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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/16/26 has been entered. Currently claims 1, 3-8, 10-21 are pending.
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, 3-8, 10-21, are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 3-8, 10-12, 21 recite a system, claims 13-19 recite a method, and claim 20 recites a non-transitory computer readable medium; therefore, the claims pass step 1 of the eligibility analysis.
For step 2A, the claim(s) recite(s) an abstract idea of resource allocation management such as occurs was a person is deceased and an executor is handing the settlement (allocation of resources) of the estate according to the will of the deceased and/or in view of applicable governmental regulations. This represents a certain method of organizing human activities as is set forth below.
For claim 13 as a representative example that is applicable to claims 1 and 20, the abstract idea is defined by the elements of:
representing a questionnaire configured to elicit a series of user inputs corresponding to one or more attributes associated with one or more resources of a resource pool;
obtain said series of user inputs corresponding to one or more attributes associated with said one or more resources of said resource pool,
wherein the attributes include data indicating types of resource assets forming part of an estate of a deceased user, data associated with one or more instruments defining the estate of the deceased user, and data associated with an executor user;
retrieving historical data sets representing prior allocations of resources, said historical data including at least one of said one or more attributes;
a machine learning allocation model defining complexity scores associated with respective resource attributes;
generating a complexity prediction associated with resource allocation based on the one or more attributes,
determine, based on the generated complexity prediction, whether the complexity prediction meets a threshold value
generating, based on the generated complexity predication and said user inputs, a selected subset of user interface elements from a global set of user interface elements representing all possible actions for allocating resource pools,
said selected subset being determined based on the generated complexity prediction and the one or more attributes to reduce a volume of user interface elements for display, said selected subset comprising:
a plurality of graphical elements identifying complexity for the one or more attributes,
targeted interface elements associated with required attributes of the one or more attributes, said required attributes being required for determining downstream operations, said required attributes having a contribution above a threshold level on the complexity prediction of said resource allocation,
elements representing a series granular tasks for allocating resources of said resource pool, wherein said granular tasks are arranged based on an estimated time required to complete said granular tasks and
displaying progressive action status for allocating the one or more resources
The claim is reciting the act of predicting the complexity involved in resource allocation (reads on estate settlement) by providing information regarding the allocation of the resources (the resources being the assets of the deceased). This represents a fundamental economic practice that is from the field of estate settlement. Various laws govern the passing of assets from a deceased to a beneficiary or next of kin. This is traditionally handled by human beings when one considers that resource allocation for estates was something practiced by people well before the invention of modern day computing devices. Keeping progress of, and tracking the execution of the will for a deceased person is something done by an executor and is considered to be reciting a certain method of organizing human activity in the form of a legal interaction or a legal obligation of the executor.
For claims 1, 13, the additional elements are the processor and memory that stores instructions to perform the recited functions that serve to define the abstract idea, the transmission of the signals to a display device or client device, the use of the interface with interface elements and to display data (the data is part of the abstract idea), and the recitation to training and using the machine learning model. The machine learning model itself is considered to be part of the abstract idea because it is just a model, where the training of the model and the use of the model is considered to be an additional element.
For claim 20, the additional element is the recitation to the non-transitory computer readable medium that causes a processor to perform the recited method.
This judicial exception is not integrated into a practical application (2nd prong of eligibility test for step 2A) because the additional elements of the claims when considered individually and in combination, do not amount to more than a mere instruction for one to use a computer and the use of a trained machine learning model, where the computer has an interface and a processor with memory that performs the steps that define the abstract idea, where the interface is used to display information (where the information being displayed is part of the abstract idea). The processor of the claimed system is being used as a tool to perform the abstract idea (see MPEP 2106.05(f)). The claimed transmitting of the signals to a client device and the communicating (claimed signals) with the display device to cause the display of data/information is the use of a computer to send data to another computer so that the information can be displayed on an interface/display, and is the equivalent of reciting “apply it with a computer” for the abstract idea. The claimed interface and its use for display of data is something that all interfaces provide for and is the same as reciting “apply it” using a computer that has an interface display. All computers have an interface that displays data to a user. The claimed training of the machine learning model and the use of the machine learning model to generate the complexity prediction (the complexity predication is part of the abstract idea, the use of machine learning is an additional element) is taken as a general link to the particular technological field of machine learning. The claimed training of the model is reciting what occurs in machine learning by definition, namely that models are trained using datasets so they can learn and work correctly. The claimed training of the model that is inherent to all machine learning models and using machine learning (recited at a high level of generality) is not sufficient to amount to more than a link to a particular technological environment, which is using a computer and machine learning to perform a step(s) that is part of the abstract idea. See MPEP2106.05(h) in this regard in addition to 2106.05(f). The claimed additional elements when taken with the claim as a whole, is simply instructing one to practice the abstract idea by using a generically recited computing device with a processor and memory, training and using a machine learning model, and using a generically recited user interface to perform steps that define the abstract idea. The claim is simply linking the execution of the abstract idea to computer implementation with a general link to the field of machine learning for the complexity prediction. The above indicative of the fact that the claim has not integrated the abstract idea into a practical application and therefore the claim is found to be directed to the abstract idea identified by the examiner. See MPEP 2106.05(f).
