DETAILED ACTION
Status of the Claims
This office action is submitted in response to the amendment filed on 3/26/26.
Examiner notes that this application claims foreign priority to 2024-099958 (Japan).
Examiner further notes Applicant’s priority date of 6/20/24, which stems from the aforementioned application.
Claims 1-9 have been amended.
Claims 10-21 are new.
Therefore, claims 1-21 are currently pending and have been examined.
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 .
Claim Objections
Claims 10–15 are objected to as being in improper dependent claim form. Each of these claims describe "the information processing apparatus according to claim 1" (or according to claim 11, which depends from claim 1); however, claim 1, as amended, is now directed to an "information processing system," not an "information processing apparatus." While claim 1 recites an information processing apparatus as a component of the claimed system, claims 10–15 appear to claim the apparatus component in isolation rather than specifying a further limitation of the information processing system of claim 1. Applicant is required to correct claims 10–15 so that they properly depend from the information processing system, for example by reciting "The information processing system according to claim 1, wherein the information processing apparatus further..." or similar language that makes clear these claims are directed to the system of claim 1. Claims 16–21, which depend directly or indirectly from claims 11 and 12, are similarly affected and should be corrected accordingly.
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 1–21 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.
Step 1: Claims 1–21 are directed to patent-eligible subject matter categories under 35 U.S.C. § 101. Specifically, claim 1 recites an information processing system, and thus falls within the "machine" category. Claim 8 recites an information processing method, and thus falls within the "process" category. Claim 9 recites a non-transitory computer readable storage medium, and thus falls within the "article of manufacture" category. Claims 2–7 and 10–21 depend from claim 1 directly or indirectly and include all limitations thereof; accordingly, these claims likewise fall within the "machine" category. The claims satisfy Step 1.
Step 2A, Prong One: Independent claims 1, 8, and 9, in part, describe an invention comprising: identifying a plurality of personal agents each associated with a corresponding user among a plurality of users who are grouped; making an inquiry to the identified personal agents about information used to provide an advertisement to a group corresponding to the plurality of users; generating answers to the inquiry requests by the personal agents based on user information or message history; aggregating the answer information received from the personal agents; and generating advertisement selection information used to select an advertisement based on the information provided by the personal agents. As such, the invention is directed to the abstract idea of collecting user information, analyzing the user information, and targeting ads to users based on the data collection and analysis, which, pursuant to MPEP § 2106.04(a)(2), is aptly categorized as a method of organizing human activity (i.e., managing commercial interactions in the form of advertising and marketing activities). Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
Next, the aforementioned claims recite additional elements that are associated with the judicial exception, including: storing user information or message history of the corresponding user by each personal agent; transmitting inquiry requests to the plurality of personal agents via a network; and providing the advertisement selection information to an advertisement provider. The Examiner understands these limitations to be insignificant extra-solution activity. See Accenture Global Servs., GmbH v. Guidewire Software, Inc., 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Cf. Diamond v. Diehr, 450 U.S. 175, 191–192 (1981) ("[I]nsignificant post-solution activity will not transform an unpatentable principle into a patentable process."). Dependent claim 2 further discloses providing an advertisement to the group, and dependent claim 5 further discloses receiving settings to form a group — the Examiner likewise understands these limitations to be insignificant extra-solution activity.
The aforementioned claims also recite additional elements including: a plurality of terminal apparatuses; an advertisement distribution apparatus; an information processing apparatus communicably connected to those components via a network; a processor; and a memory. These limitations are recited at a high level of generality and appear to be nothing more than generic computer components used to implement the abstract idea. The claims further recite an identification unit, an inquiry unit, a generation unit, and a providing unit, as well as personal agents and a group agent. The Examiner notes that these "units" and agents are features of computer software — specifically, software functions executing on generic hardware — and not structural hardware components. Claims that amount to nothing more than instructions to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 223 (2014), 110 USPQ2d 1977, 1983 (2014).
