DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. The IDSs filed on 04/19/2024 and 11/06/2025 are considered and entered into the application file.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
3. Claims 1-5, 7-11 and 13 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by
LIU et al (US 20240256615 A1). Note: the publication (US 20240256615 A1) claims priority to US Provisional No. 63/442,447, filled on Jan 31, 2023.
As per claim 1, LIU discloses an apparatus (computing system Fig. 1, 100 ) for summarizing information using a generative artificial intelligence model (generative model 112, Fig. 1) , the apparatus comprising:
one or more processors (processor 106); and
a memory (memory 108) provided for storing instructions executed by the one or more processors, wherein the one or more processors are configured to:
generate an answer sentence on a search term input from a user, using a first generative artificial intelligence model pre-trained to summarize and organize information that the user desires on the basis of information existing on the Internet ([0012] The search engine identifies information based upon the query (such as an instant answer that provides the information requested in the query) and provides such information to the generative model as part of a prompt used by the generative model to generate output. [0076] In another example, the first generative model 1010 is trained for a first topic, where the first generative model 1010 is trained based upon content from webpages labeled as corresponding to the first topic; the nth generative model 1012 is trained for a second topic, where the nth generative model 1012 is trained based upon content from webpages labeled as corresponding to the nth topic). [0100] (A4) In some embodiments of the method of at least one of (A1)-(A3), the output comprises a textual response to the input set forth by the user of the client computing device.
generate an answer image based on at least one of the search term or the answer sentence using a second generative artificial intelligence model pre-trained to generate an image corresponding to an input sentence ([0049] While the examples referenced above have referred to the generative model 112 generating text, it is understood that the generative model 112 can generate images or other multimedia; further, the generative model 112 can request that the search engine 110 perform visual searches (e.g., provide the search engine 110 with an image and request that the search engine 110 identify similar images. [0051] an image 304 identified by the search engine 110 as being relevant to the query, supplemental content 306 and 308 identified as being relevant to the query, and so forth. and
generate answer content including the answer sentence and the answer image ([0012] The generative model generates human-comprehensible output (such as text, an image, video) that is based upon content of the email and the query, such that the generative model provides the user with the requested information. Also see [0087] and Fig. 3)).
As per claim 2, LIU further discloses that the apparatus of claim 1, wherein the one or more processors are configured to manage feedback information by the user on at least one of the answer sentence, the answer image, or the answer content ([0011] The generative model is additionally able to generate queries and provide the queries to the search engine, whereupon the search engine identifies search results based upon the queries and provides information based upon the search results to the generative model for inclusion in a prompt. Thus, for instance, the generative model generates a query (based upon received user input) and provides the search engine with the generated query, and the search engine identifies additional content based upon the query generated by the generative model. [0096]The method also includes generating, by the generative model, a second query based upon the second input set forth by the user. The method further includes providing the second query to a search engine and receiving, by the generative model and from the search engine, second content identified by the search engine based upon the second query).
As per claim 3, LIU further discloses that the apparatus of claim 2, wherein the one or more processors are configured to score the feedback information, classify the scored feedback as a personal preference of the user, and reflect the scored feedback in generating at least one of the answer sentence, the answer image, or the answer content ([0009The generative model uses the additional context to provide relevant output and to further provide output that has a higher likelihood of being factually correct when compared with the generative model being provided with only the query. [0078] The classifier 1008 is configured to assign a class label from amongst several possible class labels to input received from the client computing device 1002; a generative model from amongst the generative models 1010-1012 is selected based upon the class label, and the selected generative model is provided with the input upon being selected. For instance, the classifier 1008 is employed to select appropriate generative models such that outputs are of high quality yet computing resources needed to generate the outputs are reduced. Also see [0087]).
As per claim 4, LIU further discloses that the apparatus of claim 2, wherein the one or more processors are configured to manage the feedback information in synchronization with a search term pattern of the user ([0009] In addition, the search engine can provide at least some of the information identified by the search engine to the generative model; the search engine can provide such information to the generative model immediately upon identifying the search results or in response to receipt of an indication that the user is requesting to interact with the generative model. In an example, the prompt used by the generative model to generate output can include the query and the information identified by the search engine; the generative model can then generate output based upon the prompt. The generative model uses the additional context to provide relevant output and to further provide output that has a higher likelihood of being factually correct when compared with the generative model being provided with only the query. Also see [0060]).
As per claim 5, LIU further discloses that the apparatus of claim 4, wherein the one or more processors are configured to recommend one of plurality of pre-stored feedback information synchronized with a search term pattern similar to the search term pattern of the user ([0034] the instant answers data store 116 includes an index of instant answers that are indexed by queries, query terms, and/or terms that are semantically similar or equivalent to the queries and/or query terms. For example, the instant answer “2.16 meters” can be indexed by the query “height of Shaquille O'Neal” (and queries that are semantically similar or equivalent, such as “how tall is Shaquille O'Neal”)). Also see [0037]).
As per method claims 7-11, these method claims include limitations similar to that of apparatus claims 1-5, respectively, thus, the method claims are also rejected under similar citations given the apparatus claims.
As per a non-transitory computer-readable medium claim 13, LIU further discloses (memory 108, FIG. 1). The claim is rejected under similar citations given to the method claim 7.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
4. Claims 6 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over LIU in view of Ezaki et al ( US 20020078356 A1).
As per claims 6 (method) and 12 (apparatus), although LIU discloses a methodology 1100 (Fig. 11) for generating, by a generative model, output based content received from a search engine but the output content, such as the image does not include a watermark as recited in the claim.
[0025] Ezaki, on the other hand, discloses an electronic watermark inspecting unit operable to inspect electronic watermarks inserted into the contents and to produce inspection results.
Before effective filling date of the invention, it would have been obvious to a person of ordinary skill in the art to combine the teaching of Ezaki with LIU because electronic watermarking can be used to screen such that no more copies can be made from contents illegitimately distributed or from contents already copied once (or a predetermined number of times) (see Ezaki, [0009]).
Therefore, it would have been obvious to combine Ezaki with LIU to obtain the invention as specified in claims 6 (apparatus) and 12 (method).
Conclusion
5. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TADESSE HAILU whose telephone number is (571)272-4051; and the email address is Tadesse.hailu@USPTO.GOV. The examiner can normally be reached Monday- Friday 9:30-5:30 (Eastern time).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bashore, William L. can be reached (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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/TADESSE HAILU/ Primary Examiner, Art Unit 2174