DETAILED ACTION
Notice of 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 .
Response to Arguments
Applicant’s amendments and arguments filed 12/18/2025, with respect to claim(s) 1-20 have been fully considered. Applicant amended independent claims 1, 10 and 16.
Applicant’s arguments in pages 11-12, filed 12/18/2025, with respect to 35 U.S.C 101 rejections of Claims 1-6, 8-13 and 15-20 have been fully considered but they are not persuasive. Applicant amended the independent claims and argued that “the amended limitation, inserting the one or more generated modifications into the content item without user interaction prompting the predicted content, cannot be performed in the human mind, and is a practical application, at least because it improves the functioning of a computer”. Examiner respectfully disagrees. Examiner is not certain how inserting modifications to a content item can be a practical application and an improvement to the functioning of a computer, “without user interaction” can be similar to another human listening to a conversation and providing their modification whereas the original user did not request help or assistance. Applicant further argued that “the claimed methods, systems, and non-transitory computer-readable storage media automatically populate a content item with content by predicting relevant content that the user account would otherwise manually add to the content item. This technical feature is a new computing capability that has not been available via prior systems”. Examiner respectfully disagrees. Auto populating some information based on some predicted/ previous information, is not a novel feature. Throughout the amended claim 1, no specialized or unique technology or idea have been mentioned. The use of a computer does not preclude performance of the invention via pen and paper or in a person’s mind. Also, the use of a computer or other machinery in its ordinary capacity to perform a task or simply adding a general purpose computer to an abstract idea, does not integrate a judicial exception into a practical application. Here the computer is the machine that is merely an object on which the method operates, which does not integrate the exception into a practical application or provide significantly more. Thus, 35 U.S.C 101 rejections of Claims 1-6, 8-13 and 15-20 have been maintained.
Applicant’s arguments filed 12/18/2025, with respect to claim(s) 1-20, under 35 U.S.C. 103 have been fully considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1-6, 8-13 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The Independent claims 1, 10 and 16 recite “detecting client device activity in relation to a content item associated with a user account of a content management system”; “determining, based on the client device activity and an activity history associated with the user account, an input prediction defining one or more predicted client device inputs to be provided to a client device”; “the one or more predicted client device inputs corresponding to content edits that the user account is predicted to add to the content item”; “generating, based on the input prediction and without receiving client device input,” “predicted content to add to the content item in response to the one or more predicted client device inputs, the predicted content comprising one or more generated modifications for the content item”; “and inserting the one or more generated modifications into the content item without user interaction prompting the predicted content”. The limitations above as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process, as this could be performed in the human mind or with the aid of pen and paper.
The limitation of " detecting ... ", "determining ... ", “generating..” , “inserting..” as drafted covers mental activities. More specifically, a human can detect a device activity regarding some content, determine one or more predicted input based on the input and history, the predicted input might be related to some modification to the content, generate ( write in the paper) the predicted input and insert the modified content manually. Some of the modification idea might come from the another human, not from the original user. All the steps above are examples of observation and evaluation that could be performed in the human mind or with the aid of pencil and paper.
The claims recite the additional limitation of a “processor”, “ non transitory computer readable storage medium” , for performing the method. All those are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. The current specification in paragraphs [0147],[0152],[0153] clearly specifies them as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The claims as drafted, are not patent eligible.
Thus, taken alone, the additional elements do not amount to significantly more than the above identified judicial exception (the abstract idea). 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 improves any other
technology. Their collective functions merely provide conventional computer implementation. Claims 1, 10
and 16 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without
significantly more than the abstract idea.
Claim 2 recites the additional limitation of “wherein determining the input prediction defining the one or more predicted client device inputs comprises analyzing data signals collected by connectors from software tools associated with the user account” , where analyzing data signals such as text, audio can be done in human mind or with the aid of pen and paper. Connectors, software tools are additional elements as shown in specification in para. [0059], [0106], which is not sufficient to amount to significantly more than the judicial exception. The claim 2 as drafted, is not patent eligible.
Claim 3 recites “wherein generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises processing the data signals collected by the connectors as a prompt through a large language model ”. Processing the data signal, which can be a text and presenting as a prompt with the help of language model, which can be just a knowledge source, is an evaluation, observation and could be performed in the human mind or with the aid of pen and paper. Large language model is an additional element, as shown in specification, para.[0036],can be a machine learning model or neural model, which is not sufficient to amount to significantly more than the judicial exception. The claim as drafted, is not patent eligible.
