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 .
1. This communication is responsive to the Amendment filed 11/24/2025.
2. Claims 1-9 and 17-27 are pending in this application. Claims 1, 17 and 21 are independent claims. In the instant Amendment, claim 6 was amended, claims 10-16 were canceled and claims 21-27 were added. Claims 10-16 withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected species, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on 11/24/2025. The restriction is made Final. This action is made Non-Final.
Claim Rejections - 35 USC § 102
3. 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
4. Claim(s) 1-9 and 17-27 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Karpman et al (“Karpman” 63/487,552)(US 11,995,803).
Regarding claim 1, Karpman discloses a method comprising:
identifying, by a content generation apparatus, a theme (see paragraph [0054]; e.g., image style), an audience (see paragraph [0065]; e.g., output to client device that submitted request), and an input image of a product (see paragraph [0009]; e.g., locating images from web page);
generating, for the audience, an output image depicting the product and the theme based on the input image using an image generation model that is trained to generate images consistent with a brand (see paragraph [0011]; e.g., “Once trained, the system can therefore implement, leverage, and/or execute the text-to-image diffusion model as part of an image generation platform that enables users to generate custom, high-quality images that align with (text) descriptions, image style selections, and other preferences within seconds.”; see paragraphs [0028] and [0036]; e.g., “based on color”);
generating text based on the product and the theme using a text generation model (see paragraphs [0017]-[0020]; e.g. transformer; also see paragraphs [0013] and [0040]; e.g., “generate text captions”); and
generating, by a content generation component, custom content consistent with the brand and the theme based on the output image and the text (see paragraph [0011]; e.g., “Once trained, the system 100 can therefore implement, leverage, and/or execute the text-to-image diffusion model 112 as part of an image generation platform that enables users to generate custom, high-quality images that align with (text) descriptions, image style selections, and other preferences within seconds.”).
Regarding claim 2, Karpman discloses obtaining, by an image selection model, a plurality of images of the product; and selecting the input image from the plurality of images using the image selection model (see paragraph [0013]; e.g., “access a set of training images”; see fig 2, M110).
Regarding claim 3, Karpman discloses computing, by the image selection model, a coverage score; and computing a compellingness score using the image selection model, wherein the input image is selected based on the coverage score and the compellingness score (see paragraphs [0028]-[0030] and [0062]-[0063]; e.g., quality and confidence scores; rank images based on scores).
Regarding claim 4, Karpman discloses identifying, by the image selection model, a product website, wherein the plurality of images is obtained from the product website (see paragraph [0009]; e.g., locating images from web page).
Regarding claim 5, Karpman discloses identifying, by the content generation component, a document template, wherein the custom content is generated based on the document template (see paragraphs [0052]-[0054]; e.g., pre-set style).
Regarding claim 6, Karpman discloses wherein: the image generation model comprises a diffusion model (see paragraph [0009]; e.g., “diffusion model”) and the content generation component comprises a transformer model (see paragraphs [0017]-[0020]; e.g. transformer; also see paragraphs [0013] and [0040]; e.g., “generate text captions”).
Regarding claim 7, Karpman discloses identifying, by a moderation model, brand guidelines; and determining, by the moderation model, whether the custom content is consistent with the brand based on the brand guidelines (see paragraph [0059]; e.g., “content guidelines”).
Regarding claim 8, Karpman discloses wherein: the output image comprises a custom background based on the theme (see paragraph [0054]; e.g., image style).
Regarding claim 9, Karpman discloses wherein: the text comprises a subject line, a catchphrase, a product summary, or any combination thereof (see paragraphs [0017]-[0020]; e.g. transformer; also see paragraphs [0013] and [0040]; e.g., “generate text captions”).
Claim 17 is similar in scope to claim 1 and is therefore rejected under similar rationale.
Regarding claim 18, Karpman discloses a content generation component configured to generate custom content consistent with the brand and the theme based on the output image and the text (see paragraph [0011]; e.g., “Once trained, the system 100 can therefore implement, leverage, and/or execute the text-to-image diffusion model 112 as part of an image generation platform that enables users to generate custom, high-quality images that align with (text) descriptions, image style selections, and other preferences within seconds.”).
Regarding claim 19, Karpman discloses an image selection model configured to select an input image of the product from a plurality of images, wherein the output image is generated based on the input image (see paragraph [0013]; e.g., “access a set of training images”; see fig 2, M110).
Regarding claim 20, Karpman discloses a moderation model configured to identify brand guidelines and determine whether the text or the image is consistent with the brand based on the brand guidelines (see paragraph [0059]; e.g., “content guidelines”).
Claims 21-27 are similar in scope to claims 1-7, respectively, and are therefore rejected under similar rationale.
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kumari et al (US 2024/0185588).
6. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RASHAWN N TILLERY whose telephone number is (571)272-6480. The examiner can normally be reached M-F 9:00a - 5:30p.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William L Bashore can be reached at (571) 272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RASHAWN N TILLERY/ Primary Examiner, Art Unit 2174
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