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 .
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Figs 1-6 are functional block diagrams patterned after the claims merely showing blank boxes/blocks with reference numbers that do not show the features of the invention as recited in the claims. In other words, raw reference numbers and otherwise blank boxes are simply not sufficient to show the claimed features. It is suggested that text labels be added to each of the blank boxes.
Specification
The abstract of the disclosure is objected to because it does not “enable the Office and the public generally to determine quickly from a cursory inspection the nature and gist of the technical disclosure.” 37 CFR 1.72(b). Specifically, it is not clear what this technology is used for or what the advantages may include. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 11, 13, 14, 15, and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 11 recites: “authenticating the artificial-intelligence system, preferably against the at least one content source”. The term “preferably” renders the scope of claim 11 unclear because it is uncertain whether authenticating the artificial intelligence system against the at least one content source is a required limitation of the claim or merely an optional/preferred embodiment. If authentication against the content source is intended to be required, the claims should positively recite that the artificial-intelligence system is authenticated against the at least one content source. If it is not required, the preferred language should be removed or rewritten or clearly define the metes and bounds of the claim.
Claim 13 recites: “at least one trained model, in particular an autoregressive language model, preferably a deep learning model”. The phrases “in particular” and “preferably” render the scope of the claim 13 unclear. It is uncertain whether the trained model is required to be an autoregressive language model or whether an autoregressive language model is merely an example of optional embodiment. It is also unclear whether the trained model is required to be a deep learning model, or whether a deep learning model is merely optional. As written, the claim does not clearly establish whether the claim requires: (1) any trained mode, (2) an autoregressive language model, (3) a deep learning model, or (4) an autoregressive deep learning model.
Claim 13 further recites: “allocate an amount to be paid for the responses outputted by the chat application, preferably without concurrently requiring payment of the amount”. The term “preferably” renders the scope of this limitation unclear because it is uncertain whether allocating the amount without concurrently requiring payment is required, or merely an optional feature. As currently written, the claim appears to encompass both systems that require concurrent payment and systems that do not require concurrent payment. Accordingly, the metes and bounds of the payment application limitation are unclear.
Claim 13 further recites: “monitor a total allocated amount for the ID, in particular a sum of a plurality of said amounts”. The phrase “in particular” renders the scope of this limitation unclear because it is uncertain whether the monitored total allocated amount must be a sum of plurality of said amounts, or whether summing a plurality of amounts is merely an example or preferred embodiment of the total allocated amount. If applicant intends to require summing multiple allocated amounts, the claim should positively recite that the payment application monitors a sum of a plurality of allocated amounts for the ID.
Claim 14 depends upon claim 13. Because claim 13 has been rejected under 35 U.S.C. 112(b) for being indefinite, the scope of claim 14 is rendered vague and indefinite and it is rejected under the same grounds.
Claim 15 recites: “preferably wherein the database comprises a relationship between content and/or content sources and the pricing information”. The term “preferably” renders the scope of the claim 15 unclear because it is uncertain whether the database is required to comprise a relationship between content and/or content sources and the pricing information, or whether that relationship is merely an optional embodiment. As written, the claim does not clearly establish whether the database must store pricing information in association with particular content or content sources, or whether merely storing pricing information alone is sufficient.
Claim 16 recites: “processing the client request to identify/select at least one content source which provides content, in particular paywalled content for responding to the client request”. The phrase “in particular paywalled content” renders the scope of claim 16 unclear because it is uncertain whether the claimed content source must provide paywalled content, or whether the limitation broadly covers any content source that provides non-paywalled content, with paywalled content merely being a preferred example. The phrase “in particular” introduces ambiguity by reciting what appears to be a preferred embodiment rather than a definite claim requirement.
Claim 16 further recites: “inputting at least parts of the received content and at least parts of the client request into at least one trained model, in particular an autoregressive language model, preferably a deep learning model”. The phrases “in particular an autoregressive language model” and “preferably a deep learning model” renders the scope of claim 16 unclear because it is uncertain whether the trained model receiving the input must be an autoregressive language model or must be a deep learning model. The phrases “in particular” and “preferably” introduce ambiguity by reciting what appears to be a preferred embodiment rather than a definite claim requirement.
Therefore, claims 11, 13, 14, 15, and 16 fail to particularly point out and distinctly claim the subject matter regarded as the invention. Applicant should amend the claims to remove optional/preferred language and clearly recite the intended scope in a more defined manner.
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.
Claims 1-16 are rejected under 35 U.S.C. 101 because the clamed invention is directed to a mental process without significantly more.