Claim 4 recites “wherein generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises locating sample content from a repository and modifying the sample content based on the client device activity and the activity history”, where human can locate sample content by observation and modify the content, such as any saved information on the device, based on the activity history, manually with the aid of pen and paper. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception, as claim 4 does not recite any additional limitations. The claim as drafted, is not patent eligible.
Claims 5 and 12 recite “wherein inserting the predicted content within the content item without user interaction prompting the predicted content comprises: automatically adding the predicted content to the content item”; “saving the content item as modified with the added predicted content”; “and providing, for display via a user interface of the client device, a notification that the predicted content was added to the content item”. Human can add any predicted content and save the content, after observation and evaluation, with the aid of pen and paper. Human can also notify the modification/ addition of content verbally to the user. Displaying via a user interface of the client device is a post solution activity, which is not sufficient to amount to significantly more than the judicial exception. The claims 5 and 12 as drafted, are not patent eligible.
Claims 6, 13 and 19 recite the additional limitations of “wherein: detecting the client device activity in relation to the content item comprises detecting that the user account begins a composite action”; “determining the input prediction comprises determining, based on the user account beginning the composite action, that the content item relates to the composite action”; “generating the predicted content to add to the content item comprises generating draft content for a first draft of the content item”; “and inserting the predicted content within the content item comprises inserting the draft content into a template file for the content item” . Detecting that the user is doing multiple action from the device activity, determining that the input predicted content item is related to the multiple actions, generating draft and template of the content are observation, evaluation and could be performed in the human mind or with the aid of pen and paper. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception, as claims 6, 13 and 19 do not recite any additional limitations. The claims as drafted, are not patent eligible.
Claim 8 recites “further comprising: determining that a composite action of the user account is paused or complete”; “and generating a summary content item comprising a summary of the at least one user interface element”. The status of the actions in a user’s account in a user’s device can be find out by looking at the device and observing the indications/notifications which shows the status of the actions such as complete, incomplete, in progress etc. User can generate a summary of different types of notifications ( user interface element), such as how many “complete” notifications, how many “on hold” or “paused” notifications, which can be done by observations and by using pen and paper. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception, as claim 8 does not recite any additional limitations. The claim as drafted, is not patent eligible.
Claims 9 and 15 recite “further comprising: determining that a composite action of the user account is paused or complete”; “generating, for additional user accounts of the content management system, an update notification indicating a completion status for the composite action”; “and providing, without additional interaction by the user account, the update notification to the additional user accounts for display via user interfaces of client devices associated with the additional user accounts”. The status of the actions in a user’s account in a user’s device can be find out by looking at the device and observing the indications/notifications which shows the status of the actions such as complete, incomplete, in progress etc. Same type of status indication can be find out for additional user’s account by observing the device. Displaying the notifications is a post solution activity, which is not sufficient to amount to significantly more than the judicial exception. The claims as drafted, are not patent eligible.
Claim 11 recites the additional limitation of “wherein generating the predicted content to add to the content item comprises processing, as a prompt through a large language model, data signals collected by connectors from software tools associated with the user account” . Processing the data signal, which can be a text and presenting as a prompt with the help of language model, which can be just a knowledge source, is an evaluation, observation and could be performed in the human mind or with the aid of pen and paper. Connectors, software tools as shown in specification in para. [0059], [0106], also large language model, as shown in specification, para.[0036], which can be a machine learning model or neural model, are additional elements, which are not sufficient to amount to significantly more than the judicial exception. The claim 11 as drafted, is not patent eligible.
Claim 17 recites the additional limitation of “wherein: determining the input prediction defining the one or more predicted client device inputs comprises analyzing data signals collected by connectors from software tools associated with the user account”; “and generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises processing the data signals collected by the connectors as a prompt through a large language model” , where processing/ analyzing data signals such as text, audio and presenting as a prompt with the help of language model, which can be just a knowledge source, is an evaluation, observation and could be performed in the human mind or with the aid of pen and paper.. Connectors, software tools as shown in specification in para. [0059], [0106], also large language model, as shown in specification, para.[0036], which can be a machine learning model or neural model, are additional elements, which are not sufficient to amount to significantly more than the judicial exception. The claim 17 as drafted, is not patent eligible.