Step 2A, Prong Two: Looking at the elements individually and in combination, the claims as a whole do not integrate the judicial exception into a practical application because they fail to: improve the functioning of a computer or a technical field; apply the judicial exception in the treatment or prophylaxis of a disease; apply the judicial exception with a particular machine; effect a transformation or reduction of a particular article to a different state or thing; or apply the judicial exception beyond generally linking the use of the judicial exception to a particular technological environment. Rather, the claims merely use generic computers, terminal apparatuses, networks, and software agents as tools to perform the abstract idea of collecting user information, analyzing it, and targeting ads, and/or add insignificant extra-solution activity to the judicial exception, and/or generally link the use of the judicial exception to a particular technological environment (e.g., generic terminal apparatuses and an advertisement distribution apparatus connected via a network). The distribution of generic software agents across generic hardware components — personal agents on terminal apparatuses coordinated by a group agent — does not constitute an improvement to computer functionality or any other technology. This arrangement describes how the abstract idea is implemented using generic software tools deployed on generic hardware, which is insufficient to integrate the judicial exception into a practical application. Accordingly, the claims do not integrate the judicial exception into a practical application, and the analysis proceeds to Step 2B.
Step 2B: The claims do not include additional elements sufficient to amount to significantly more than the judicial exception. The additional elements, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or any other technology, and their collective functions are merely facilitated by generic computer implementation.
Additionally, pursuant to the requirement under Berkheimer v. HP Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), the following citations are provided to demonstrate that the additional elements identified above as extra-solution activity are well-understood, routine, and conventional. See MPEP § 2106.05(d).
Storing data. Versata Dev. Grp., Inc. v. SAP Am., Inc., 793 F.3d 1306, 1333, 115 USPQ2d 1681, 1700 (Fed. Cir. 2015); Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat'l Ass'n, 776 F.3d 1343, 1347–48, 113 USPQ2d 1354, 1357–58 (Fed. Cir. 2014) (storing data in memory is well-understood, routine, and conventional).
Transmitting data over a network. Symantec Corp., 838 F.3d at 1321, 120 USPQ2d at 1362; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Thus, taken alone and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception, and claims 1–21 are ineligible under 35 U.S.C. § 101.
Claims 2–7 depend from claim 1 and include all limitations contained therein. These claims do not recite any additional elements sufficient to transform the abstract idea into patent-eligible subject matter. Specifically:
Claim 2 further limits the system to providing, to the group, an advertisement provided by the advertisement provider in response to provision of the advertisement selection information. This limitation describes additional extra-solution activity — delivering the selected advertisement to the group — and does not transform the nature of the claims.
Claims 3–4 further limit the generation unit to include an estimation processing unit that estimates a persona of the group (e.g., a common attribute or common interest among the plurality of users) and a generation processing unit that generates the advertisement selection information based on the estimated persona. These limitations add further detail to the abstract data analysis process — estimating group characteristics from collected user data — without adding any improvement to computer functionality or any other technology.
Claim 5 further limits the system to include a reception unit that receives settings to form a group of users for a group chat. This limitation describes additional extra-solution activity — receiving preliminary input data to configure the group — and does not transform the nature of the claims.
Claim 6 further limits the generation unit to include an estimation processing unit that estimates a situation of the group in a chat room using a generative artificial intelligence based on message histories of the users, and a generation processing unit that generates the advertisement selection information based on the estimated situation. The use of a generative artificial intelligence as a tool to process message histories and estimate group situational context amounts to an "apply it" limitation under MPEP § 2106.05(f), and does not amount to significantly more than the abstract idea.
Claim 7 further limits the personal agents to make an inquiry to the user when necessary and provide information based on the user's answer. This limitation adds further detail to the abstract data collection process — querying individual users for information — without adding any improvement to computer functionality or any other technology.
New claims 10–21 depend from claim 1 and include all limitations contained therein. These claims do not recite any additional elements sufficient to transform the abstract idea into patent-eligible subject matter. Specifically:
Claim 10 further limits the personal agents to include answer possibility information indicating whether an answer is possible for each type of predetermined information, set by the corresponding user. This limitation adds further detail to how user data access permissions are managed within the abstract data collection process, without adding any improvement to computer functionality or any other technology.
Claims 11–13 further limit the generation unit to use a generative artificial intelligence comprising a well-known large language model (claim 11), which may comprise a well-known transformer-based model (claim 12), accessed via a well-known application programming interface (claim 13). Using a generic AI model to receive collected user data as input, process that data, and estimate a group persona amounts to an "apply it" limitation under MPEP § 2106.05(f) — the generative artificial intelligence is simply used as a tool to carry out the abstract idea and does not add anything beyond the abstract idea itself.
