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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/03/2024 has been made record of and considered by the examiner.
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.
Claim(s) 1-2, 5-6, and 16-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental processes (concepts performed in a human mind, including as an observation, evaluation, judgment, opinion, organizing human activity and/or mathematical concepts and calculations). The independent claims 1 and 16 recites a method and a system for image difference captioning. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the independent claims 1 and 16 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Independent claims 1 and 16 are directed to a method for image difference captioning.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental processes and/or mathematical concepts (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Independent claims 1 and 16 comprise mental processes and/or mathematical concepts that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding independent claim(s) 1 and 16, the limitations recite:
in response to the image difference captioning request, generating text inputs from the series of versions of the digital image and the one or more edit descriptions (The step of falls into the “mental processes” grouping because it can be performed in the human mind as an observation, evaluation, judgement or opinion. A person could think of/write down labels to describe versions.); and
generating, from the text inputs utilizing a large language model, a caption prediction that indicates a difference between a first version of the digital image of the series of versions of the digital image and a last version of the digital image of the series of versions of the digital image. The step of falls into the “mental processes” grouping because it can be performed in the human mind as an observation, evaluation, judgement or opinion. A person could view two images and think of/write down differences between the images. The use of a LLM would not negate the mental nature of this limitation.)
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could mentally manually annotate the differences between a series of images. The mere nominal recitation that the various steps are being executed by a processor, client device, non-transitory CRM does not take the limitations out of the mental process and/or mathematical concepts groupings. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Independent claims 1 and 16 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
Independent claims 1 and 16 discloses an processors, client device, non-transitory CRM; receiving, from a client device, an image difference captioning request comprising a series of versions of a digital image with a series of manipulations applied to the series of versions of the digital image; accessing one or more edit descriptions for one or more of the series of manipulations; which are generic computer components and/or insignificant pre/post-solution extra activity that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea in a method or system.
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Independent claim(s) 1 and 16 do not recite any additional elements that are not well-understood, routine or conventional. The use of a generic computer elements are routine, well-understood and conventional process that is performed by computers.
Thus, since independent claims 1 and 16 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that independent claims 1 and 16 are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2, 5, and 6: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) fall into the mental processes grouping of abstract ideas.
Regarding claim 2: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) fall into the mathematical concepts grouping of abstract ideas.
Regarding claims 17, the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) is/are generic computer components.
Claim Objections
Claim 9 is objected to because of the following minor informalities: Line 1 of claim 1 recites “The computer-implemented method of claim 8, further comprises.” The examiner respectfully suggests correcting to: “The computer-implemented method of claim 8, further comprising.” Appropriate correction is required.
Claim 16 is objected to because of the following informalities: Line 7 of claim 16 recites “a second versions”. The plurality of versions would introduce ambiguity into the claim. The examiner is reading “versions” as a typo, and should be corrected to “version”. Appropriate correction is required.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3-4, 6-7, 10-14, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Guo (‘CLIP4IDC’), in further view of Zhang (‘MagicBrush’), in further view of Liu (‘Visual Instruction Tuning’), and in further view of Cho (US 2023/0153522 A1).
Consider claims 1, 10, and 16, Guo discloses: receive, (FIG. 2; Image 1, 2; T: the brown matte cube changed to green, 2.3 IDC-specific Adaptation);
[claim 1: accessing one or more edit descriptions for one or more of the series of manipulations (Guo Section 2);]
generate, utilizing a vision transformer, a first group of visual features for a first version of the digital image of the series of versions of the digital image (FIG. 2; Intra Encoder, Multi-layer transformer);
transform, utilizing a neural network layer, the first group of visual features to a first group of text inputs for compatibility in an embedding space of a large language model (2.3 IDC-specific Adaptation);
[Claim 1: in response to the image difference captioning request, generating text inputs from the series of versions of the digital image and the one or more edit descriptions (FIG. 2; the brown matte cube changed to green; the brown … green; 2.3, 2.4); and]
generate additional text inputs from the one or more edit descriptions for one or more of the series of manipulations (2.3, 2.4 Captioning); and
[Claim 16: generating, utilizing the vision transformer, a second group of visual features corresponding to a second versions of the digital image of the series of versions of the digital image (FIG. 2; Image 2; 2.3, 2.4); ]
generate, (FIG. 2; the brown matte cube changed to green).
[Claim 16: and providing the caption prediction that indicates the difference between the first version of the digital image and the last version of the digital image of the series of versions of the digital image (FIG. 2; the brown matte cube changed to green).]
Guo fails to explicitly disclose:
one or more memory devices; and
one or more processors;
[Claim 16: A non-transitory computer-readable medium storing executable instructions which, when executed by at least one processing device, cause the at least one processing device to perform operations comprising:]
receiving, from a client device, an image difference captioning request comprising a series of versions of a digital image with a series of manipulations applied to the series of versions of the digital image;
generate, [Claim 16: utilizing a large language model,] from the first group of text inputs and the additional text inputs utilizing the large language model, a caption prediction that indicates a difference between the first version of the digital image of the series of versions of the digital image and a last version of the digital image of the series of versions of the digital image.