Independent claims 1, 13, and 16 recite a computer-implemented method/system for receiving a user request, identifying content sources, obtaining content, using the content to generate an AI response, and allocation/defer charging payment for the content or response. Under the broadest reasonable interpretation (BRI), the claims cover the abstract idea of selecting information responsive to a request and arranging payment for use of that information. This is a series of mental steps and commercial interactions that can be performed by a human using a pen and paper, or by using generic computer/AI tools merely as proxy. Specifically, claim 1 recites:
a) receiving the client request over an interface from a client device (a human receiving a question/request from another person by email, chat, or written note); b) determining a client identity (ID) associated with at least one user device issuing the request (a human identifying who made the request, such as by recognizing the user, checking the account name, or looking up a customer number); c) processing the client request to identify at least one content source which provides paywalled content for responding to the client request (a human reading the request and deciding which paid article, database, website, book, journal, or other source would help answer the questions); d) obtaining an index of content based on the user request, wherein the index identifies paywalled content of the at least one content source (a human searching a catalog, search engine, table of contents, index, or search-result list to find potentially relevant paid content); e) determining a cost and payment terms of the at least one content source for a deferred payment arrangement for obtaining the paywalled content (a human reading the listed price, subscription terms, rental, terms, or payment terms for accessing the content and deciding whether the payment can be deferred); f) confirming a selection of the paywalled content of the at least one content source based on a characteristic of the client and the associated payment terms of the at least one content source (a human deciding whether to select the content based on the user’s account status, creditworthiness, payment history, authorization, or willingness to pay); g) issuing at least one secondary request to the at least one content source to provide the selected content (a human requesting, ordering, downloading, or otherwise asking for selected source); h) receiving the selected content from the at least one content source in response to the secondary request (a human receiving the article, webpage, report, or other selected content); i) inputting at least parts of the received content and at least parts of the client request into at least one trained model (a human person pasting or typing the request and selected content into a generic AI tool, search tool, or summarization tool as a proxy); j) transmitting at least partially an output of the trained model, to the client component to provide the response to the client request (a human sending the answer back to the requester); and k) allocating an amount to be paid for the received content without concurrently requiring payment of the amount to a payment system, using the ID (a human putting the content cost on the requester’s account, invoice, tab, ledger, or other deferred payment record).
Claim 13 recites: a chat application, the chat application providing at least one first participant of the chat conversation, the chat application being adapted to determine and output responses to questions issued by at least one second participant of the chat conversation (a human can act as the first participant in a chat or conversation by receiving questions from another person, determining an answer, and providing the answer orally, by email, by message, or in writing);
at least one trained model, in particular an autoregressive language model, preferably a deep learning model configured such that the trained model receives the questions issued by the at least one second participant, determines the responses and outputs the responses to the chat application (A person can use their own knowledge, notes, reference materials, or a generic AI tool such as ChatGPT as a proxy to receive a question, determine a response, and provide that response back to the chat participant), wherein the chat application is adapted to
a) issue at least one secondary request to a content source to receive content (A person can ask a third party, search a website, etc. to obtain additional information for answering the question);
b) input at least partially the received content and questions in the trained model (A person can read the question and the received content, or copy/paste the question and receive content into a generic AI tool, summarization tool, or search tool);
a payment application, adapted to:
store at least one client identity (ID) to identify the at least one second participant and/or a client component used by the at least one second participant (A person can write down the requester’s name, account number, customer ID, or other identifying information in a ledger/spreadsheet);
allocate an amount to be paid for the responses outputted by the chat application, preferably without concurrently requiring payment of the amount, using the ID (A person can record a charge for the answer to content on the requester’s account of tab, without collecting immediate payment));
monitor a total allocated amount for the ID, in particular a sum of a plurality of said amounts (A person can keep a running balance for the requester by adding together multiple charges associated with the same account or ID); and
transmit a payment request, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount (A person can send an invoice or other payment request when requester’s running balance exceeds a chosen threshold).
Claim 16 recites: a) receiving the client request over an interface from a client device (a person can receive a question/request from another person via generic computer medium);
b) determining a client identity (ID) of at least one of a user, and client component, issuing the request (a person can identify who made the request by checking requester’s name, email address, profile, etc.));
c) processing the client request to identify/select at least one content source which provides content, in particular paywalled content for responding to the client request (A person can read the request and decide which source would help answer it);
d) issuing at least one secondary request to the identified/selected content source to provide content (a person can request the selected content by searching a website, opening a database, asking an expert, etc.);
e) receiving content from the identified/selected content source in response to the secondary request (a person can receive the requested article, webpage, report, search result, from the selected source);
f) inputting at least parts of the received content and at least parts of the client request into at least one trained model, in particular an autoregressive language model, preferably a deep learning model (a person can read the request and received content to generate an answer themselves or with ChatGPT);
g) transmitting at least partially the output of the trained model to the client component to provide the response to the client request (A person can send the generated answer back to requester via email, chat message, verbal response, etc.);
h) optionally allocating an amount to be paid for the transmission of the response, preferably without concurrently requiring payment of the amount, using the ID (A person can optionally write down a charge for the response on the requester’s account, tab, etc. without requiring requester to pay immediately).
The remaining dependent claims fail to adad patent eligible subject matter to the independent claims:
Claims 2 and 6 simply adds providing cost information and receiving user authorization to proceed with allocating the cost. A human could perform these commercial approval steps by telling requested price of a paid source and receiving permission to put the cost on their tab.
Claim 3 simply adds that the cost is zero in exchange for an acknowledgement that the user will provide a service. A human can mentally understand this compensation arrangement such as allowing access in exchange for feedback, answering questions, agreeing to perform task, etc.
Claim 4 simply adds a characteristic comprising creditworthiness which a human could make a judgement on by reviewing request’s credit score, account history, etc. before deciding whether to allow deferred payment from them.
Claim 5 simply adds bypassing paywall to receive selected content which under BRI is merely a deciding step for access of restricted content after satisfying a condition with no technological improvement to the paywall access.
