5-7, 11-13, 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Zou (US 2020/0242215 A1, Applicant’ submitted IDS filed 7/07/2024), hereinafter “Zou”, and in view of Singi et al. (US 2020/0252219 A1), hereinafter “Singi”. As per claim 1, Zou teaches a system comprising: at least one processor, memory, operatively connected to the at least one processor and storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations comprising: “receiving, from a content source, an indication of content” at [0031]; (Zou teaches the transaction node is configured to upload a target image (i.e., “content”) into a blockchain) “wherein the indication of content further comprises metadata associated with the content” at [0011]; (Zou teaches uploading the transaction price of the target image into the blockchain. The transaction price of the target image is metadata associated with the image) “storing the content in a data store” at [0036]; (Zou teaches the target image is added into an image transaction pool (i.e., “a data store”)) “generating a content hash based on the content, wherein the metadata is not used to generate the content hash” at [0013], [0038]; (Zou teaches generating image hash value of the target image. Note that Zou teaches uploading both target image and transaction price of the target image into the blockchain, but only the target image is used to generate image hash value) “storing the content hash… as a content record in a distributed ledger” at [0014], [0038]; (Zou teaches the image hash value is stored as copyright certificate of the target image, maintained by the blockchain (i.e., “distributed ledger”)) “receiving, from a client device, a request for the content” at [0042]-[0046]; (Zou teaches the transaction request triggers a designated smart contract corresponding to the target image to complete a transaction of the target image, and to trigger the designate smart contract to upload, after the transaction is completed, a transaction record corresponding to the transaction into the blockchain. The designated smart contract may further upload, after each image transaction is completed, a transaction record corresponding to the transaction into the blockchain, so that other nodes (e.g., a judicial agency node) in the blockchain confirm and record this transaction record for evidence collection when transaction disputes occur later) “providing, in response to the request, at least a part of the content from the data store” at [0061]. (Zou teaches the images obtained by the transaction node from the image transaction pool may be displayed to the user on a transaction platform) Zou does not teach “generating, separate from the content hash, a metadata hash based on the metadata”, “storing the metadata hash as a content record in a distributed ledger” as claimed. However, Singi teaches an identity generation platform for generating a verification composite identity for software application, including the steps of generating content hash based on the content and a separate metadata hash based on the metadata and storing the content hash and the metadata hash on a smart contract-based blockchain at [0016]-[0019]. Thus, it would have been obvious to one of ordinary skill in the art to combine Singi with Zou teaches so that “the identity generation platform may identify discrepancies in large, complex software applications, thereby improving the software development process, reducing scheduling or cost overruns, reducing security vulnerabilities, reducing computing resources associated with identifying discrepancies, and/or the like. Further, the identity generation platform may automatically resolve an identified discrepancy by replacing an altered artifact of the software application with an unaltered version of the artifact. In this way, identity generation platform enables automated software application version management and issue resolution”, as suggested by Singi at [0014]. As per claim 2, Zou and Singi teach the system of claim 1 discussed above. Zou also teaches: “generating a smart contract associated with the content, wherein the smart contract is associated with a trigger, identifying the trigger based on the request for the content from the client device; and in response to identifying the trigger, executing the smart contract to generate a new record in the distributed ledger” at [0042]-[0046] (Zou teaches the transaction request triggers a designated smart contract corresponding to the target image to complete a transaction of the target image, and to trigger the designate smart contract to upload, after the transaction is completed, a transaction record (i.e., “a new record”) corresponding to the transaction into the blockchain. The designated smart contract may further upload, after each image transaction is completed, a transaction record corresponding to the transaction into the blockchain, so that other nodes (e.g., a judicial agency node) in the blockchain confirm and record this transaction record for evidence collection when transaction disputes occur later) As per claim 5, Zou and Singi teach the system of claim 1 discussed above. Zou also teaches: wherein “at least a part of the metadata is stored in the content record” at [0011]. As per claim 6, Zou and Singi teach the system of claim 1 discussed above. Zou also teaches: wherein “at least a part of the metadata is stored in a metadata repository and associated with the content hash” at [0011]. As per claim 7, Zou teaches a method for generating a smart contract for content of a network comprising: “receiving, from a content source, an indication of content” at [0031]; (Zou teaches the transaction node is configured to upload a target image (i.e., “indication of content”) into a blockchain) “wherein the indication of content further comprises metadata associated with the content” at [0011]; (Zou teaches uploading the transaction price of the target image into the blockchain. The transaction price of the target image is metadata associated with the image) “generating a smart contract associated with the content, wherein the smart contract is associated with a trigger” at [0042]-[0046]; (Zou teaches if the transaction node selects the target image from the image transaction pool for transaction, the transaction node sends, based on the target image, a transaction request to the blockchain, so as to trigger a designated smart contract corresponding to the target image to complete a transaction of the target image, and to trigger the designate smart contract to upload, after the transaction is completed, a transaction record