[Claim 16: and providing the caption prediction to the client device.]
In related art, Zhang discloses: receive, (E.1 Edit Instruction) for one or more of the series of manipulations (Zhang FIG. 5 Shows a multi-turn editing scenario in which the original image is modified to make the subject angry, then dressed in a dinner jacket, then changed the item the subject is holding; 3.1 Problem Definition; “In multi-turn scenario, models take the source image and a sequence of textual instructions to generate intermediate images and final image.”);
generate, utilizing a vision transformer, a first group of visual features for a first version of the digital image of the series of versions of the digital image (Zhang C Implementation Details);
generate additional text inputs from the one or more edit descriptions for one or more of the series of manipulations (Zhang C.4; To transform the edit instruction to global description and local description required by other baselines; 3.1; E.1); and
generate, [Claim 16: utilizing a large language model,] from the first group of text inputs and the additional text inputs utilizing the large language model, a caption prediction that indicates a difference between the first version of the digital image of the series of versions of the digital image and a last version of the digital image of the series of versions of the digital image (Zhang FIG. 5; Section 3).
[Claim 16: and providing the caption prediction that indicates the difference between the first version of the digital image and the last version of the digital image of the series of versions of the digital image (Zhang E.1 Global Description).]
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the multi-turn instruction editing of Zhang into the image difference captioning method of Guo to identify and apply manipulations to a series of versions (Zhang FIG. 5).
In related art, Liu discloses: generate, utilizing a vision transformer, a first group of visual features for a first version of the digital image of the series of versions of the digital image (Liu FIG. 1 XV, ZV, HV);
transform, utilizing a neural network layer, the first group of visual features to a first group of text inputs for compatibility in an embedding space of a large language model (Liu FIG. 1; 4.1; “we apply a trainable projection matrix W to convert Zv into language embedding tokens Hv, which have the same dimensionality as the word embedding space in the language model”);
generate additional text inputs from the one or more edit descriptions for one or more of the series of manipulations (Liu FIG. 1; 4.1; Hq); and
generate, [Claim 16: utilizing a large language model,] from the first group of text inputs and the additional text inputs utilizing the large language model, a caption prediction (Liu FIG. 1; Language Response Xa);
and providing the caption prediction (Liu FIG. 1; Language Response Xa).]
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the explicit LLM of Liu into the image difference captioning method of Guo, as modified by Zhang, to effectively leverage the capabilities of both the LLM and visual model (Liu 4.1). Liu additionally discloses multi-turn sequencing (Liu 4.2).
In related art, Cho explicitly discloses the general image captioning structure: one or more memory devices (¶34-35); and
one or more processors configured to cause the system (Cho ¶34-35) to:
[Claim 16: A non-transitory computer-readable medium storing executable instructions which, when executed by at least one processing device, cause the at least one processing device to perform operations (Cho ¶34) comprising:]
receive, from a client device (Cho ¶32; User device 105), [claim 1: an image (Cho ¶30; “a system or method based on the present disclosure may be used to return an image and caption to a user in response to receiving a user query”)];
[Claim 16: and providing the caption prediction … to the client device (Cho ¶30; “a system or method based on the present disclosure may be used to return an image and caption to a user in response to receiving a user query”).]
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the explicit structure of Cho into the image difference captioning method of Guo, as modified by Zhang and Liu, to support providing a caption in response to a user request (Cho ¶30-32).
Consider claim 3, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention further comprising:
generating, utilizing a vision transformer, visual features of the series of versions of the digital image (Guo FIG. 2; Section 2; Liu Section 4; Zhang 3, FIG. 5); and
transforming, utilizing a neural network layer, the visual features into the text inputs for compatibility in an embedding space of the large language model (Guo FIG. 2; Section 2; Liu Section 4).
Consider claim 4, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention further comprising: extracting, utilizing the vision transformer, a plurality of image patches from the first version of the digital image of the series of versions of the digital image (Guo Section 2; Appendix B); and
generating, utilizing a combination neural network layer, the visual features by combining visual tokens corresponding to the plurality of image patches (Guo FIG. 2; Section 2).
Consider claim 6, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention further comprising:
generating, utilizing a vision transformer, a first group of visual features from the first version of the digital image (Guo Section 2; Zhang Section 3; Liu 4.1); and
generating, utilizing the vision transformer, a second group of visual features from an intermediate version of the digital image of the series of versions of the digital image (Guo Section 2; Zhang Section 3; Liu 4.1).