Claim 7 simply adds generating an output by the trained model which a person can do with ChatGPT as a summarization tool as a proxy to generate and answer from the request and selected source material (with no improvement on the trained model itself))
Claims 8 and 13 simply add payment application monitoring/transmitting limitations reciting monitoring a running total and transmitting a payment request when the total exceeds a threshold. A person can perform this by keeping a ledger or tab for a requester and sending an invoice when the balance exceeds the set amount.
Claim 9 simply adds increasing the threshold after payment is received which a person can perform mentally by increasing customer’s credit/tab limit after they pay prior bills.
Claim 10 simply adds issuing a search request to a database based on client request which a person can perform by searching database, library, etc. using terms from the question of a requester.
Claims 11 and 14 simply adds authentication certifications that are generic verifications steps a person can perform by them checking credentials, certificates, log in information, keys, etc.
Claim 12 simply adds acquiring and verifying payment information from the ID which a person could perform by checking payment information, account details, credit card information etc. that is associated with the requestor.
Claim 15 simply adds a database storing content pricing and relationships between content sources and pricing information which is a generic price list a human could maintain and consult when deciding whether to use a paid source or not.
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does/do not fall within at least one of the four categories of patent eligible subject matter because it is drawn to a combination of software per se. and data per se.
Claim 13 describes a system, however even though the applicant is claiming a "system", this system is in the form of: a chat application, at least one trained model, and a payment application. Thus, under the BRI, this claim is directed towards nothing more than a collection of software (i.e., chat and payment) and data (the trained model). A combination of software and data per se does not fall within the 4 statutory categories of invention.
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.
Claims 1, 4, 6, 7, 10, 12, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy) in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1) in further view of Kublickis (US 20070067297 A1).
Regarding claim 1, Gray discloses:
A method for providing an artificial-intelligence system responsive to a client request, comprising the steps of (Gray, P(4): "Implementations disclosed herein are directed to at least selectively utilizing an LLM in generating an NL based summary to be rendered (e.g., audibly and/or graphically) in response to a query" (teaches AI/LLM system generating a response to a client/user query)):
a) receiving the client request over an interface from a client device (Gray, P(7): "a given query is submitted, such as a given query formulated and submitted based on user input", "a search can performed for the given query", P(136): "receiving a query associated with a client device (e.g., a query submitted based on user interface input at the client device" (teaches receiving a user/client request/query and using it to drive the system's response., teaches receiving request from client device));
c) processing the client request to identify at least one content source (Gray, P(6): "content from query-responsive search result document(s) that are responsive to the query", "The search result document(s), from which the content is obtained" (teaches processing query to identify select content sources/documents responsive to the client request))
d) obtaining an index of content based on the user request (Gray, P(7): "a search can performed for the given query to obtain query-responsive search result documents", "search result documents A and B can be selected", "Contents A, B, C, and D can then be included in the additional content" (teaches obtaining a query-based set/index of responsive content/documents)),
g) issuing at least one secondary request to the at least one content source to provide the selected content (Gray, P(136): "corresponding content from each of the search result documents of the set" (teaches obtaining/requesting content from selected responsive search-result documents/content sources for LLM processing));
h) receiving the selected content from the at least one content source in response to the secondary request (Gray, P(136): "generating large language model (LLM) output based on processing, using an LLM, corresponding content from each of the search result documents of the set." (teaches receiving/obtaining selected content because the LLM processes content from each selected document/source));
i) inputting at least parts of the received content and at least parts of the client request into at least one trained model (Gray, P(150): "generating large language model (LLM) output based on processing input using an LLM. The input is based on the query and/or corresponding content from one or more search result documents " (query teaches to client request, corresponding content teaches to the received content, LLM teaches to trained model));
j) transmitting at least partially an output of the trained model, to the client component to provide the response to the client request (Gray, P(150): "generating a natural language (NL) based summary using the LLM output and causing the NL based summary to be rendered, at the client device" (teaches transmitting/rendering trained model output to the client component to provide the response)); and
Gray does not explicitly disclose:
b) determining a client identity (ID) associated with at least one user device issuing the request
which provides paywalled content for responding to the client request
wherein the index identifies paywalled content of the at least one content source
e) determining a cost and payment terms of the at least one content source for a deferred payment arrangement for obtaining the paywalled content;
f) confirming a selection of the paywalled content of the at least one content source based on a characteristic of the client and the associated payment terms of the at least one content source;
k) allocating an amount to be paid for the received content without concurrently requiring payment of the amount to a payment system, using the ID. However, Hutchison discloses:
b) determining a client identity (ID) associated with at least one user device issuing the request (Hutchison, P[0012]: "the credit processing server or commerce gateway communicates with one or more identity bureaus in order to determine a buyer's identity before creating a virtual payment account." (teaches determining a client/buyer identity), P[0089]: "The container includes: transaction information, such as purchase detail; identification of the parties, such as a buyer identification" (teaches buyer/client ID used in the transaction));
for a deferred payment arrangement for obtaining the paywalled content (Hutchison, P[0010], teaches deferred payment arrangement for obtaining content through virtual account rather than immediate direct payment);
f) confirming a selection of the paywalled content of the at least one content source based on a characteristic of the client (Hutchison, P[0049]: "determine the credit worthiness of a buyer." "The score equates to the credit worthiness of the buyer" (teaches client characteristic as creditworthiness)), and the associated payment terms of the at least one content source (Hutchison, Claim 9: "in response to determining that said virtual payment account may be charged for said cost of said product, transmitting" (teaches conforming the transaction/selection based on payment/account authorization));
k) allocating an amount to be paid for the received content (Hutchison, claim 14: "charging said virtual payment account for a cost associated with said product" (teaches allocating an amount owed for the received content/product)) without concurrently requiring payment of the amount to a payment system (Hutchison, P[0130]: "waits for their billing cycle, e.g., monthly, and then charges the buyers for their purchases" (teaches deferred/non concurrent payment), ), using the ID (Hutchison, P[0089]: "buyer identification which identifies the buyer").