Claim 18 recites “wherein generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises identifying sample content within another content item and modifying the sample content based on the client device activity and the activity history”, where locating/ identifying sample content within another content, such as identifying any saved document within a saved set of documents on the device, and changing/editing/modifying the identified saved document based on how recently it has been used by the user, could be done by a human manually or with the aid of pen and paper. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception, as claim 18 does not recite any additional limitations. The claim as drafted, is not patent eligible.
Claim 20 recites “wherein the instructions, when executed by the at least one processor, further cause the computing device to provide the template file with the draft content for the first draft of the content item for display via a user interface of the client device”, where providing the template file with draft content for presentation can be done with the aid of pen and paper. Display via the client device is post solution activity, which is not sufficient to amount to significantly more than the judicial exception. The claim as drafted, is not patent eligible.
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 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 of this title, 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 1-6, 9-13 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dicklin et al. ( US 20250103867 A1), hereinafter referenced as Dicklin, in view of BrockSchmidt et al. ( US 20200104102 A1), hereinafter referenced as BrockSchmidt, further in view of Kulkarni et al. (US 11567812 B2), hereinafter referenced as Kulkarni.
Regarding Claim 1, Dicklin teaches a computer-implemented method comprising:
detecting client device activity in relation to a content item associated with a user account of a content management system ( Dicklin: Para.[0034],[0041],Fig. 1, the platform 100 which include a cloud content management system 110, detect an activity from user’s device ( such as text from client devices from clients 140-1,..,140-m), such as typing “passport” ( content item). Para.[0036], user’s cloud storage ( user’s account) on the cloud based content management platform consists of accessible, relevant documents) ;
determining, based on the client device activity and an activity history associated with the user account, an input prediction defining one or more predicted client device inputs to be provided to a client device ( Dicklin: Para.[0175], Fig. 11, based on user inputting text data “ file size” into a user interface of the platform 100 and activity during the past week ( history), at block 1126, the real-time anticipation subsystem 116 may input the paragraph selected in block 1124);
Dicklin while teaching the method of claim 1, fails to explicitly teach the claimed, the one or more predicted client device inputs corresponding to content edits that the user account is predicted to add to the content item; generating, based on the input prediction and without receiving client device input, predicted content to add to the content item in response to the one or more predicted client device inputs, the predicted content comprising one or more generated modifications for the content item; and inserting the one or more generated modifications into the content item without user interaction prompting the predicted content.
However, BrockSchmidt does teach the claimed, the one or more predicted client device inputs corresponding to content edits that the user account is predicted to add to the content item (BrockSchmidt: Para.[0023], Fig. 1 illustrates a content editor 100 in communication with end user computing devices 106, 108, 110 and is connected to, or has access to, a store of change representations 102. Para. [0026], When a programmer writes a code snippet, the content editor computes a representation of the code snippet. The editing tool finds a cluster of similar code snippets. One of the looked up change representations is selected and input to the trained neural network with the representation of the code snippet. The neural network then computes a predicted code snippet which is a predicted second version of the code snippet after having the change of the change representation applied. The predicted code snippet is then presented to the user at a graphical user interface or other user interface so that the programmer can input the predicted code snippet to the computing device);
generating, based on the input prediction [and without receiving client device input], predicted content to add to the content item in response to the one or more predicted client device inputs, the predicted content comprising one or more generated modifications for the content item ( BrockSchmidt: Para.[0047],[0048], Fig. 6, the content editor selects a change representation ( possible change to the content items), input to the neural network and generates predicted modified/edited content item);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate BrockSchmidt’s teaching of automated content editor, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve functioning of a computing-device since edits to content items are predicted and a user is able to input predicted edits to the computing device which saves burden of user input and gives an improved human to machine interaction.( BrockSchmidt, Para.[0020],[0021]).
Dicklin in view of BrockSchmidt while teaching the method of claim 1, fail to explicitly teach the claimed, generating, based on the input prediction and without receiving client device input, predicted content to add to the content item in response to the one or more predicted client device inputs, and inserting the one or more generated modifications into the content item without user interaction prompting the predicted content.
