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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Objections
Claims 8 and 17 are objected to because of the following informalities: each of the claims recites identifying “complimentary” components. This is a typographical error, and should read “complementary” Appropriate correction is required.
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.
1. Claims 1-20 are 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.
Claims 1-20 are directed to determining product purchase alternatives, which is considered a commercial interaction. Commercial interactions fall within a subject matter grouping of abstract ideas which the Courts have considered ineligible (Certain methods of organizing human activity). The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea).
Under step 1 of the Alice/Mayo framework, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claim 1-9 recite a method and at least one step. Claims 10-18 recite a computer program product comprising one or more computer readable storage media explicitly defined by the disclosure as non-transitory. Claims 19-20 recite a system comprising a processor set and one or more computer readable storage media. Therefore, the claims are each directed to one of the four statutory categories of invention (process, manufacture, apparatus).
Under step 2A of the Alice/Mayo framework, it must be considered whether the claims are “directed to” an abstract idea. That is, whether the claims recite an abstract idea and fail to integrate the abstract idea into a practical application.
Regarding independent claim 1, the claim sets forth a process in which product purchase alternatives are determined for a consumer in the following limitations:
Identifying a replacement component for a device component;
performing, using a regression model, predictive analysis on user input data to identify a root cause that the device component would need to be replaced;
generating one or more replacement subsets or one or more replacement supersets, wherein the one or more replacement subsets or one or more replacement supersets each correspond to the replacement component;
determining device maintenance metrics over time corresponding to the replacement component and the one or more replacements subsets and the replacement supersets; and
in response to determining device maintenance metrics over time, communicating a ranked list of product alternatives.
The above-recited limitations establish a commercial interaction with a consumer to determine and communicate product purchase alternative determinations. This arrangement amounts to both a sales activity or behavior; and business relations. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts (See MPEP 2106.04(a)).
Claim 1 does recite additional elements:
by a processor set
by the processor set
by the processor set using large language model processing
These additional elements merely amount to the general application of the abstract idea to a technological environment (“by a processor set”, “using large language model processing”). The specification makes clear the general-purpose nature of the technological environment. Paragraphs 22-37 indicate that while exemplary general-purpose systems may be specific for descriptive purposes, any elements or combinations of elements capable of implementing the claimed invention are acceptable. That is, the technology used to implement the invention is not specific or integral to the claim.
Therefore, considered both individually and as an ordered combination, the additional elements do no more than generally link the use of the abstract idea to a particular technological environment or field of use. That is, given the generality with which the additional limitations are recited, the limitations do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim. Additionally, the claims do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not effect a transformation or reduction of a particular article to a different state or thing; and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea. Accordingly, the Examiner concludes that the claim fails to integrate the abstract idea into a practical application, and is therefore “directed to” the abstract idea.
Under step 2B of the Alice/Mayo framework, it must finally be considered whether the claim includes any additional element or combination of elements that provide an inventive concept (i.e., whether the additional element or elements are sufficient to amount to significantly more than the abstract idea). In the instant case, the additional elements (recited above) simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. Communicating information (i.e., receiving or transmitting data over a network) has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). Accordingly, the Examiner asserts that the additional elements, considered both individually, and as an ordered combination, do not provide an inventive concept, and the claim is ineligible for patent.
Independent Claims 10 and 19 are parallel in scope to claim 1 and ineligible for similar reasons.
Regarding Claims 2-5, 9, 11-14, 18
Claims 2-5, 9 set forth:
wherein the ranked list of product alternatives comprises one or more product alternatives selected from a group consisting of the replacement component, the one or more replacement subsets, and the one or more replacement supersets.
wherein the identifying the replacement component occurs based on user data selected from a group consisting of a user search query, a user purchase research, and a user purchase attempt, wherein the user data corresponds to the replacement component for a device.
wherein the identifying the replacement component occurs based on feedback and consensus from historical user reviews of the replacement component.
wherein the device maintenance metrics are selected from a group consisting of expectations of repair time, install time, and overall interaction time of a user.
wherein the device maintenance metrics comprise metrics selected from a group consisting of cost, repair time, installation time, repair time, and installation difficulty.
.
Such recitations merely embellish the abstract idea of determining product purchase alternatives. The claims do not set forth any additional limitations beyond those recited in claim 1. As such, the claims do not integrate the abstract idea into a practical application, and do not provide an inventive concept. Accordingly, the claims do not confer eligibility on the claimed invention and are ineligible for similar reasons to claim 1.
Claims 11-14, and 18 are parallel in scope to claims 2-5, and 9 and ineligible for similar reasons.
Regarding Claims 6-8, 15-17, 20
Claims 6-8 set forth:
performing predictive analysis on user data selected from a group consisting of a user search query, a user purchase research, and a user purchase attempt to identify a root cause that the device component would need to be replaced.
wherein the generating the one or more replacement subsets or the one or more replacement supersets occurs based on the root cause.
identifying one or more complimentary components based on the one or more replacement subsets or the one or more replacement supersets; and in response to identifying the one or more complimentary components, communicating, by the processor set, a recommendation of the one or more complimentary components.