With respect to the claim reciting that the selected subset is less than all possible actions for allowing resource pools, and which is displayed by the interface, the examiner notes that this does not serve to improve technology or the field of interfaces. Just because the claim is displaying less than all possible options that exist does not mean that technology is being improved, this is just claiming the data to be displayed. The examiner equates this to displaying less than all of the search results that are returned for a search query, because it is not possible to display hundreds or thousands of search results to a user at one time. Deciding on what subset to display and providing it for display does not serve to improve technology or the interface that is claimed. While the invention recognizes the obvious, namely that it is not always possible to display all options to a user at the same time due to limited space, such as a when a search query returns 5000 results, the act of making a selection on what to display is not itself something that improves technology. Rather than claiming specifics of an interface or the manner in which the display of data occurs via the interface, the claim simply recites the data that is displayed is less than all of the options that could be displayed. That is not an improvement to technology that provides for integration into a practical application.
For step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not amount to more than simply instructing one to practice the abstract idea by using a generically recited computing device with a processor and memory, training and using a machine learning model, and using a generically recited user interface of a display device to perform steps that define the abstract idea. The use of a computing device with a processor and memory and that has an interface, the use of machine learning, all of which are being used as a tool to execute the abstract idea, does not provide for significantly more, see MPEP 2106.05(f), (h). The rationale set forth for the 2nd prong of the eligibility test above is also applicable to step 2B in this regard so no further comments are necessary. This is consistent with the PEG found in the MPEP 2106.
In addition to that above, with respect to the claimed transmission of signals to cause the display of data, the examiner notes that a mere data transmission is something that is considered to be an insignificant extra solution activity that is also well understood in the computing field. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016),
and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Using a computer and a network to send a signal to another computer to display data does not provide for integration or significantly more. The examiner makes this comment in response to the applicant arguing that the ending of signals using a computer integrated the invention into a practical application and/or recites significantly more. Transmitting a signal using a computer can be interpreted to be a general instruction for one to use a computer (“apply it”) and can be considered as an insignificant extra solution activity that is also well understood routine and conventional in the computing field. Either way, the user of a computer and sending signals to another computer to display an interface does not render the claims eligible.
For claims 3, 14, the representation that is a predicted time duration for the allocated resources is a further embellishment of the same abstract idea set forth for claims 1, 13 The use of the interface element (an additional element) as far as computer implementation is concerned has been treated in the same manner as was set forth for claims 1, 13. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 4, 15, the identification of the allocation complexity for respective resources as claimed is part of the abstract idea. This is the result of the prediction that is part of the abstract idea. The use of interface elements (additional element) has been treated in the manner set forth for claim 1, 13. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 5, 16, the claimed determining that a proposed resource application is associated with a complexity that exceeds a threshold, providing guidance operations for allocating the resources is a further recitation to the same abstract idea of claims 1, 13. Determining the complexity and if it meets a threshold is part of the abstract idea and is also something that can be done mentally. The providing of guiding operations is claiming that recommendations are being made, and this is also part of the abstract idea. The additional elements of the processor and memory has been treated with claim 1 to which applicant is referred. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 6, 17, similar to claims 5 and 16, the determination if the complexity does not meet a threshold and generating a set of operations for allocating the resources, is a further defining of the same abstract idea that was set forth for claims 1, 13. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 7, 18, the recited transmitting of the signal to a service provider is being done so that a service provider can assist in the estate settlement, according to the disclosure in the specification. With respect to the use of a signal and electronic transmission by the processor, this is simply using a computer as a tool to provide a notification to the service provider and does not provide for integration or significantly more, see MPEP 2106.05(f). Additionally or alternatively, a mere data transmission is something that is considered to be an insignificant extra solution activity that is also well understood in the computing field. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016),
and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Using a computer and a network to send a signal to another computer to display data does not provide for integration or significantly more for the above reasons. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 8, 19, the claimed pre-population based on user inputs is taken as being part of the abstract idea of the claims. The recitation to using the processor is an instruction for one to use a computer to perform a step that is part of the abstract idea and does not provide for integration or significantly more, see MPEP2106.05(f). Therefore the claims are not considered to be eligible.
For claim 10, the recited types of resources are part of the abstract idea because that is what is being allocated, money or assets, etc... The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 11, 12, the applicant claims that the model is trained based on data. This is also taken as a high level recitation to the use of machine learning and trained models. This is not sufficient to amount to more than a link to a particular technological environment that is using a computer and machine learning, as was set forth for claim 1. See MPEP2106.05(h) in this regard. The claimed training is reciting what occurs in machine learning by definition, meanly that models are trained. This does not provide for integration or significantly more. Therefore the claims are not considered to be eligible.