However, Kulkarni does teach the claimed, generating, based on the input prediction and without receiving client device input, predicted content to add to the content item in response to the one or more predicted client device inputs ( Kulkarni: Column 12, lines 33-47, Fig. 2, sequential acts of saving edits ( content to add) after creating/opening a document without a prior indication, in accordance with the predicted activity event 206 ),
and inserting one or more generated modifications into the content
item without user interaction prompting the predicted content ( Kulkarni: Column 16, lines 22-33, Column 36, lines 7-12, Fig. 2, user activity sequence system 104 may auto populate ( without user interaction) one or more entry fields of the previous documents to reflect content for the next project based on the predicted activity events 206 which indicates that the user account is initiating a new contract-based project. The content management system can have edited/modified contents).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method, taught by Dicklin in view of BrockSchmidt, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claim 10 is system claim comprising: at least one processor ( Dicklin: Para.[0193], Fig.14, processor 1402); and at least one non-transitory computer-readable storage medium comprising instructions that, when executed by the at least one processor, cause the system to (Dicklin: Para.[0195], Fig. 14, non-transitory machine-readable storage medium 1424), perform the steps in method claim 1 above and as such, claim 10 is similar in scope and content to claim 1 and therefore, claim 10 is rejected under similar rationale as presented against claim 1 above.
Claim 16 is non-transitory computer-readable storage medium claim comprising instructions that, when executed by at least one processor, cause a computing device to ( Dicklin: Para.[0193], Fig.14, processor 1402. Para.[0195], Fig. 14, non-transitory machine-readable storage medium 1424), perform the steps in method claim 1 above and as such, claim 16 is similar in scope and content to claim 1 and therefore, claim 16 is rejected under similar rationale as presented against claim 1 above.
Regarding Claim 2, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, wherein determining the input prediction defining the one or more predicted client device inputs comprises analyzing data signals collected by connectors from software tools associated with the user account (Kulkarni: Column 16, lines 8-17, software tools can be applied to content creation associated with user account corresponds to a content creator segment based on the predicted activity event 206. Column 33, lines 50-67, Fig. 9 illustrates computing device 900 ( content management system may comprise one or more device such as 900) and the communication interface 908, 910 ( to collect data signals to be analyzed)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Regarding Claim 3, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 2. Dicklin further teaches, wherein generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises processing the data signals collected by the connectors as a prompt through a large language model ( Dicklin: Para.[0050], Fig. 1, the real-time anticipation subsystem 116 may be configured to predict, in real-time, a user's interests and generate generative MLM prompts. Para.[0054], the generative MLM 120 may include a machine learning model configured to predict the next word and may include a transformer- based large language model (LLM). Para. [0194], network interface 1408).
Claim 11 is system claim performing the steps in method claim 3 above and as such, claim 11 is similar in scope and content to claim 3 and therefore, claim 11 is rejected under similar rationale as presented against claim 3 above.
Regarding Claim 4, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, wherein generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises locating sample content from a repository and modifying the sample content based on the client device activity and the activity history ( Kulkarni: Column 23, lines 44-66, Fig. 5, user activity sequence system 104 may sample raw event data for a percentage of user accounts of the content management system 103 or may sample raw event data for a predetermined time period. At pre-processing act 502, the user activity sequence system 104 may filter raw event data ( remove unreliable data or filter out duplicates)) .
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claim 18 is non-transitory computer-readable storage medium claim performing the steps in method claim 4 above and as such, claim 18 is similar in scope and content to claim 4 and therefore, claim 18 is rejected under similar rationale as presented against claim 4 above.
Regarding Claim 5, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, wherein inserting the predicted content within the content item without user interaction prompting the predicted content comprises: automatically adding the predicted content to the content item ( Kulkarni: Column 12, lines 33-42, user activity sequence system 104 may perform workflow automation as an automatic response to determining the predicted activity event 206. The user activity sequence system 104 may surface a prompt in the client application 108a to share the document after the user activity sequence system 104 receives an indication that edits to a new/opened document at the client device 106a have been saved in the content management system 103);
saving the content item as modified with the added predicted content ( Kulkarni: Column 12, lines 33-47, user activity sequence system 104 receives an indication that edits to a new/opened document at the client device 106a have been saved in the content management system 103);
and providing, for display via a user interface of the client device, a notification that the predicted content was added to the content item ( Kulkarni: Column 7, lines 50-57, client applications can present or display information to respective users associated with the client devices, including information or content responsive to a predicted activity event such as view, annotate, edit, send, or share a digital content item).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claim 12 is system claim performing the steps in method claim 5 above and as such, claim 12 is similar in scope and content to claim 5 and therefore, claim 12 is rejected under similar rationale as presented against claim 5 above.