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]). Thus, the combination would allow Gray’s AI response system to associate user requests/responses with a client ID and allocate payment using Hutchison’s deferred payment account framework.
Hutchison, in combination with Gray, does not explicitly disclose:
which provides paywalled content for responding to the client request
wherein the index identifies paywalled content of the at least one content source e) determining a cost and payment terms of the at least one content source
However, Kublickis discloses:
which provides paywalled content for responding to the client request (Kublickis, P[0184]: "websites offering content for free, content on a paid subscription basis, or content on a fee-per-item-viewed or fee-per-item-downloaded basis." (teaches the identified content source may provide paid/paywalled content));
wherein the index identifies paywalled content of the at least one content source (Kublickis, P[0334]: "appropriate queries against the content databases, using either affinity values, or keywords or phrases will generate result sets containing lists of links to relevant websites" (teaches indexed/searchable content databases identifying relevant websites/content sources), "content on a paid subscription basis, or content on a fee-per-item-viewed or fee-per-item-downloaded basis" (teaches indexed content/content source may be paid/paywalled);
e) determining a cost and payment terms of the at least one content source (Kublickis, P[0613], teaches cost/payment terms of the content source, P[0651], teaches content-provider payment terms)
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and in further view of Kublickis. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), and Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]). Thus, the combination would allow Gray’s AI system to obtain paid content responsive to a user query and allocate payment for that content using Hutchison’s deferred payment account system.
Regarding claim 4, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Hutchison further discloses:
wherein the client characteristic of step f) comprises a credit worthiness characteristic of the client (Hutchison, P[0049]: "determine the credit worthiness of a buyer.", "The score equates to the credit worthiness of the buyer").
Regarding claim 6, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Hutchison further discloses:
wherein step f) includes the step of:
receiving an authorization signal indicating that the user of the client device is accepting (Hutchison, P[0087]: "After selecting an account and entering the correct pass phrase, the buyer clicks "Continue" 1177 to proceed with the purchase." (teaches user of client device accepting/authorizing transaction because the buyer selects account, authenticates, and clicks continue to proceed), P[0087]: "the seller server 51 calculates the total cost of the order, including tax and shipping and handling, and the buyer is presented with a confirmation screen 1180" (teaches authorization of an amount correlating to the indicated total cost because the total cost is calculated and the buyer authorizes the purchase), P[0089]: "an authentication request and container are received from the Web browser 64", "The container includes: transaction information, such as purchase detail; identification of the parties, such as a buyer identification which identifies the buyer" (teaches authorization signal associated with client device/user ID and purchase details))
Hutchison, in combination with Gray, does not explicitly disclose:
to allocate an amount that correlates to indication total cost for receiving the response to the client request
However, Kublickis discloses:
to allocate an amount that correlates to indication total cost for receiving the response to the client request (Kublickis, P[0613]: "along with purchase prices or rental rates and terms" (teaches cost amount for content/response transaction because content providers post prices/rates/terms for digital content))
Regarding claim 7, the combination of Gray, Hutchison, and Kublickis discloses the method according to claim 1.
Gray further discloses: comprising, prior to step j), the step of:
generating an output by the trained model, based on the input of step i) (Gray, P(136): "generating large language model (LLM) output based on processing, using an LLM" (teaches generating output by trained mode because Gray's LLM/trained model generates LLM output based on processed input))).
Regarding claim 10, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Gray further discloses:
the search request at least partially being based on the client request (Gray, P(136): "Selecting the set of search result documents includes selecting, for inclusion in the set, a plurality of query-responsive search result documents based on the query-responsive search result documents being responsive to the query' (teaches the search being based on the client request/query because Gray selects responsive search-result documents based on the query)).
Gray does not explicitly disclose:
wherein the step c) further comprises:
issuing a search request to a database of the artificial-intelligence system
However, Kublickis further discloses:
wherein the step c) further comprises:
issuing a search request to a database of the artificial-intelligence system (Kublickis, P[0334]: "appropriate queries against the content databases, using either affinity values, or keywords or phrases will generate result sets containing lists of links to relevant websites" (teaches issuing a database search request because Kublickis teaches queries against content databases producing result sets))
Regarding claim 12, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Hutchison further discloses:
wherein the step b) further comprises:
acquiring and verifying payment information from the ID (Hutchison, P[0070]: "submits the application data 106 from the completed form to the credit processing server 53 for account and credit limit authorization" (teaches acquiring payment/account information), P[0070]: "The credit processing server 53 verifies the application data by requesting identity information 116 from an identity bureau 56" (teaches verifying payment/credit information associated with the user/account ID)).
