DETAILED ACTION
This FINAL office action is in response to Applicant’s amendment filed February 13, 2026. Applicant’s February 13th amendment amended claims 1-4, 8, 10, 11, 13-15, 17, 20, canceled claims 5-7 and added new claims 21-24. Currently Claims 1-4 and 8-24 are pending. Claims 1, 8 and 15 are the independent claims.
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 .
Response to Amendment
The Objection to the Title in the previous office action is withdrawn.
The 35 U.S.C. 112b rejection of claim 1 in the previous office action is withdrawn in response to Applicant's amendment to claim 1.
The Double Patenting rejections of claims 1-4 and 8-20 in the previous office action are maintained.
The 35 U.S.C. 101 rejection of claims 1-4 and 8-20 in the previous office action is maintained.
The 35 U.S.C. 102 rejections of claims 1, 8 and 15 in the previous office action are withdrawn in response to Applicant's amendments to the claims.
Response to Arguments
Examiner notes Applicant’s remarks did not address the pending double patenting rejections; accordingly, the double patenting rejections are maintained.
Applicant’s arguments, see Pages 16-19, filed February 13, 2026, with respect to Whitney have been fully considered and are persuasive. The 35 U.S.C. 102 rejection of claims 1, 8 and 15 has been withdrawn.
Applicant's arguments filed February 13, 2026 have been fully considered but they are not persuasive. Specifically, Applicant argues that the claims are patent eligible under 35 U.S.C. 101 as the claims are claims are not directed to an abstract idea (e.g. uses machine learning in a closed look to control a resource planning system, restocking/recalling/substituting items, closed loop machine learning control process, automatically reconfigure resource planning system, automated item-management transactions; Remarks: Page 20; Paragraphs 1-2, Page 21); the claims cannot be practically performed in the human mind (e.g. not directed to a mental process, see USPTO AI guidance training perception nodes comprising a neural network, repeating training/correlating until deviation threshold is reached, automatically adjusting settings OR operations of the resource planning system; Remarks: Last Two Paragraphs, Page 21); the claims are not directed to/recite a specific mathematical formula or algorithm (Remarks: Paragraph 2, Page 22); the claims recite an improvement to computer-implemented resource planning and item management functions (Remarks: Paragraph 2, Page 22); the claims integrate the abstract idea into a practical application (e.g. specific machine learning architecture/training loop; directly control resource planning system - adjusting at least one setting OR operation; training/re-training neural network improves system level performance and computer functionality; Remarks: Page 23); the claims recite significantly more than the abstract idea (e.g. non-conventional combination/arrangement of elements, neural network, training/adaptation loop, resource control planning logic; integration of ML driven control architecture and resource planning system; Remarks: Last Two Paragraphs, Page 24; Paragraph 1, Page 25); and the claims are similar to Subject Matter Eligibility Example 47 (Remarks: Pages 25, 26).
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are not directed to an abstract idea, the examiner respectfully disagrees.
The claims are directed to a well-known business practice – resource planning/management (Title: “IDENTIFYING AND CORRECTING SUPPLIER ITEM DISCREPANCIES IN A PROCUREMENT SYSTEM” – i.e. resources/items are medical products/goods and resource planning/management is directed managing the procurement/inventory of those products)– more specifically the claimed invention directed controlling the item management activity by automatically adjusting at least ONE setting OR operation of the resource planning system to eliminate at least one deviation including initiating at least ONE automated transaction corresponding to at least ONE of a reorder or a substitute item or a restock or a recall (e.g. issuing a recall notification/alert).
Regarding the use of the generic (known, conventional) recited one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se)," the Supreme Court has held "the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice, 573 U.S. 208, 223. Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. The claims as a whole do not recite more than what was well-known, routine and conventional in the field (see MPEP § 2106.05(d)). In light of the foregoing and under the guidance, that each of the claims, considered as a whole, is directed to a patent-ineligible abstract idea that is not integrated into a practical application and does not include an inventive concept.