Claim 14 further limits the system to a representative personal agent that collects answer information from other personal agents and outputs the collected information to the group agent. This limitation describes a particular data routing arrangement within the abstract aggregation process, without adding any improvement to computer functionality or any other technology.
Claim 15 further limits the generation unit to also generate the advertisement selection information based on a relationship between the users in the group, identified from a conversation history of chat messages. This limitation adds further categories of user data to be analyzed within the abstract targeted advertising process — user relationships — without adding any improvement to computer functionality or any other technology.
Claims 16–17 further limit the generative artificial intelligence to receive, as input information, the pieces of answer information from the personal agents together with instruction information, and to output information indicating the persona of the group (claim 16), wherein the instruction information includes a sentence for instructing estimation of the persona of the group (claim 17). These limitations further detail the inputs and outputs of the generic generative AI tool used as an "apply it" implementation of the abstract idea under MPEP § 2106.05(f), without adding any technical improvement.
Claims 18–19 further limit the large language model to be trained to estimate and output a next token from an input token string (claim 18), or to be a language model fine-tuned using a data set of pieces of information on users and personas (claim 19). These limitations describe well-known characteristics of a generic large language model architecture, without adding anything that amounts to significantly more than the abstract idea.
Claim 20 further limits the generative artificial intelligence to receive message histories and instruction information as input and to output information indicating the situation of the group in the chat room. This limitation further details the inputs and outputs of the generic generative AI tool used as an "apply it" implementation of the abstract idea under MPEP § 2106.05(f), without adding any technical improvement.
Claim 21 further limits the transformer-based model to comprise a well-known Generative Pre-trained Transformer. This limitation specifies a well-known AI architecture without adding anything that amounts to significantly more than the abstract idea.
Therefore, claims 1–21 are not drawn to eligible subject matter, as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 7-10, and 14-15 are rejected under 35 U.S.C. § 103 as being unpatentable over Ono et al. (US 11,475,336 B2) in view of Roundtree (US 2014/0344953 A1), and in further view of Sharma et al. (US 10,992,625 B2).
Claims 1, 8, and 9: Ono discloses an information processing system, method, and non-transitory computer readable storage medium comprising:
a plurality of terminal apparatuses, each terminal apparatus being used by a corresponding user among a plurality of users (Col. 5, ll. 9-24; FIG. 2. Ono discloses personal agent terminals 1 (1a, 1b, 1c) each used by a corresponding user—User A, User B, User C—implemented as smartphones, tablet terminals, wearable devices, and PCs.);
an information processing apparatus communicably connected to the plurality of terminal apparatuses via a network, the information processing apparatus being configured to coordinate data processing between a group agent and a plurality of distributed personal agents, wherein the group agent coordinates information sharing among the plurality of distributed personal agents (Col. 5, ll. 9-17; col. 3, l. 53 – col. 4, l. 9; FIG. 1; FIG. 2. Ono discloses group agent terminal 2 communicably connected to personal agent terminals 1a, 1b, 1c via network 4, and operating group agent 20 configured to provide group support by cooperating with personal agents 10A-10C of the grouped users, coordinating information collection and aggregation across the distributed personal agents.);
a processor; a memory storing instructions that, when executed by the processor, cause the processor to implement (Col. 9, ll. 1-10; FIG. 4. Ono discloses group agent terminal 2 comprising control unit 200 implemented as a CPU or microprocessor, and storage unit 260 storing programs and calculation parameters.);
an identification unit that identifies a plurality of personal agents each being associated with a corresponding user among the plurality of users who are grouped, and wherein each personal agent stores user information or message history of the corresponding user (Col. 15, ll. 1-27; col. 5, ll. 54-65; col. 6, ll. 5-40; FIG. 8, Steps S203-S209. Ono discloses the group agent 20 searching for personal agents present in a network area (Step S203), displaying a list of detected agents (Step S206), and registering selected agents in the group (Step S209), identifying personal agents each associated with a corresponding grouped user; each personal agent 10 stores user information in storage unit 160 including schedule information, action history, operation history, preference information, and personal determination criterion data.);
an inquiry unit that makes an inquiry to the plurality of personal agents that are identified by the identification unit about information that is used to provide an advertisement to a group corresponding to the plurality of users, wherein the inquiry unit transmits inquiry requests to the plurality of personal agents via a network, and wherein each personal agent, in response to the inquiry request, generates answer information based on the user information or message history stored by the personal agent (Col. 9, ll. 44-50; col. 12, ll. 44-48; FIG. 5, Steps S118-S133. Ono discloses the group support determining unit 204 and group schedule management unit 205 of the group agent terminal 2 transmitting inquiry requests via network 4 to the personal agent terminal 1 of each user (Steps S118, S124), wherein each personal agent consults the user's stored schedule information and returns a determination result to the group agent (Steps S121, S127, S130, S133).); and
a generation unit that generates advertisement selection information that is information that is used to select the advertisement by using pieces of information that are provided by the plurality of personal agents in response to the inquiry that is made by the inquiry unit, wherein the generation unit aggregates pieces of answer information received from the plurality of distributed personal agents to generate the advertisement selection information for the group (Col. 13, ll. 42-65; col. 14, ll. 1-10; FIG. 5, Steps S130-S136. Ono discloses the group agent 20 receiving determination results from the father agent (Step S130) and child agent (Step S133) and aggregating the responses to generate a group-level support outcome (Step S136).)