Regarding claim 16, Gray further discloses:
A method for providing an artificial-intelligence system responsive to a client request, comprising the steps of (Gray, P(136): "receiving a query associated with a client device", "generating a natural language (NL) based summary using the LLM output (teaches the preamble because Gray teaches an AI/LLM based method that receives a client query/request and generates a responsive output/summary for the client device)):
a) receiving the client request over an interface from a client device (Gray, P(7): "a given query is submitted, such as a given query formulated and submitted based on user input", "a search can performed for the given query", P(136): "receiving a query associated with a client device (e.g., a query submitted based on user interface input at the client device" (teaches receiving a user/client request/query and using it to drive the system's response., teaches receiving request from client device));
c) processing the client request to identify/select at least one content source which provides content (Gray, P(136): "selecting a set of search result documents. Selecting the set of search result documents includes selecting, for inclusion in the set, a plurality of query-responsive search result documents based on the query-responsive search result documents being responsive to the query" (teaches processing the client request to identify/select a content source because Gray selects query responsive search result documents/content sources based on the user query)),
d) issuing at least one secondary request to the identified/selected content source to provide content (Gray, P(136): "corresponding content from each of the search result documents of the set" (teaches issuing a secondary request to the selected content source because Gray obtains/retrieves corresponding content from the selected search result documents/content sources for use in response generation));
e) receiving content from the identified/selected content source in response to the secondary request (Gray, P(136): "generating large language model (LLM) output based on processing, using an LLM, corresponding content from each of the search result documents of the set" (teaches receiving content from the selected content source because Gray's LLM processes corresponding content obtained from the selected search-result documents));
f) inputting at least parts of the received content and at least parts of the client request into at least one trained model, in particular an autoregressive language model, preferably a deep learning model (Gray, P(15): "generating large language model (LLM) output based on processing input using an LLM. The input is based on the query and/or corresponding content from one or more search result documents that are responsive to the query" (teaches inputting received content and the client request into a trained model because the query correspond to the client request, the corresponding content corresponds to received content, and the LLM corresponds to the trained/autoregressive language model deep learning model));
g) transmitting at least partially the output of the trained model to the client component to provide the response to the client request (Gray, P(136): "generating a natural language (NL) based summary using the LLM output, and causing the NL based summary to be rendered at the client device" (teaches transmitting at least part of the trained model output to the client component because the LLM output is used to generate the NL summary rendered at the client device in response to eh query/request));
Gray does not disclose:
b) determining a client identity (ID) of at least one of a user, and client component, issuing the request
h) optionally allocating an amount to be paid for the transmission of the response, preferably without concurrently requiring payment of the amount, using the ID
in particular paywalled content for responding to the client request
However, Hutchison discloses:
b) determining a client identity (ID) of at least one of a user, and client component, issuing the request (Hutchison, P[0089]: "buyer identification which identifies the buyer" (teaches determining a client identity of the user issuing the request), P[0107]: "internal account identification associated with authentication container is determined", "internal account identification and sub-account information is added to the empty account identification container" (teaches determining/using an ID associated with the client/account component for transaction procession));
h) optionally allocating an amount to be paid for the transmission of the response (Hutchison, P[0010]: "the buyer is automatically billed for the ordered good, service or content based on a virtual payment account" (teaches allocating an amount to be paid because Hutchison bills the buyer through a virtual payment account for ordered content/service)), preferably without concurrently requiring payment of the amount (Hutchison, P[0130]: "waits for their billing cycle, e.g., monthly, and then charges the buyers for their purchases" (teaches non-concurrent/deferred payment because the buyer is charged later during the billing cycle)), using the ID (Hutchison, P[0089]: "a buyer identification which identifies the buyer").
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]). Thus, the combination would allow Gray’s AI response system to associate user requests/responses with a client ID and allocate payment using Hutchison’s deferred payment account framework.
Hutchison, in combination with Gray, does not disclose:
in particular paywalled content for responding to the client request
However, Kublickis discloses:
in particular paywalled content for responding to the client request (Kublickis, P[0184]: "websites offering content for free, content on a paid subscription basis, or content on a fee-per-item-viewed or fee-per-item-downloaded basis." (teaches paywalled content because Kublickis teaches content sources providing paid subscription or fee per item content for user access));
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and in further view of Kublickis. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), and Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]). Thus, the combination would allow Gray’s AI system to obtain paid content responsive to a user query and allocate payment for that content using Hutchison’s deferred payment account system.
Claims 2, 3, 5, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy), in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1), in further view of Kublickis (US 20070067297 A1), in furthest view of Weigle et al. (hereinafter Weigle) (US 8706639 B1) (US 8706639 B1).
Regarding claim 2, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Kublickis further discloses:
wherein step f) further comprises the steps of:
providing cost information for the paywalled content to the user device (Kublickis, P[0613]: "electronically post their wares to the stores, along with purchase prices or rental rates and terms" (teaches providing cost information for paid content));
Kublickis, in combination with Gray and Hutchison, does not disclose:
and obtaining an indication from the user device to proceed to obtain the paywalled content
However, Weigle discloses:
and obtaining an indication from the user device to proceed to obtain the paywalled content (Weigle, P(80): "the user chooses an offer to accept. The client device 120 sends an indication of the chosen offer " (teaches obtaining an indication from the user device to proceed because the user/client device sends an indication accepting an offer to access requested content)).