Regarding the recited one or more perception nodes comprising a neural network trained to correlate operating parameters with a critical parameter and generate a prediction indicating a deviation trained perception nodes/neural network (independent claims 1, 8, 15) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic trained perception nodes on a generic computer, also recited at a high level of generality. The trained perception nodes are used to generally apply the abstract idea without limiting how the trained perception nodes function. The trained perception nodes are described at a high level such that it amounts to using a generic computer with generic trained perception nodes to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Regarding the recited first/second/third machine learning models (dependent claims 2, 3, 9, 10, 16, 17, 21), the first/second/third ML models are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic first/second/third ML models on a generic computer, also recited at a high level of generality. The first/second/third ML models are used to generally apply the abstract idea without limiting how the first/second/third ML models function. The first/second/third ML models are described at a high level such that it amounts to using a generic computer with generic first/second/third ML models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
While the claims may represent an improvement to the fundamental economic process of resource management/planning (e.g. procurement management, recall alert notifications/escalations), the claims in no way either claimed or disclosed represent a practical application (e.g. provide a technical solution to a technical problem; improve any of the underlying technology (processor, computer readable medium, hardware device, display, database, control devices).
Additionally, the claims are directed to a mental processing practically capable of being performed in the human mind via observation, evaluation, judgement and opinion. Representative claim 1: The step of diagnosing a condition of a case of a resource planning system may be performed in the human mind using observation and evaluation. The step of training one or more perception nodes comprising a neural network may be performed in the human mind using evaluation and judgement. The step of correlating at least ONE operating parameter with at least ONE critical parameter to generate a prediction of a deviation may be performed in the human mind using judgement and opinion. The step of adapting at least ONE of a correlation module OR the neural network and repeating the training/correlation steps in response to determining that the deviation exceeds a threshold may be performed in the human mind using judgement and opinion. The step of terminating training in response to determining that the deviation is below a threshold may be performed in the human mind using judgement and opinion. The step of ‘controlling’ activity by automatically adjusting at least ONE setting OR operation may be performed in the human mind using judgement and opinion.
Other than the recitation of a one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se) nothing in the claimed steps precludes the step from practically being performed in the mind. The claims do not recite additional elements that are sufficient to amount to significantly more than the abstract idea. The limitations directed to a hardware device including a processor, computer readable memory, display device, sensors, network, control devices and/or database are each recited at a high level of generality and amount to no more than mere instructions to apply the exception using a generic computer, generic sensors, and/or generic control devices. See MPEP 2106.05(f).
Further the mere nominal recitation of a generic computer (i.e., one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se); each used for their well-understood, conventional and routine purpose) does not take the claim limitation out of the mental processes grouping. The claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of resource planning/management. In re TLI Commc’ns LLC Pat. Litig., 823 F.3d 607, 612 (Fed. Cir. 2016). The recited technology (processor, memories, etc.), are used as a “conduit for the abstract idea,” not to provide a technological solution to a specific technological problem. Id.; see also id. at 611–13 (holding claims reciting the use of a cellular telephone and a network server to classify an image and store the image based on its classification to be abstract because the patent did “not describe a new telephone, a new server, or a new physical combination of the two” and did not address “how to combine a camera with a cellular telephone, how to transmit images via a cellular network, or even how to append classification information to that data”).
Nothing in Applicant’s disclosures suggests that the Applicant intended to accomplish any of the steps recited in the claims through anything other than well understood technology used in a routine and conventional manner. Therefore, the claims lack an inventive concept. See also, e.g., Elec. Power Grp., 830 F.3d at 1355 (holding claims lacked inventive concept where “[n]othing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information”); Content Extraction, 776 F.3d at 1348 (holding claims lacked an inventive concept where the claims recited the use of “existing scanning and processing technology”).