Ono does not appear to explicitly disclose an advertisement distribution apparatus communicably connected to the information processing apparatus via a network, generating advertisement selection information for use in selecting advertisements, or a providing unit that provides the advertisement selection information to an advertisement provider.
Roundtree, however, discloses an advertisement distribution apparatus communicably connected to the information processing apparatus via a network; a generation unit that generates advertisement selection information comprising persona demographic characteristics used to select advertisements; and a providing unit that provides the advertisement selection information that is generated by the generation unit to an advertisement provider (Paragraphs 0056, 0120, 0121, 0134. Roundtree discloses an audience engine 214/1220 that administers user persona data and interfaces with advertisers 1240 and advertising companies 1260 via network, constituting an advertisement distribution apparatus; the audience engine generating advertisement selection information comprising persona demographic tags and characteristics used to match advertisements to an identified audience (Paragraphs 0120, 0121); and the audience engine providing persona demographic data to advertisers 1240 and advertising companies 1260, constituting a providing unit that provides advertisement selection information to an advertisement provider (Paragraph 0134).)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to incorporate the advertisement distribution functionality of Roundtree into the distributed personal agent architecture of Ono. One would have been motivated to do this in order to monetize the group preference data already aggregated by Ono's personal agent system through Roundtree's persona-based advertisement targeting mechanism, providing the predictable benefit of enabling targeted advertisement delivery to groups based on the aggregated user preference data already collected by Ono's distributed personal agents.
The Ono/Roundtree combination does not appear to explicitly disclose each personal agent operating as a software agent function within a chat application on a respective terminal apparatus of the corresponding user.
Sharma, however, discloses each personal agent operates as a software agent function within a chat application on a respective terminal apparatus of the corresponding user, and wherein each personal agent stores user information or message history of the corresponding user (Col. 5, ll. 17-35; col. 8, ll. 4-15; col. 9, ll. 28-50; col. 14, ll. 7-11; FIG. 4. Sharma discloses assistant interface 412, which "may be logically considered a 'plugin' associated with messaging app 112" and which "may be directly incorporated into messaging app 112," operating on a per-user client device (410.1 for User A, 410.2 for User B) on a respective terminal apparatus. Sharma further discloses that the assistant interface stores per-user learned data including context, prior inputs, and input-to-command mappings on a per-user basis.)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to incorporate the advertisement distribution functionality of Roundtree and the chat application agent integration of Sharma into the distributed personal agent architecture of Ono. One would have been motivated to do this in order to monetize the group preference data already aggregated by Ono's personal agent system through Roundtree's persona-based advertisement targeting mechanism, and to implement each personal agent as a software agent function within the user's existing chat application as taught by Sharma, thereby enabling each personal agent to access message history from the chat application and operate within the user's established communication interface on the respective terminal apparatus.