It would have been prima facie obvious to one of ordinary skill in the art before the earlist filing date of the claimed invention to have modified Gray in view of Hutchison, in further view of Kublickis, and in furthest view of Weigle. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and Weigle’s known protected content access framework for determining whether a user is allowed to access a requested content item based on a n offer, user class, and access conditions (Weigle, P[0007]), thus, the combination would predictably allow paid or protected content identified for an AI response to be authorized and accessed before being used to generate the response.
Regarding claim 3, the combination of Gray, Hutchison, Kublickis, and Weigle discloses the method of claim 2.
Kublickis further discloses:
wherein the cost is zero, in exchange for an acknowledgement from the user device that the user will provide a service (Kublickis, P[0632]: "The pre-funding of their accounts through good-faith participation in the marketplace enables consumer members to purchase or rent digital content without spending money from their existing personal cash flow" (zero out of pocket cost in exchange for user participation/service)).
Regarding claim 5, the combination of Gray, Hutchison, and Kublickis discloses the method according to claim 1.
The combination of Gray, Hutchison, and Kublickis does not disclose:
wherein step c) includes the step of:
bypassing a paywall of the content source by the artificial-intelligence system to receive the selected content
However, Weigle discloses:
wherein step c) includes the step of:
bypassing a paywall of the content source by the artificial-intelligence system to receive the selected content (Weigle, P(7): "determining whether the user is allowed to access the content item" and "the authorization system 170 determines whether the user has accepted an offer granting access to the requested content" (teaches bypassing/obtaining access to protected content after access authorization because Weigle determines whether the user may access requested protected content based on offer acceptance.)).
It would have been prima facie obvious to one of ordinary skill in the art before the earlist filing date of the claimed invention to have modified Gray in view of Hutchison, in further view of Kublickis, and in furthest view of Weigle. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and Weigle’s known protected content access framework for determining whether a user is allowed to access a requested content item based on a n offer, user class, and access conditions (Weigle, P[0007]), thus, the combination would predictably allow paid or protected content identified for an AI response to be authorized and accessed before being used to generate the response.
Regarding claim 11, the combination of Gray, Hutchison, and Kublickis discloses the method of claim 1.
Hutchison further discloses:
wherein the step d) further comprises:
authenticating the artificial-intelligence system (Hutchison, P[0015]: "Security is ensured via authentication of the parties to a transaction." (teaches authentication of system/party involved in the transaction)
Hutchison, in combination with Gray and Kublickis, does not disclose:
preferably against the at least one content source
However, Weigle discloses:
preferably against the at least one content source (Weigle, P(7): "determining whether the user is allowed to access the content item based on the offer, the user's class, and a current timestamp." (teaches authentication/authorization against a protected content source because access to the requested content item is determined based on access conditions)).
It would have been prima facie obvious to one of ordinary skill in the art before the earlist filing date of the claimed invention to have modified Gray in view of Hutchison, in further view of Kublickis, and in furthest view of Weigle. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and Weigle’s known protected content access framework for determining whether a user is allowed to access a requested content item based on a n offer, user class, and access conditions (Weigle, P[0007]), thus, the combination would predictably allow paid or protected content identified for an AI response to be authorized and accessed before being used to generate the response.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy), in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1), in further view of Kublickis (US 20070067297 A1), in furthest view of O’Donoghue et al. (hereinafter O’Donoghue) (US 20130054417 A1).
Regarding claim 8, the combination of Gray, Hutchison, and Kublickis discloses the method according to claim 1.
The combination of Gray, Hutchison, and Kublickis does not explicitly disclose:
comprising the steps of:
monitoring a total allocated amount, in particular a sum of a plurality of said amounts, the ID; and
transmitting a payment request to the client device, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount;
However, O’Donoghue discloses:
comprising the steps of:
monitoring a total allocated amount, in particular a sum of a plurality of said amounts, the ID (O'Donoghue, P[0031]: "Transactions in which a user is required to pay a micropayment (i.e., such as a few pennies for access to "premium" content) are aggregated over time in a purchaser's computing device, such as a smartphone. Eventually the accumulated micropayment transactions are downloaded to a trusted payment authority for settlement." (teaches monitoring a total allocated amount/sum of plural allocated amounts because micropayment transactions are aggregated/accumulated over for later settlement)); and
transmitting a payment request to the client device, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount (O'Donoghue, P[0007]: "purchaser's computing device may determine that transaction data should be downloaded to the payment authority based upon one or more of a total amount of money in the stored transactions equals or exceeds a threshold value" (teaches threshold-triggered settlement/payment handling because stored transaction data is downloaded to the payment authority when the total stored amount equals or exceeds threshold.);
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and Kublickis, and in further view of O’Donoghue. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and O’Donoghue’s known technique for aggregating micropayment transactions and downloading transaction data for settlement when a stored total equals or exceeds a threshold (O’Donoghue, P[0011], P[0021]), thus, the combination would reduce repeated small payment processing by accumulating content-related charges and triggering settlement when the accumulated amount exceeds a predetermined threshold.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy), in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1), in further view of Kublickis (US 20070067297 A1), in furthest view of Sanchez et al. (hereinafter Sanchez) (US 20020188533 A1).