Such recitations merely embellish the abstract idea of determining product purchase alternatives. While the claims do set forth the additional limitations of “by the processor set using a generative pretrained transformative model” and “by the processor set”, these recitations are similar to the additional limitations in claim 1, as they do no more than generally link the use of the abstract idea to a particular technological environment. As such, they do not integrate the abstract idea into a practical application, and do not provide an inventive concept. Accordingly, the claims do not confer eligibility on the claimed invention and are ineligible for similar reasons to claim 1.
Claims 15-17 are parallel in scope to claims 6-8 and are ineligible for similar reasons. Claim 20 is parallel in scope to claims 6 and 15, and is ineligible for similar reasons.
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.
2. Claims 1-7, 10-16, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Shah et al. (US 20120109662 A1, hereinafter Shah) in view of Travalini et al. (US 20230259821 A1, hereinafter Travalini) and Dietens (US 20230376642 A1, hereinafter Dietens).
Regarding Claim 1
Shah discloses a computer-implemented method, comprising:
identifying, by a processor set, a replacement component for a device component (Shah: see at least ¶28 module determines when an existing component should be replaced, and identifies replacement components)
generating, by the processor set, one or more replacement subsets or one or more replacement supersets, wherein the one or more replacement subsets or one or more replacement supersets each correspond to the replacement component; (Shah: see at least ¶46-47: module accesses a database to identify compatible replacement components for existing components)
determining, by the processor set, device maintenance metrics over time corresponding to the replacement component and the one or more replacements subsets and the replacement supersets; (Shah: see at least ¶20, 48-49: life cycle costs, including time to install replacement components, determined)
Shah does not explicitly disclose, but Travalini teaches in a similar environment:
performing, by the processor set using a regression model, predictive analysis on user input data to identify a root cause that the device component would need to be replaced; (Travalini: see at least ¶52, 136-138: regression models used to trained AI chatbot to diagnose problems, including root cause of a problem with a home component)
using large language model processing to generate the one or more replacement subsets or one or more replacement supersets (Travalini: see at least ¶51, 52, 129: chatbot identifies sets of replacement parts; chatbot model may be large language model)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the analysis and replacement component generation, as taught by Travalini, since such a modification would have delivered a better maintenance experience for all stakeholders by providing an artificial intelligence (“AI”) platform that intakes and generates work orders with a higher degree of accuracy, completes advanced diagnostics before a technician/vendor is sent out, advises tenants and/or homeowners on do-it-yourself (DIY) solutions, and/or builds intelligent home profiles (Travalini: see ¶3)
Shah further does not explicitly disclose:
in response to determining device maintenance metrics over time, communicating, by the processor set, a ranked list of product alternatives.
Dietens teaches that it is known to include communicating a ranked list of product alternatives based on determined maintenance metrics over time (Dietens: see at least ¶184, fig. 3A: list of alternative lighting products presented, can be sorted by total cost of ownership) in a similar environment. It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the ranked list of product alternatives, as taught by Dietens, since such a modification would have provided a more complete and optimized integration of parameters related to a plurality of sites for which products are sought (Dietens: see ¶4)
Regarding Claims 10, 19
Claims 10 and 19 are parallel in scope to claim 1 and are rejected on similar grounds.
Regarding Claims 2, 11
Shah further discloses:
wherein the product alternatives comprises one or more product alternatives selected from a group consisting of the replacement component, the one or more replacement subsets, and the one or more replacement supersets (Shah: see at least ¶46-47: replacement components identified for presentation to user)
While Shah does not explicitly disclose a ranked list of product alternatives, Dietens teaches a ranked list of product alternatives (Dietens: see at least ¶184, fig. 3A: list of alternative lighting products presented, can be sorted by total cost of ownership) in a similar environment. It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the ranked list of product alternatives, as taught by Dietens, since such a modification would have provided a more complete and optimized integration of parameters related to a plurality of sites for which products are sought (Dietens: see ¶4)
Regarding Claims 3, 12
Shah does not explicitly disclose, but Travalini teaches in a similar environment:
wherein the identifying the replacement component occurs based on user data selected from a group consisting of a user search query, a user purchase research, and a user purchase attempt, wherein the user data corresponds to the replacement component for a device. (Travalini: see at least ¶51: search query with AI chatbot triggers identification of suitable replacement parts)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the analysis and replacement component generation, as taught by Travalini, since such a modification would have delivered a better maintenance experience for all stakeholders by providing an artificial intelligence (“AI”) platform that intakes and generates work orders with a higher degree of accuracy, completes advanced diagnostics before a technician/vendor is sent out, advises tenants and/or homeowners on do-it-yourself (DIY) solutions, and/or builds intelligent home profiles (Travalini: see ¶3)
Regarding Claims 4, 13
Shah does not explicitly disclose, but Travalini teaches in a similar environment:
wherein the identifying the replacement component occurs based on feedback and consensus from historical user reviews of the replacement component. (Travalini: see at least ¶65-66, 88, 105-108: historical feedback used to train the model, which determines diagnosis and replacement parts)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the analysis and replacement component generation based on feedback, as taught by Travalini, since such a modification would have delivered a better maintenance experience for all stakeholders by providing an artificial intelligence (“AI”) platform that intakes and generates work orders with a higher degree of accuracy, completes advanced diagnostics before a technician/vendor is sent out, advises tenants and/or homeowners on do-it-yourself (DIY) solutions, and/or builds intelligent home profiles (Travalini: see ¶3)
Regarding Claims 5, 14
Shah further discloses:
wherein the device maintenance metrics are selected from a group consisting of expectations of repair time, install time, and overall interaction time of a user (Shah: see at least ¶20, 48-49: life cycle costs, including time to install replacement components used to identify replacement components)
Regarding Claims 6, 15, 20
Shah does not explicitly disclose, but Travalini teaches in a similar environment:
performing, by the processor set using a generative pretrained transformative model, predictive analysis on user data selected from a group consisting of a user search query, a user purchase research, and a user purchase attempt to identify a root cause that the device component would need to be replaced. (Travalini: see at least ¶51-52, 58: search query with AI chatbot triggers analysis to identify root cause that a component would need to be replaced and identification of suitable replacement parts using trained transformative model)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the analysis and replacement component generation, as taught by Travalini, since such a modification would have delivered a better maintenance experience for all stakeholders by providing an artificial intelligence (“AI”) platform that intakes and generates work orders with a higher degree of accuracy, completes advanced diagnostics before a technician/vendor is sent out, advises tenants and/or homeowners on do-it-yourself (DIY) solutions, and/or builds intelligent home profiles (Travalini: see ¶3)
Regarding Claims 7, 16
Shah does not explicitly disclose, but Travalini teaches in a similar environment:
wherein the generating the one or more replacement subsets or the one or more replacement supersets occurs based on the root cause. (Travalini: see at least ¶51-52: search query with AI chatbot triggers analysis to identify root cause that a component would need to be replaced and identification of suitable replacement parts)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah, with the analysis and replacement component generation, as taught by Travalini, since such a modification would have delivered a better maintenance experience for all stakeholders by providing an artificial intelligence (“AI”) platform that intakes and generates work orders with a higher degree of accuracy, completes advanced diagnostics before a technician/vendor is sent out, advises tenants and/or homeowners on do-it-yourself (DIY) solutions, and/or builds intelligent home profiles (Travalini: see ¶3)
Regarding Claims 9, 18
Shah further discloses:
wherein the device maintenance metrics comprise metrics selected from a group consisting of cost, repair time, installation time, repair time, and installation difficulty (Shah: see at least ¶20, 48-49: life cycle costs, including time to install replacement components used to identify replacement components)
3. Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Shah in view of Travalini and Dietens, as applied above, and further in view of Marinkovich et al. (US 12511630 B2, hereinafter Marinkovich).
Regarding Claims 8, 17
Shah in view of Travalni and Dietens does not explicitly disclose, but Marinkovich teaches in a similar environment:
identifying, by the processor set, one or more complimentary components based on the one or more replacement subsets or the one or more replacement supersets; (Marikovich: see at least col. 418, line 7 – col. 419, line 28: complementary components that may be generated are determined and recommended based on determination of potential replacement parts)
in response to identifying the one or more complimentary components, communicating, by the processor set, a recommendation of the one or more complimentary components. (Marikovich: see at least col. 418, line 7 – col. 419, line 28: complementary components that may be generated are determined and recommended based on determination of potential replacement parts)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Shah in view of Travalini and Dieters, determination and recommendation of complementary components, as taught by Marinkovich, since such a modification would have allowed enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations. (Marinkovich: see col. 2: lines 22-26)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Song et al. (US 8340948 B1) discloses a computer-based method for simulating an overall effect of a component replacement on the reliability of a platform, including presenting a ranked list of supersets based on maintenance metrics.
Diaz et al. (US 20190370717 A1) discloses system and method for recommending a transaction to replace a device based upon total cost of ownership, including calculating a total-cost of ownership for a recommended replacement component set.
Olivier et al. (US 20240378654 A1) discloses an online system determines whether to recommend a replacement item to a user based on a predicted sentiment score, including training a large language model based on historical feedback from users regarding the recommendation of replacement items.
Dagley et al. (US 20210342790 A1) discloses visualizing vehicle part replacement information using extended reality, including identifying components in need of replacement.
“Assessing the capabilities of ChatGPT to improve additive manufacturing troubleshooting” (PTO-892 Reference U) discloses using LLMs to aid in additive manufacturing processes, including using ChatGPT to diagnose causes for component failures.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL A MISIASZEK whose telephone number is (571)272-6961. The examiner can normally be reached Monday-Thursday. 8:00 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Smith can be reached at 571272-6763. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL MISIASZEK/Primary Examiner, Art Unit 3688