Claim 2: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Roundtree further discloses a system wherein the providing unit provides, to the group, an advertisement that is provided by the advertisement provider in response to provision of the advertisement selection information to the group (Paragraph 0134. Roundtree discloses that once the audience engine 1220 identifies personas matching advertiser demographic criteria, ads 1256 are supplied from advertising companies 1260 to the audience engine 1220, which forwards the advertisements to the addresses or identifiers associated with the identified personas.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 3: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Roundtree further discloses a system wherein the generation unit includes an estimation processing unit that estimates a persona of the group based on pieces of information that are provided by the plurality of personal agents in response to an inquiry that is made by the inquiry unit; and a generation processing unit that generates the advertisement selection information based on the persona of the group that is estimated by the estimation processing unit (Paragraphs 0120, 0121, 0134. Roundtree discloses an audience engine 1220 that receives persona information derived from user preference inputs—constituting pieces of information provided by users—and generates advertisement selection information based on the composite persona demographic characteristics matched against advertiser criteria.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 4: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Roundtree further discloses a system wherein the estimation processing unit estimates, as the persona of the group, one of a common attribute and a common interest among the plurality of users (Paragraph 0155. Roundtree discloses an audience engine 1220 that produces an audience of users whose personas share desired demographic characteristics such as "coffee drinkers who live in Seattle and who are over 30 years old," constituting common attributes and common interests among a plurality of users.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 5: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Ono further discloses a system further comprising a reception unit that receives setting to form a group of the plurality of users for a group chat among the plurality of users (Col. 15, ll. 1-27; FIG. 8, Steps S203-S209. Ono discloses the group agent 20 searching for personal agents present in a network area (Step S203), displaying a list of detected agents (Step S206), and registering selected personal agents in the group (Step S209), thereby receiving a setting to form a group of users.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 7: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Ono further discloses a system wherein each of the personal agents makes an inquiry to the user if it is possible to provide information corresponding to the inquiry, and provides the information corresponding to the inquiry based on an answer that is given by the user (Col. 13, ll. 55-65; FIG. 5, Steps S127, S133. Ono discloses the child agent (personal agent 10C) checking with the child user by voice conversation whether the child can stop by the supermarket, and the child agent providing the user's confirmation result to the family agent based on the answer given by the user.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 10: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Ono further discloses a system wherein each personal agent has answer possibility information that indicates whether or not an answer is possible for each type of predetermined information, and wherein the answer possibility information is set by the corresponding user of the terminal apparatus that includes the personal agent (Col. 9, ll. 56-65; col. 10, ll. 1-15. Ono discloses that the user of each personal agent terminal 1 sets in advance which personal determination criteria are "closed" and not transmissible to the group agent, such that each personal agent has answer possibility information indicating whether or not providing each type of predetermined information is possible, configurable by the corresponding user.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 14: The Ono/Roundtree/Sharma combination discloses those limitations cited above. Ono further discloses a system wherein a representative personal agent among the plurality of personal agents collects pieces of answer information from other personal agents among the plurality of personal agents and outputs the collected pieces of answer information to the group agent (Col. 13, ll. 55-65; FIG. 5, Steps S130-S133. Ono discloses a cooperative personal agent architecture in which the child agent (personal agent 10C), upon confirming availability with the child user, relays its schedule confirmation to the family agent (group agent) alongside the father agent's response, operating within a relay structure of the agent network. It would have been obvious to configure one representative personal agent to collect and relay answer information from peer personal agents to the group agent, as this represents a well-known hierarchical data collection topology for reducing direct communication overhead between distributed agents and a central coordinator.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claim 15: The Ono/Roundtree/Sharma combination discloses those limitations cited above.
Ono further discloses a system wherein the generation unit further generates the advertisement selection information based on a relationship between the users in the group, wherein the relationship is identified based on a conversation history of chat messages between the users (Col. 5, ll. 54-65; col. 4, ll. 1-9. Ono discloses the group agent 20 using user information gathered from personal agents, including action histories, to understand group member relationships for group support decisions.)
Roundtree further discloses a system wherein the generation unit further generates the advertisement selection information based on a relationship between the users in the group (Paragraphs 0120, 0121. Roundtree discloses using persona information derived from user preference and interaction data to generate advertisement selection information for users with shared characteristics.)
Sharma further discloses a system wherein the relationship is identified based on a conversation history of chat messages between the users (Col. 9, ll. 28-50. Sharma discloses that the assistant interface stores message history from user conversations and uses this history as contextual input reflecting user relationships within a chat session.)
The rationale for combining Ono, Roundtree, and Sharma is articulated above and is reincorporated herein by reference.
Claims 6, 11-13, and 16-21 are rejected under 35 U.S.C. § 103 as being unpatentable over Ono/Roundtree/Sharma in view of Davish (US 2025/0005297 A1).