Regarding claim 9, the combination of Gray, Hutchison, and Kublickis discloses the method according to claim 6.
The combination of Gray, Hutchison, and Kublickis does not disclose:
wherein a new predetermined threshold amount for receiving a subsequent payment request is increased after a payment has been received from the client device for the payment request;
However, Sanchez discloses:
wherein a new predetermined threshold amount for receiving a subsequent payment request is increased after a payment has been received from the client device for the payment request (Sanchez, P[0044]: "when financial account provider 1200 receives the certain number of consecutive timely payments (Step 460; YES), it may increase the credit limit associated with the SGSG account a certain amount based on the terms and conditions associated with the SGSG account" (teaches increasing a future threshold/credit limit after payment has been received), P[0044]: "financial account provider 1200 may increase the credit limit for a SGSG account by $100 for every three consecutive timely payments received." (teaches increasing the threshold amount after payments are received)).
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and Kublickis, and in further view of Sanchez. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and Sanchez’s known adjustable account parameter technique in which a credit card limit is increased after receiving timely payments (Clifford, P[0044]-P[0045]), thus, predictably increasing a subsequent payment or credit card threshold after payment is received, based on known account management practices.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy) in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1) in further view of O’Donoghue et al. (Hereinafter O’Donoghue) (US 20130054417 A1).
Regarding claim 13, Gray further discloses:
A system for providing an artificial-intelligence system responsive to a client request, the system comprising (Gray, P(136): "receiving a query associated with a client device", "generating a natural language (NL) based summary using the LLM output, and causing the NL based summary to be rendered at the client device" (teaches a system providing an AI/LLM response to a client request/query)):
a chat application, the chat application providing at least one first participant of the chat conversation, the chat application being adapted to determine and output responses to questions issued by at least one second participant of the chat conversation (Gray, P(136): "receiving a query associated with a client device", "generating a natural language (NL) based summary using the LLM output, and causing the NL based summary to be rendered at the client device" (teaches the chat application determining and outputting responses to user questions/queries because the system generates and renders an NL response to the client device));
at least one trained model, in particular an autoregressive language model, preferably a deep learning model configured such that the trained model receives the questions issued by the at least one second participant, determines the responses and outputs the responses to the chat application (Gray, P(136): "generating large language model (LLM) output based on processing, using an LLM" (teaches the trained model/autoregressive language model/deep learning model because an LLM receives input corresponding to the question, determines LLM output and provides that output for the response.)), wherein the chat application is adapted to
a) issue at least one secondary request to a content source to receive content (Gray, P(136): "corresponding content from each of the search result documents of the set" (teaches issuing a secondary request/obtaining content from selected content sources because the system obtains corresponding content from selected search result documents));
b) input at least partially the received content and questions in the trained model (Gray, claim 1: "the input being based on the query and/or corresponding content from one or more search result documents" (teaches inputting received content and questions into the trained model because the input to the LLM is based on both the query question and the corresponding content), P[0107]: "internal account identification associated with authentication container is determined.", "internal account identification and sub-account information is added" (teaches storing/using an ID to identify the user/account/client component));
Gray does not explicitly disclose:
a payment application, adapted to:
store at least one client identity (ID) to identify the at least one second participant and/or a client component used by the at least one second participant;
allocate an amount to be paid for the responses outputted by the chat application, preferably without concurrently requiring payment of the amount, using the ID;
monitor a total allocated amount for the ID, in particular a sum of a plurality of said amounts; and transmit a payment request, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount.
Hutchison discloses:
a payment application, adapted to (Hutchison, Abstract: "virtual payment card application"):
store at least one client identity (ID) to identify the at least one second participant and/or a client component used by the at least one second participant (Hutchison, P[0089]: "buyer identification which identifies the buyer" (teaches storing/using client identity to identify the participant);
allocate an amount to be paid for the responses outputted by the chat application (Hutchison, P[0010]: "the buyer is automatically billed for the ordered good, service or content based on a virtual payment account" (teaches allocating an amount to be paid for a content/service/response transaction)), preferably without concurrently requiring payment of the amount (Hutchison, P[1060]: "waits for their billing cycle, e.g., monthly, and then charges the buyers for their purchases" (teaches deferred/non concurrent payment)), using the ID (Hutchison, P[0107]: "internal account identification associated with authentication container is determined" and "internal account identification and sub-account information is added" (teaches using the IS/account identification to associate the charge));
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]). Thus, the combination would allow Gray’s AI response system to associate user requests/responses with a client ID and allocate payment using Hutchison’s deferred payment account framework.
The combination of Gray and Hutchison does not explicitly disclose:
monitor a total allocated amount for the ID, in particular a sum of a plurality of said amounts; and
transmit a payment request, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount.