Reevaluating the step of imitating at least one automatic transaction which is considered insignificant extra solution activity, these limitations are mere data gathering and output recited at a high level of generality and amount to nothing more than requesting, starting, or the like an action (reorder an item, substitute an item, restock an item or recall an item) all of which are well-understood, routine and conventional activities. The limitations remain insignificant extra solution activity even upon reconsideration. Even when considered in combination the additional elements represent mere instructions to apply an exception and insignificant extra solution activity which cannot provide an inventive concept.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims cannot be practically performed in the human mind, examiner respectfully disagrees.
As discussed above the claims are directed to a series of method steps which can be performed in the human mind or via pen and paper. The claims recite the use of generic computers performing generic computing functions in order to process data. The recitation of trained perception nodes in the claims does not negate the mental nature of these limitations because the trained perception nodes is merely used at a tool to perform an otherwise mental process. That the final step of the method is to ‘controlling’ item management activity including initiating at least one automated transaction corresponding to at least ONE of a reorder or substitute or recall or restock is a step a human is more than capable of completing upon determining that there is a deviation (e.g. send/generating a recall notification/alert is something a human mind via pen and paper is readily capable of performing).
As for Applicant’s argument that the claims are similar to the recent USPTO AI guidance, as the claims recite training/retraining of perception nodes comprising a neural network, the examiner respectfully disagrees. As discussed above the perception nodes comprising a neural network are recited at a high level of generality and are merely a tool/instructions to apply the abstract idea utilizing a generic computer.
Nowhere in Applicant’s disclosure or remarks is there any discussion at any level that the invention either as disclosed or claimed provides a technical solution to a technical problem or improves a technology or technical field. More specifically, as discussed in MPEP § 2106.04(d)(1) (below) nowhere in Applicant’s disclosure is there any discussion that the claims improve the field of machine learning or artificial intelligence.
MPEP § 2106.04(d)(1)
In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement in the functioning of a computer, or an improvement to other technology or a technical field. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine that the claim improves technology or a technical field. Second, if the specification sets forth an improvement in technology or a technical field, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement, i.e., That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. The claim itself does not need to explicitly recite the improvement described in the specification (e.g., “thereby increasing the bandwidth of the channel”). See, e.g., Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential), in which the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are not directed to/recite a specific mathematical formula or algorithm, the examiner respectfully disagrees.
While the claims include one more mathematical operations/concepts (e.g. comparing the at least one critical parameter to a threshold) the claims are not specifically rejected under 35 U.S.C. 101 as being directed to a mathematical concept as argued. As discussed above, the claims are directed to an abstract idea without significantly more. Specifically, the claims are directed to the well-known business/economic practice of resource planning/management as well as a mental process.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims recite an improvement to computer-implemented resource planning and item management functions, the examiner respectfully disagrees.
At best the claims represent an improvement in the well-known business/economic process of resource planning/management (e.g. generating/sending recall notices/alerts) wherein the improvement lies in the abstract idea itself. Computer implemented resource planning and item management functions are not technologies nor are they a technological field, they are well-known business/economic practice. The instant application merely applies the abstract idea using a generic computer as a conduit/tool for the abstract idea and does not improve the functioning of a computer or computer networks, does not improve another technical field and does not provide a technical solution to a technical problem.
There is a fundamental difference between computer functionality improvements, on the one hand, and uses of existing computers as tools to perform a particular task, on the other — a distinction that the Federal Circuit applied in Enfish, in rejecting a § 101 challenge at the first stage of the Mayo/Alice framework because the claims at issue focused on a specific type of data structure, i.e., a self-referential table, designed to improve the way a computer stores and retrieves data in memory, and not merely on asserted advances in uses to which existing computer capabilities could be put. See Enfish, 822 F.3d at 1335-36. Here the claims simply use a computer as a tool and nothing more.
For the reasons outlined above, the claims a method of organizing human activity, i.e., an abstract idea, and that the additional element recited in the claim beyond the abstract idea (i.e., processor, memory, resource planning system, etc.) is no more than a generic computer component used as a tool to perform the recited abstract idea. As such, it does not integrate the abstract idea into a practical application. See Alice Corp., 573 U.S. at 223-24 (“[Wholly generic computer implementation is not generally the sort of ‘additional featur[e]’ that provides any ‘practical assurance that the process is more than a drafting effort designed to monopolize the [abstract idea] itself.’” (quoting Mayo, 566 U.S. at 77)). Accordingly, we agree with the Examiner that claim 1 is directed to an abstract idea.