Consider claim 7, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention further comprising:
transforming, utilizing a neural network layer, the first group of visual features and the second group of visual features into the text inputs for the large language model (Guo Section 2; Liu Section 4); and
generating, utilizing the large language model, the caption prediction from the text inputs of the first group of visual features and the second group of visual features (Guo Section 2; Liu Section 4; Zhang 3.3).
Consider claim 11, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein the one or more processors are configured to cause the system to:
generate, for the first version of the digital image of the series of versions of the digital image, a plurality of image patches (Guo FIG. 2, Section 2; Liu 4);
generate, utilizing the vision transformer, visual tokens corresponding to the plurality of image patches (Guo FIG. 2, Section 2; Liu 4); and
generate, utilizing a concatenation layer, the first group of visual features by combining the visual tokens (Guo FIG. 2, Section 2; Liu 4).
Consider claim 12, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein the one or more processors are configured to cause the system to transform the first group of visual features to the first group of text inputs in the embedding space of the large language model by utilizing a linear projection layer or a multi-layer perceptron (Guo Section 3; Liu 4.1).
Consider claim 13, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein the one or more processors are configured to cause the system to generate the additional text inputs from the one or more edit descriptions based on a type of manipulation and parameters of one or more of the series of manipulations (Zhang 3.3, Appendix E.1; Liu 4.1).
Consider claim 14, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein the one or more processors are configured to cause the system to generate the caption prediction by utilizing context from a plurality of intermediate versions of the series of versions of the digital image (Guo Section 2; Zhang Section 3; Liu Section 4).
Consider claim 17, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein the operations further comprise accessing one or more edit descriptions for one or more of a series of manipulations applied to the series of versions of the digital image (Guo Section 2; Zhang Section 3, Appendix E.1; Liu 4.1).
Consider claim 18, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention, wherein the operations further comprise: generating, utilizing a neural network layer, text inputs from the first group of visual features and the second group of visual features (Guo Section 2; Zhang Section 3; Liu Section 4);
generating additional text inputs from the one or more edit descriptions (Guo Section 2; Zhang Section 3, Appendix E.1; Liu Section 4); and
generating, utilizing the large language model to process the text inputs and the additional text inputs, the caption prediction (Guo Section 2; Zhang Section 3; Liu Section 4).
Claim(s) 2 and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Guo, in view of Zhang, Liu, and Cho, as applied to claims 1, 3-4, 6-7, 10-14, and 16-18 above, and further in view of Sun (‘The STVchrono Dataset: Towards Continuous Change Recognition in Time’).
Consider claim 2, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein accessing the one or more edit descriptions comprises:
determining a type of manipulation and parameters of one or more of the series of manipulations (Guo FIG. 2, Section 2; Zhang E.1); and
identifying a binary mask for applying one or more of the series of manipulations (Zhang 3.1, C.2).
In related art, Sun further supports identifying a binary mask for applying one or more of the series of manipulations (Sun FIG. 3, Section 4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the masking of Sun into the IDC method of Guo, as modified by Zhang, Liu, and Cho, “to track change instances (e.g. roads, trees, or buildings) in sequential images (Sun Section 4).”
Consider claim 5, Guo, as modified by Zhang, Liu, and Cho, discloses the claimed invention wherein:
receiving the series of versions of the digital image comprises receiving the first version of the digital image, the last version of the digital image, and a plurality of intermediate versions of the digital image (Zhang Section 3.1); and
Guo, as modified by Zhang, Liu, and Cho, fails to explicitly disclose generating the caption prediction comprises utilizing context of the plurality of intermediate versions of the digital image to generate the caption prediction that indicates the difference between the first version of the digital image and the last version of the digital image.
In related art, Sun discloses generating the caption prediction comprises utilizing context of the plurality of intermediate versions of the digital image to generate the caption prediction that indicates the difference between the first version of the digital image and the last version of the digital image (Sun Sections FIGs. 3, Table 2; 3.2-3.4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the utilization of intermediate versions of Sun into the IDC method of Guo, as modified by Zhang, Liu, and Cho, “to track change instances (e.g. roads, trees, or buildings) in sequential images (Sun Section 4).”
Allowable Subject Matter
Claims 8-9, 15, and 19-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten (1) in independent form including all of the limitations of the base claim and any intervening claims, and (2) to overcome other outstanding rejections.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Yao, “Image difference captioning with pre-training and contrastive learning.”
Brooks, “Instructpix2pix: Learning to follow image editing instructions.”
Hu, “OneDiff: A Generalist Model for Image Difference Captioning.”
Jiang, “Mantis: Interleaved multi-image instruction tuning."
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASHLEY HYTREK whose telephone number is (703)756-4562. The examiner can normally be reached M-F 9:00-5:00.
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, Steve Koziol can be reached at (408)918-7630. 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.
/ASHLEY HYTREK/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
Prosecution Insights