corresponding to the transaction into the blockchain) “storing the smart contract in a distributed ledger” at [0042]-[0045]; (Zou teaches storing the smart contract in the blockchain) “receiving, from a client device, a request for the content” at [0045]; (Zou teaches if the transaction node selects the target image from the image transaction pool for transaction, the transaction node sends, based on the target image, a transaction request to the blockchain) “identifying the trigger based on the request for the content from the client device, in response to identifying the trigger, executing the smart contract to generate a new record in the distribute ledger” at [0045]-[0046]; (Zou teaches the transaction request triggers a designated smart contract corresponding to the target image to complete a transaction of the target image, and to trigger the designate smart contract to upload, after the transaction is completed, a transaction record (i.e., “a new record”) corresponding to the transaction into the blockchain. The designated smart contract may further upload, after each image transaction is completed, a transaction record corresponding to the transaction into the blockchain, so that other nodes (e.g., a judicial agency node) in the blockchain confirm and record this transaction record for evidence collection when transaction disputes occur later) “providing, in response to the request, at least a part of the content” at [0061]. (Zou teaches the images obtained by the transaction node from the image transaction pool may be displayed to the user on a transaction platform) “generating a content hash based on the content, wherein the metadata is not used to generate the content hash” at [0013], [0038]; (Zou teaches generating image hash value of the target image. Note that Zou teaches uploading both target image and transaction price of the target image into the blockchain, but only the target image is used to generate image hash value) “storing the content hash…as a content record in a distributed ledger” at [0014], [0038]; (Zou teaches the image hash value is stored as copyright certificate of the target image, maintained by the blockchain (i.e., “distributed ledger”)) Zou does not teach “generating, separate from the content hash, a metadata hash based on the metadata”, “storing the metadata hash as a content record in a distributed ledger” as claimed. However, Singi teaches an identity generation platform for generating a verification composite identity for software application, including the steps of generating content hash based on the content and a separate metadata hash based on the metadata and storing the content hash and the metadata hash on a smart contract-based blockchain at [0016]-[0019]. Thus, it would have been obvious to one of ordinary skill in the art to combine Singi with Zou teaches so that “the identity generation platform may identify discrepancies in large, complex software applications, thereby improving the software development process, reducing scheduling or cost overruns, reducing security vulnerabilities, reducing computing resources associated with identifying discrepancies, and/or the like. Further, the identity generation platform may automatically resolve an identified discrepancy by replacing an altered artifact of the software application with an unaltered version of the artifact. In this way, identity generation platform enables automated software application version management and issue resolution”, as suggested by Singi at [0014]. As per claim 11 Zou and Singi teach the system of claim 7 discussed above. Zou also teaches: wherein “the content is a subpart of streaming content from the content source” at [0003]-[0004]. Claims 12-13, 16-17 recite similar limitations as in claims 1-2, 5-6 and are therefore rejected by the same reasons. Claims 3, 9 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Zou and Singi as applied to claims 1-2, 5-7, 11-13, 16-17 above, and further in view of Crowell (US 2022/0083507 A1, Applicant’s submitted IDS filed 7/07/2025), hereinafter “Crowell”. As per claim 3, Zou and Singi teach the system of claim 1 discussed above. Zou does not explicitly teach: “receiving, from the client device, a validation request comprising a second content hash; determining that the content is validated when the first content hash matches the second content hash; and in response to the validation request, providing an indication that the content is validated” as claimed. However, Crowell teaches a similar method for storing content and content hash in a distributed ledger, including the steps of: “receiving, from the client device, a validation request comprising a second content hash; determining that the content is validated when the first content hash matches the second content hash; and in response to the validation request, providing an indication that the content is validated” at [0085]-[0087] and Fig. 4. Thus, it would have been obvious to one of ordinary skill in the art to combine Crowell with Zou’s teaching in order to determine whether the content is unmodified and trusted based on the matching hash values. Claims 9, 14 recite similar limitations as in claim 3 and are therefore rejected by the same reasons. Response to Arguments Applicant’s arguments filed 9/30/2026 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 Examiner's Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. Any inquiry concerning this communication or earlier communications from the examiner should be directed to KHANH B PHAM whose telephone number is (571)272-4116. The examiner can normally be reached Monday - Friday, 8am to 4pm. 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, Sanjiv Shah can be reached at (571)272-4098. 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. /KHANH B PHAM/Primary Examiner, Art Unit 2166 October 8, 2026
Read full office action

Prosecution Timeline

Show 14 earlier events
Feb 17, 2026
Response after Non-Final Action
Apr 29, 2026
Response after Non-Final Action
Jul 21, 2026
Response after Non-Final Action
Jul 30, 2026
Response after Non-Final Action
Jul 30, 2026
Response after Non-Final Action
Sep 30, 2026
Request for Continued Examination
Oct 07, 2026
Response after Non-Final Action
Oct 09, 2026
Non-Final Rejection mailed — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
72%
Grant Probability
88%
With Interview (+15.5%)
3y 3m (~11m remaining)
Median Time to Grant
High
PTA Risk
Based on 858 resolved cases by this examiner. Grant probability derived from career allowance rate.

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