Step Two of the Mayo/Alice Framework (Step 2B)
Having determined under step one of the Mayo/Alice framework that claim 1 is directed to an abstract idea, we next consider under Step 2B of the Guidance, the second step of the Mayo/Alice framework, whether the claims include additional elements or a combination of elements that provides an “inventive concept,” i.e., whether an additional element or combination of elements adds specific limitations beyond the judicial exception that are not “well-understood, routine, conventional activity” in the field (which is indicative that an inventive concept is present) or simply appends well-understood, routine, conventional activities previously known to the industry to the judicial exception.
Under step two of the Mayo/Alice framework, the elements of each claim are considered both individually and “as an ordered combination” to determine whether the additional elements, i.e., the elements other than the abstract idea itself, “transform the nature of the claim” into a patent-eligible application. Alice Corp., 573 U.S. at 217 (citation omitted); see Mayo, 566 U.S. at 72-73 (requiring that “a process that focuses upon the use of a natural law also contain other elements or a combination of elements, sometimes referred to as an ‘inventive concept,’ sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the natural law itself’ (emphasis added) (citation omitted)).
Here the only additional element recited in the claims beyond the abstract idea is a “one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se),” i.e., generic computer component. See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”).
Applicant has not identified any additional elements recited in the claim that, individually or in combination, provides significantly more than the abstract idea.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims integrate the abstract idea into a practical application, the examiner respectfully disagrees.
The claims are directed to a well-known business practice – resource planning/management (e.g. item/product procurement) – in this case ‘directed controlling the item management activity by automatically adjusting at least ONE setting OR operation of the resource planning system to eliminate at least one deviation including initiating at least ONE automated transaction corresponding to at least ONE of a reorder or a substitute item or a restock or a recall (e.g. issuing a recall notification/alert). While the claims may represent an improvement to the business process of resource planning / procurement management they in no way either claimed or disclosed represent a practical application.
Under the see MPEP § 2106.05, the claims are evaluated to determine if additional elements that integrate the judicial exception into a practical application (see Manual of Patent Examining Procedure ("MPEP") §§ 2106.05(a)-(c), (e)- (h)). A claim that integrates a judicial exception into a practical application applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.
For example, limitations that are indicative of "integration into a practical application" include:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP § 2106.05(a);
Applying the judicial exception with, or by use of, a particular machine - see MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP § 2106.05(e).
In contrast, limitations that are not indicative of "integration into a practical application" include:
Adding the words "apply it" (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP § 2106.05(±);
Adding insignificant extra-solution activity to the judicial exception- see MPEP § 2106.05(g); and
Generally linking the use of the judicial exception to a particular technological environment or field of use - see MPEP 2106.05(h).
In view of the MPEP § 2106.05, one must consider whether there are additional elements set forth in the claims that integrate the judicial exception into a practical application. The identified additional non-abstract elements recited in the independent claims are the generic one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se). These generic computer hardware merely performs generic computer functions of processing and providing data and represent a purely conventional implementation of applicant’s procurement management summary in the general field of resource planning/management and do not represent significantly more than the abstract idea. See at least MPEP § 2106.05(a) ("Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field").
These recited additional elements are merely generic computer components. The claims do present any other issues as set forth in the MPEP § 2106.05 regarding a determination of whether the additional generic elements integrate the judicial exception into a practical application. Rather, the claims merely use instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea.