Regarding Claim 6, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, wherein: detecting the client device activity in relation to the content item comprises detecting that the user account begins a composite action ( Kulkarni: Column 29, lines 46-58, Fig. 8,act 802 shows identification of sequence of activity events ( composite action) associated with a user account ( or a group of user accounts) of a content management system);
determining the input prediction comprises determining, based on the user account beginning the composite action, that the content item relates to the composite action ( Kulkarni: Column 30, lines 28-47, Fig. 8, at 808, performing the action based on the predicted activity event, display on a first and second client device associated with the first and second user account, a first and second action suggestion related to a digital content item accessible by the group of user accounts, wherein the action suggestions are based on the first predicted activity event );
generating the predicted content to add to the content item comprises generating draft content for a first draft of the content item ( Kulkarni: Column 13, lines 20-22, generating draft content);
and inserting the predicted content within the content item comprises inserting the draft content into a template file for the content item ( Kulkarni: Column 16, lines 22-33, the user activity sequence system 104 may auto populate ( inserting) one or more entry fields of a template with the previous documents/ mining digital content data);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claim 13 is system claim performing the steps in method claim 6 above and as such, claim 13 is similar in scope and content to claim 6 and therefore, claim 13 is rejected under similar rationale as presented against claim 6 above.
Claim 19 is non-transitory computer-readable storage medium claim performing the steps in method claim 6 above and as such, claim 19 is similar in scope and content to claim 6 and therefore, claim 19 is rejected under similar rationale as presented against claim 6 above.
Regarding Claim 9, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, further comprising: determining that a composite action of the user account is paused or complete ( Kulkarni: Column 15, lines 14-22, the predicted activity event 206 may indicate that a user account has completed work on digital content items and/or has moved onto new/different digital content items);
generating, for additional user accounts of the content management system, an update notification indicating a completion status for the composite action ( Kulkarni: Column 16, lines 34-50, the user activity sequence system 104 can generate one or more activity highlights based on the predicted activity events 206, may prioritize and/or focus on highlights ( such as completion) of various user account activities performed based on the particular predicted activity
event 206. Column 5, lines 3-9, sending notification);
and providing, without additional interaction by the user account, the update notification to the additional user accounts for display via user interfaces of client devices associated with the additional user accounts ( Kulkarni: Column 30, lines 28-47, displaying on client devices different suggestions/updates related to a digital content item accessible by the group of user accounts).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claim 15 is system claim performing the steps in method claim 9 above and as such, claim 15 is similar in scope and content to claim 9 and therefore, claim 15 is rejected under similar rationale as presented against claim 9 above.
Regarding Claim 17, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the non-transitory computer-readable storage medium of claim 16. Kulkarni further teaches, wherein: determining the input prediction defining the one or more predicted client device inputs comprises analyzing data signals collected by connectors from software tools associated with the user account (Kulkarni: Column 16, lines 8-17, software tools can be applied to content creation associated with user account corresponds to a content creator segment based on the predicted activity event 206. Column 33, lines 50-67, Fig. 9 illustrates computing device 900 ( content management system may comprise one or more device such as 900) and the communication interface 908, 910 ( to collect data signals to be analyzed)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Dicklin further teaches, and generating the predicted content to add to the content item in response to the one or more predicted client device inputs comprises processing the data signals collected by the connectors as a prompt through a large language model ( Dicklin: Para.[0050], Fig. 1, the real-time anticipation subsystem 116 may be configured to predict, in real-time, a user's interests and generate generative MLM prompts. Para.[0054], the generative MLM 120 may include a machine learning model configured to predict the next word and may include a transformer- based large language model (LLM). Para. [0194], network interface 1408).
Regarding Claim 20, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the non-transitory computer-readable storage medium of claim 19. Kulkarni further teaches, wherein the instructions, when executed by the at least one processor, further cause the computing device to provide the template file with the draft content for the first draft of the content item for display via a user interface of the client device ( Kulkarni: Column 13, lines 20-22, generating draft content. Column 16, lines 22-33, the user activity sequence system 104 may auto populate one or more entry fields of a template with the previous documents/ mining digital content data. Column 30, lines 28-47, displaying on client devices).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Claims 7, 8, 14 are rejected under 35 U.S.C. 103 as being unpatentable over Dicklin et al. ( US 20250103867 A1), hereinafter referenced as Dicklin, in view of BrockSchmidt et al. ( US 20200104102 A1), hereinafter referenced as BrockSchmidt, further in view of Kulkarni et al. (US 11567812 B2), hereinafter referenced as Kulkarni, further in view of Mansour et al. ( US 20250005263 A1), hereinafter referenced as Mansour.