Claim 6: The Ono/Roundtree/Sharma combination discloses those limitations cited above, but does not appear to explicitly disclose an estimation processing unit that estimates a situation of the group in a chat room by using a generative artificial intelligence based on message histories.
Davish, however, discloses a system wherein the generation unit includes an estimation processing unit that estimates a situation of the group in a chat room by using a generative artificial intelligence based on message histories of the plurality of users U in the chat room of the group chat; and a generation processing unit that generates the advertisement selection information based on the situation that is estimated by the estimation processing unit (Paragraphs 0029, 0031, 0053, 0054. Davish discloses a system employing a large language model (generative artificial intelligence) to analyze chat history (message histories) from users in a chat interaction to understand the current conversational situation and generate appropriate responses, wherein "the natural language instructions may be presented to the LLM along with other context such as the message history and metadata" (Paragraph 0029), and goal detection "involves prompting an LLM, using prompts that are constructed dynamically based on templates... interpolating aspects of the chat history 140 and the bot configuration 150 into the prompt" (Paragraphs 0053, 0054). Roundtree teaches that generating advertisement selection information based on an estimated group situation is a well-known application of aggregated user preference data. Paragraph 0120, 0134.)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to incorporate the generative AI large language model analysis of Davish into the combined Ono/Roundtree/Sharma system to estimate the situation of the group from chat room message histories. One would have been motivated to do this in order to leverage Davish's well-known LLM-based conversational analysis technique to accurately derive group situation information from chat message histories, thereby providing more accurate advertisement selection information for group targeting pursuant to Roundtree's advertisement distribution mechanism.
Claim 11: The Ono/Roundtree/Sharma combination discloses those limitations cited above, but does not appear to explicitly disclose the generation unit using a generative artificial intelligence comprising a large language model to estimate the persona of the group.
Davish, however, discloses a system wherein the generation unit uses a generative artificial intelligence to estimate a persona of the group based on the pieces of answer information received from the plurality of personal agents, wherein the generative artificial intelligence comprises a large language model (Paragraphs 0026, 0028, 0029. Davish defines a "large language model" or LLM as "an artificial intelligence system that is designed to process and generate realistic human text, being trained on a large dataset of human-authored input and language data," and discloses a system employing such an LLM to process user-provided information and generate contextually appropriate outputs reflecting user intent and situation.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 12: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the large language model comprises a transformer-based model (Paragraph 0155. Davish discloses model selection including "gpt-3.5-turbo" (OpenAI), which is a well-known transformer-based generative model.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 13: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above.
Davish further discloses a system wherein the generation unit accesses the generative artificial intelligence via an application programming interface (Paragraphs 0030, 0064. Davish discloses that the chat bot 110 is accessed via an application programming interface (API) 115 that processes conversation interactions, and that the particular instruction set includes "instructions for performing a call to an application programming interface.")
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 16: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the generation unit inputs, as input information to the generative artificial intelligence, information that includes the pieces of answer information received from the plurality of personal agents and instruction information, and causes the generative artificial intelligence to output information that indicates the persona of the group (Paragraphs 0053, 0054, 0160. Davish discloses the LLM receiving a prompt comprising both the chat history data—analogous to pieces of answer information from users—and instruction information, causing the LLM to output a contextually appropriate response indicating the user's current goal or persona. Table 1 of Davish further shows prompt components comprising both conversation data and instruction information, the combination of which causes the LLM to generate an output characterizing the relevant situation. Paragraph 0160.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 17: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the instruction information includes a sentence for instructing estimation of the persona of the group (Paragraphs 0025, 0160. Davish defines a "prompt" as "a text input or instruction designed to guide a large language model (LLM) in generating contextually appropriate responses," and discloses prompt components comprising instruction sentences—such as "You are a helpful assistant who suggests responses to online reviews for {{Entity Name}}"—that guide the LLM in generating outputs aligned with specified estimation instructions.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 18: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the large language model is trained to estimate and output a next token from an input token string (Paragraph 0095. Davish discloses that the LLM generates streaming responses by sending "one event per token from the response," wherein the token-by-token output reflects the LLM's underlying next-token prediction architecture.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 19: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the generative artificial intelligence is a language model that is trained by fine-tuning using a data set of pieces of information on users and personas (Paragraph 0155. Davish discloses "in-house models trained on specific businesses" as an alternative to commercially available models, constituting language models fine-tuned on domain-specific datasets of user and business information analogous to pieces of information on users and personas.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 20: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the generation unit inputs, as input information to the generative artificial intelligence, information that includes the message histories and instruction information, and causes the generative artificial intelligence to output information that indicates the situation of the group in the chat room (Paragraphs 0029, 0053, 0054, 0160. Davish discloses the LLM receiving prompts that include both the chat history—message histories—and goal/instruction information, causing the LLM to output information indicating the current state of the conversation and the user's situational context.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Claim 21: The Ono/Roundtree/Sharma/Davish combination discloses those limitations cited above. Davish further discloses a system wherein the transformer-based model comprises a Generative Pre-trained Transformer (Paragraph 0155. Davish discloses "gpt-3.5-turbo" (OpenAI), which is a Generative Pre-trained Transformer (GPT) model.)