The claims do not recite improvements to the functioning of a computer or any other technology field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, the claims to do apply the abstract idea with a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (e.g. data remains data even after processing; MPEP 2106.05(c)), the claims no not apply or use the abstract idea in some other meaningful way beyond generally linking the user of the abstract idea to a particular technological environment (i.e. a generic computer) such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea (MPEP 2106.05(e)). The recited generic computing elements are no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding the recited one or more perception nodes comprising a neural network trained to correlate operating parameters with a critical parameter and generate a prediction indicating a deviation trained perception nodes/neural network (independent claims 1, 8, 15) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic trained perception nodes on a generic computer, also recited at a high level of generality. The trained perception nodes are used to generally apply the abstract idea without limiting how the trained perception nodes function. The trained perception nodes are described at a high level such that it amounts to using a generic computer with generic trained perception nodes to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Regarding the recited first/second/third machine learning models (dependent claims 2, 3, 9, 10, 16, 17, 21), the first/second/third ML models are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic first/second/third ML models on a generic computer, also recited at a high level of generality. The first/second/third ML models are used to generally apply the abstract idea without limiting how the first/second/third ML models function. The first/second/third ML models are described at a high level such that it amounts to using a generic computer with generic first/second/third ML models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e)- (h)), the claims do not integrate the judicial exception into a practical application.
There is a fundamental difference between computer functionality improvements, on the one hand, and uses of existing computers as tools to perform a particular task, on the other — a distinction that the Federal Circuit applied in Enfish, in rejecting a § 101 challenge at the first stage of the Mayo/Alice framework because the claims at issue focused on a specific type of data structure, i.e., a self-referential table, designed to improve the way a computer stores and retrieves data in memory, and not merely on asserted advances in uses to which existing computer capabilities could be put. See Enfish, 822 F.3d at 1335-36. Here the claims simply use a computer as a tool and nothing more.
For the reasons outlined above, that the claims recite a method of organizing human activity, i.e., an abstract idea, and that the additional element recited in the claim beyond the abstract idea (i.e., one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se)) is no more than a generic computer component used as a tool to perform the recited abstract idea. As such, it does not integrate the abstract idea into a practical application. See Alice Corp., 573 U.S. at 223-24 (“[Wholly generic computer implementation is not generally the sort of ‘additional featur[e]’ that provides any ‘practical assurance that the process is more than a drafting effort designed to monopolize the [abstract idea] itself.’” (quoting Mayo, 566 U.S. at 77)).
Accordingly, the claims are directed to an abstract idea.
Step Two of the Mayo/Alice Framework (Step 2B)
Having determined under step one of the Mayo/Alice framework that the claims are directed to an abstract idea, we next consider under Step 2B of the Guidance, the second step of the Mayo/Alice framework, whether the claims include additional elements or a combination of elements that provides an “inventive concept,” i.e., whether an additional element or combination of elements adds specific limitations beyond the judicial exception that are not “well-understood, routine, conventional activity” in the field (which is indicative that an inventive concept is present) or simply appends well-understood, routine, conventional activities previously known to the industry to the judicial exception. See MPEP § 2106.05.
Under step two of the Mayo/Alice framework, the elements of each claim are considered both individually and “as an ordered combination” to determine whether the additional elements, i.e., the elements other than the abstract idea itself, “transform the nature of the claim” into a patent-eligible application. Alice Corp., 573 U.S. at 217 (citation omitted); see Mayo, 566 U.S. at 72-73 (requiring that “a process that focuses upon the use of a natural law also contain other elements or a combination of elements, sometimes referred to as an ‘inventive concept,’ sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the natural law itself’ (emphasis added) (citation omitted)).
Here the only additional element recited in the claims beyond the abstract idea is a one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se)” i.e., generic computer component. See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). Applicant has not identified any additional elements recited in the claim that, individually or in combination, provides significantly more than the abstract idea.