Regarding Claim 7, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the computer-implemented method of claim 1. Kulkarni further teaches, further comprising: providing, for display via the client device, the content item comprising the predicted content ( Kulkarni: Column 7, lines 50-57, client applications 108 can present or display information to respective users associated with the client devices 106, including information or content responsive to a predicted activity event) ;
receiving at least one user interface element associated with a different content item ( Kulkarni: Column 31, lines 43-49, receiving/generating digital reminder ( user interface element) associated with different content items);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Dicklin in view of BrockSchmidt, further in view of Kulkarni, while teaching the claim 7, fail to explicitly teach the claimed, and based on determining that the at least one user interface element is unrelated to the content item, suppressing the at least one user interface element from display via the client device.
However, Mansour does teach the claimed, and based on determining that the at least one user interface element is unrelated to the content item, suppressing the at least one user interface element from display via the client device ( Mansour: Para.[0251], Fig. 5, the edit control 512 ( user interface element) in the graphical user interface 500 get suppressed, if the user does not have a permissions profile that allows edit permissions with respect to the currently displayed electronic document or page ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Mansour’s teaching of systems and methods for automatically generating content, structuring user-generated content, and/or generating structured content in collaboration platforms, into the system and method, taught by Dicklin in view of Kulkarni, because, this would improve the efficiency of an organization by establishing a collaborative work environment with access to, a suite of discrete software platforms or services to facilitate cooperation and completion of work.(Mansour, Para.[0003],[0004]).
Regarding Claim 8, Dicklin in view of BrockSchmidt, further in view of Kulkarni, further in view of Mansour teach the computer-implemented method of claim 7. Kulkarni further teaches, further comprising: determining that a composite action of the user account is paused or complete ( Kulkarni: Column 15, lines 14-22, the predicted activity event 206 may indicate that a user account has completed work on a digital content item and/or has moved onto a new/different digital content item);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Dicklin further teaches and generating a summary content item comprising a summary of the at least one user interface element ( Dicklin: Para.[0183], the user interface may display a context menu, and the context menu may include the selectable option of "Summarize this document”).
Regarding Claim 14, Dicklin in view of BrockSchmidt, further in view of Kulkarni teach the system of claim 10. Kulkarni further teaches, wherein the instructions, when executed by the at least one processor, further cause the system to: receive one or more user interface elements associated with a different content item ( Kulkarni: Column 31, lines 43-49, receiving/generating digital reminder ( user interface element) associated with different content items);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kulkarni’s teaching of natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity, into the system and method of real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers, taught by Dicklin, because, this would improve the accuracy of predicted activity events for different users of a content management system.(Kulkarni [ Column 5, lines 30-65]).
Dicklin in view of BrockSchmidt, further in view of Kulkarni, while teaching the claim 14, fail to explicitly teach the claimed, based on determining that the one or more user interface elements are unrelated to the content item, suppress the one or more user interface elements from display via the client device;
However, Mansour does teach the claimed, based on determining that the one or more user interface elements are unrelated to the content item, suppress the one or more user interface elements from display via the client device ( Mansour: Para.[0251], Fig. 5, the edit control 512 ( user interface element) in the graphical user interface 500 get suppressed, if the user does not have a permissions profile that allows edit permissions with respect to the currently displayed electronic document or page );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Mansour’s teaching of systems and methods for automatically generating content, structuring user-generated content, and/or generating structured content in collaboration platforms, into the system and method, taught by Dicklin in view of Kulkarni, because, this would improve the efficiency of an organization by establishing a collaborative work environment with access to, a suite of discrete software platforms or services to facilitate cooperation and completion of work.(Mansour, Para.[0003],[0004]).
Dicklin further teaches, and generate a summary content item comprising a summary of the one or more user interface elements ( Dicklin: Para.[0183], the user interface may display a context menu, and the context menu may include the selectable option of "Summarize this document”).
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 extension fee 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 date of this final action.
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/NADIRA SULTANA/Examiner, Art Unit 2653
/Paras D Shah/Supervisory Patent Examiner, Art Unit 2653
03/09/2026