The rationale for combining Ono, Roundtree, Sharma, and Davish is articulated above and is reincorporated herein by reference.
Other Relevant Prior Art
Though not relied upon in the aforementioned rejections, the following references are nevertheless deemed to be relevant to Applicant’s disclosures:
Kothandaraman et al. (20250209348), directed to an intelligent virtual assistant for conversing with multiple users.
Ryan et al. (20250041736), directed to processing devices and methods for generating a group of users.
Peris et al. (12499470), directed to an intelligent electronic advertisement generation and distribution method.
Ciano et al. (11886823), directed to a method for dynamically constructing and configuring a conversational agent learning model.
Publicover et al. (12506918), directed to a method and system for providing customized entertainment content.
Response to Arguments
Applicant argues that the amended claims recite an "unconventional arrangement" of known elements sufficient to provide an inventive concept under BASCOM Global Internet Services, Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016), specifically pointing to the multi-tier distributed architecture comprising a group agent coordinating distributed personal agents that operate locally on each user's terminal apparatus, store user information locally, and generate answer information in response to inquiry requests. These arguments are not persuasive.
BASCOM held that an inventive concept can reside in "the non-conventional and non-generic arrangement of known, conventional pieces," but that holding requires the arrangement to impose a meaningful limit on the claims beyond merely implementing the abstract idea using a computer. Id. at 1350. Applicant's characterization of the distributed personal agent architecture as "unconventional" does not establish the requisite meaningful limit. As set forth in the rejection, the personal agents, group agent, terminal apparatuses, processor, memory, and network connections are each generic computer components recited at a high level of generality. The fact that these generic components are arranged in a distributed configuration does not, without more, render the arrangement non-conventional—distributed software agent architectures were well-known in the art at the time of the invention. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225 (2014) ("[s]imply appending conventional steps, specified at a high level of generality, [is] not enough to supply an inventive concept.").
Applicant further argues that the claims are directed to a specific technical architecture for "aggregating information from multiple sources while maintaining distributed data storage and processing." However, collecting user information from multiple distributed sources, storing that information locally, transmitting it to a central processor upon request, and aggregating the results are each conventional data processing functions. The claimed architecture implements these conventional functions across multiple devices without improving computer functionality or achieving any result beyond the abstract idea of collecting and analyzing user preference data to identify and deliver targeted advertisements. Arranging conventional computer components in a distributed topology to perform conventional data processing operations does not supply significantly more than the abstract idea itself under Alice Step 2B.
Furthermore, BASCOM is distinguishable on its facts. In BASCOM, the claims required installation of a filtering tool at a specific network location—the ISP—rather than on local devices or end servers, which represented a specific technical implementation that improved the prior art filtering technology. Here, Applicant does not identify a specific technical problem in the prior art that the claimed distributed agent architecture solves, nor does Applicant explain how the architecture improves computer functioning. The specification characterizes the invention as enabling group advertisement targeting using personal agent-collected user data—a functional outcome, not a technical improvement to computing.
Accordingly, Applicant's arguments under 35 U.S.C. § 101 have been fully considered but are not persuasive. The rejection of claims 1-21 under 35 U.S.C. § 101 is therefore maintained.
Finally, Applicant's arguments regarding the rejection under § 103 have been fully considered, but are rendered moot in view of the new grounds of rejection, which were necessitated by the amendments.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER BUSCH whose telephone number is (571)270-7953. The examiner can normally be reached M-F 10-7.
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/CHRISTOPHER C BUSCH/Examiner, Art Unit 3621
/WASEEM ASHRAF/Supervisory Patent Examiner, Art Unit 3621
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