However, O’Donoghue discloses:
monitor a total allocated amount for the ID, in particular a sum of a plurality of said amount (O'Donoghue, P[0031]: "Transactions in which a user is required to pay a micropayment (i.e., such as a few pennies for access to "premium" content) are aggregated over time in a purchaser's computing device, such as a smartphone. Eventually the accumulated micropayment transactions are downloaded to a trusted payment authority for settlement." (teaches monitoring a total allocated amount/sum of plural allocated amounts because micropayment transactions are aggregated/accumulated over for later settlement)); and
transmit a payment request, the payment request for at least partially settling the total allocated amount assigned to the ID when the total allocated amount exceeds a predetermined threshold amount (O'Donoghue, P[0007]: "purchaser's computing device may determine that transaction data should be downloaded to the payment authority based upon one or more of a total amount of money in the stored transactions equals or exceeds a threshold value" (teaches threshold-triggered settlement/payment handling because stored transaction data is downloaded to the payment authority when the total stored amount equals or exceeds threshold.);
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and in further view of O’Donoghue. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), and O’Donoghue’s method of aggregation of micropayment transactions for later settlement when a stored total reaches a threshold (O’Donoghue, P[0011], P[0021]), thus, providing an AI chat response system with a payment application that stores a client ID, allocates charges, monitors a running total, and transmits a settlement request when the total exceeds a predetermined threshold.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy) in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1) in further view of O’Donoghue et al. (Hereinafter O’Donoghue) (US 20130054417 A1) and Weigle et al. (hereinafter Weigle) (US 8706639 B1) (US 8706639 B1) (for page numbers see attached copy).
Regarding claim 14, the combination of Gray, Hutchison, and O’Donoghue discloses the system according to claim 13.
Hutchison further discloses:
wherein the system is adapted to store certificates to authenticate the system (Hutchison, P[0072]:" The commerce gateway 52 digitally signs the public key to generate a digital certificate 126" (teaches storing/providing certificates for later transaction authorization), P[0015]: "Authentication can be performed by verification of a digital certificate" (teaches certificate-based authentication))
Hutchison, in combination with Gray and O’Donoghue, does not explicitly disclose:
against different content sources
However, Weigle discloses:
against different content sources (Weigle, P(7): "determining whether the user is allowed to access the content item based on the offer, the user's class, and a current timestamp." (teaches authentication/authorization for access to protected content items/sources)).
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and in further view of O’Donoghue and Weigle. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), O’Donoghue’s method of aggregation of micropayment transactions for later settlement when a stored total reaches a threshold (O’Donoghue, P[0011], P[0021]), and Weigle’s protected content access system for determining whether a user may access content based on an offer and access conditions (Weigle, P[0007]), thus, allowing the AI/payment system to authenticate and obtain protected content from different content sources while maintaining deferred payment and threshold based settlement.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (hereinafter Gray) (US 11769017 B1) (for page numbers see attached copy) in view of Hutchison et al. (hereinafter Hutchison) (US 20050102188 A1) in further view of O’Donoghue et al. (Hereinafter O’Donoghue) (US 20130054417 A1) and Kublickis (US 20070067297 A1).
Regarding claim 15, the combination of Gray, Hutchison, and O’Donoghue discloses the system according to claim 13.
The combination of Gray, Hutchison, and O’Donoghue does not disclose:
comprising:
a database for storing content pricing, wherein the chat application is adapted to provide pricing information for responding to the questions using the database, preferably wherein the database comprises a relationship between content and/or content sources and the pricing information.
However, Kublickis discloses:
comprising:
a database for storing content pricing (Kublickis, P[0613]: "digital content providers may open accounts with the marketplace, and then electronically post their wares to the stores, along with purchase prices or rental rates and terms" (teaches storing content pricing because provider content is posted with purchase prices/rental rates/terms)), wherein the chat application is adapted to provide pricing information for responding to the questions using the database (Kublickis, P[0334]: "appropriate queries against the content databases, using either affinity values, or keywords or phrases will generate result sets containing lists of links to relevant websites" (teaches using database to provide content/source information responsive to a query)), preferably wherein the database comprises a relationship between content and/or content sources and the pricing information (Kublickis, P[0613]: "digital content providers may open accounts with the marketplace, and then electronically post their wares to the stores, along with purchase prices or rental rates and terms" (teaches relationship between content/content providers and pricing information because provider wares are stored with corresponding purchase prices/rental rates/terms)).
It would have been prima facie obvious to one of ordinary skill in the art before the earliest filing date of the claimed invention to have modified Gray in view of Hutchison and Kublickis, and in further view of O’Donoghue. Doing so would have provided Gray’s LLM/search summary system, which receives a query and generates an LLM-based response for a client device (Gray, P[136]), with Hutchison’s known virtual payment account system in which a buyer is identified and later billed for ordered goods, services, or content (Hutchison, P[0049], P[0103]), with Kublickis’ known paid content marketplace n which websites provide content on a paid subscription, fee per item viewed, or fee per item downloaded basis (Kublickis, P[0184]), and O’Donoghue’s known technique for aggregating micropayment transactions and downloading transaction data for settlement when a stored total equals or exceeds a threshold (O’Donoghue, P[0011], P[0021]), thus, the combination would reduce repeated small payment processing by accumulating content-related charges and triggering settlement when the accumulated amount exceeds a predetermined threshold.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHASHIDHAR S MANOHARAN whose telephone number is (571)272-6772. The examiner can normally be reached M-F 8:00-4:00.
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/SHASHIDHAR SHANKAR MANOHARAN/Examiner, Art Unit 2655
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655
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