For claim 21, the updating of the machine learning model is considered to be a further embellishment of the abstract idea. A human can update a model by changing weights used by the model or by providing a new data training set to the model. Claim 21 is not reciting the use of a machine learning model as the updating of the model is not the same as claiming a use of the model. The use of the machine learning model for the complexity predication has been treated in the same manner that was set forth for claim 1 and does not provide for integration into a practical application or significantly more.
Therefore, for the above reasons, claims 1, 3-8, 10-21, are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Response to arguments
The traversal of the 35 USC 101 rejection is not persuasive. On page 8 of the reply the applicant argues that the claims as amended recite an improvement to technology, specifically an improvement to user interface technology. The applicant argues that the improvement is the generation of a reduced bespoken subset of elements for display, which is claimed as being less than all options. This is not persuasive. Just because the claim is reciting the display of less than all possible options that exist does not mean that technology is being improved. The examiner equates this to displaying less than all of the search results that are returned for a search query, because it is not possible to display hundreds or thousands of search results to a user at one time. Deciding on what subset of options to display and providing it for display via an interface is a broadly recited and non-limiting manner does not serve to improve technology or the interface that is claimed. While the invention recognizes that it is not possible to display all options that exist to a user at the same time due to limited space (which all depends on the number of options that exist), such as a when there are 5000 options, the act of making a selection on what to initially display to the user is not itself something that improves technology. Rather than claiming specifics to an interface and it functionality, or the manner in which the display occurs via the interface, the claim simply recites the data that is displayed as being less than all that could be displayed. That is not an improvement to technology that provides for integration into a practical application or significantly more.
The reliance upon Core Wireless is noted, but is not found to be persuasive. Unlike the claims in Core Wireless, the pending claims do not recite an improvement to the GUI art as was addressed immediately above. By claiming the data to be displayed is a subset of all data that could be displayed the applicant is not claiming any structure to the interface and is not claiming any specific manner in which the data is being displayed. The claim is simply reciting a subset of data is displayed, which itself does not serve to improve technology or the claimed interface of the claims. The reliance upon Core Wireless is not found to be persuasive. When one does a search online and is presented with results, they are displayed to a user one page at a time, where sometimes the search results could include hundreds of pages. In that situation, the interface is not being improved by deciding on the best search results to provide to the user on page one, it is just displaying what the interface is instructed to display and the presentation of search results with some order to the results, does not serve to improve technology. The same analogy can be made to the pending claims and the recitation to selecting and displaying a subset of all possible options, which does not serve to improve the interface in any manner.
On page 9 of the reply the applicant argues that the examiner has not considered the claims as a whole. The applicant argues that an improvement to technology is a result of an ML derived complexity prediction and the dynamic selection of the subset of data to be displayed. The argument is not persuasive. The fact that the claim recites the use of machine learning to perform the determining a complexity prediction (the prediction is part of the abstract idea) is taken as a link to a particular technological environment that does not render the claims eligible. This is just using machine learning as a tool to execute the functions that represent the abstract idea. The use of historical data to train the machine learning model is claiming machine learning by definition as all machine learning models are trained. The complexity prediction and its use to determine what subset of data is to be displayed is part of the abstract idea and does not result in an improvement to technology as has already been addressed.
On pages 10-11 the applicant argues that the claims do not recite or set forth mathematical concepts, which is argued as being the use of machine learning. The examiner notes that the claims are considered to be reciting a certain method of organizing human activities abstract idea. The examiner has not alleged that the claims recite mathematical concepts. When artificial intelligence or machine learning is recited at a high level of generality and is not expressly reciting math, the USPTO guidance instructs examiners to consider the use of AI/ML to be a general link to a particular technological environment. When the machine learning or AI is recited such that it expressly recites the performance of math, then the claimed element is considered to be part of an abstract idea. The examiner agrees with the applicant that the claims are not expressly reciting the performance of math such that the claims would be found to be reciting a mathematical concept based on the eligibility guidance for mathematic concepts found in MPEP 2106.
On page 10 the applicant argues that the technological improvement lies in the manner in which the interfaces are generated for computing devices with limited space on a screen for display. This is not persuasive. Upon a review of the claims it is noted that the claims do not recite anything about how the interface is actually being generated. The claims recite how the subset of data is selected for display, which is not claiming anything about how the interface is being generated such that it would be considered as an improvement to technology. All that is claimed is the generation of the interface in a broad and non-limiting manner. Simply determining the data to be displayed that is less than all of the data that could be displayed does not confer an improvement onto the interface. The argument is not persuasive. The 101 rejection is being maintained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS WILLIAM RUHL whose telephone number is (571)272-6808. The examiner can normally be reached M-F 7am-3:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at 5712703445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DENNIS W RUHL/Primary Examiner, Art Unit 3626
Prosecution Insights