Regarding the recited one or more perception nodes comprising a neural network trained to correlate operating parameters with a critical parameter and generate a prediction indicating a deviation trained perception nodes/neural network (independent claims 1, 8, 15) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic trained perception nodes on a generic computer, also recited at a high level of generality. The trained perception nodes are used to generally apply the abstract idea without limiting how the trained perception nodes function. The trained perception nodes are described at a high level such that it amounts to using a generic computer with generic trained perception nodes to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Regarding the recited first/second/third machine learning models (dependent claims 2, 3, 9, 10, 16, 17, 21), the first/second/third ML models are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic first/second/third ML models on a generic computer, also recited at a high level of generality. The first/second/third ML models are used to generally apply the abstract idea without limiting how the first/second/third ML models function. The first/second/third ML models are described at a high level such that it amounts to using a generic computer with generic first/second/third ML models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Similar to the discussion in Uniloc USA, Inc. v. LG Electronics USA, Appeal No. 19-1835 (Fed. Cir. Apr. 30, 2020), where the Federal Circuit reaffirmed that software inventions are patentable in the U.S. with a bright-line statement: “Our precedent is clear that software can make patent-eligible improvements to computer technology, and related claims are eligible as long as they are directed to non-abstract improvements to the functionality of a computer or network platform itself.” The instant application merely applies the abstract idea using a generic computer as a conduit/tool for the abstract idea and does not improve the functioning of a computer or computer networks, does not improve another technical field and does not provide a technical solution to a technical problem.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims recite significantly more than the abstract idea, the examiner respectfully disagrees.
The claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of resource planning/management. In re TLI Commc’ns LLC Pat. Litig., 823 F.3d 607, 612 (Fed. Cir. 2016). The recited technology (processor, memories, neural network, ML models, etc.), are used as a “conduit for the abstract idea,” not to provide a technological solution to a specific technological problem. Id.; see also id. at 611–13 (holding claims reciting the use of a cellular telephone and a network server to classify an image and store the image based on its classification to be abstract because the patent did “not describe a new telephone, a new server, or a new physical combination of the two” and did not address “how to combine a camera with a cellular telephone, how to transmit images via a cellular network, or even how to append classification information to that data”).
Nothing in Applicant’s disclosures suggests that the Applicant intended to accomplish any of the steps recited in the claims through anything other than well understood technology used in a routine and conventional manner. Therefore, the claims lack an inventive concept. See also, e.g., Elec. Power Grp., 830 F.3d at 1355 (holding claims lacked inventive concept where “[n]othing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information”); Content Extraction, 776 F.3d at 1348 (holding claims lacked an inventive concept where the claims recited the use of “existing scanning and processing technology”).
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are similar to Subject Matter Eligibility Example 47, the examiner respectfully disagrees.
Subject Matter Eligibility Example 47 (e.g. claim 3), is directed to a system and method that utilizes an trained artificial neural network to identify/detect and drop malicious network packets in real-time wherein the trained ANN detects anomalies in network traffic more accurately than traditional network anomaly detection methods and provides for faster training times. The claimed invention is directed to providing a technical solution to a technical problem. More specifically providing, similar to the findings in DDR, "the claimed solution is necessarily rooted in computer technology in order to overcome a problem specifically arising in the realm of computer networks." Further that the invention established an "inventive concept" for resolving an Internet-centric problem.
In sharp contrast the instant application and claimed invention are directed to resource planning/management (“controlling the item management activity…..initiating an least one automated transaction…at least ONE of reorder…substitute…restock OR recall”) is a business problem (e.g. procurement management, recall management), not a technical problem, not a solution necessarily rooted in computer technology, not a solution to overcome a problem arising from the realm of computer networks.
As for new limitations directed to repeatedly training of the perception nodes until a deviation is below a threshold, iteratively/repeatedly training and retraining an AI/ML model in a loop machine is old, well-known, conventional and routine. Machine learning and Artificial Intelligence algorithms, commonly and routinely – if not inherently – work by ‘learning’ from previous iterations/instances and as such repeated training/retraining of an ML model does not represent a technical improvement to the field of machine learning, does not improve the functioning of the underlying computer, processor or memory) and does not improve another technical field. The claims training and repeated training, until a termination deviation threshold hold is reached, is conventional, well-understood, and routine use of neural networks wherein the claims generally apply the abstract idea with limiting how the neural network are described at such a high level that the claims amount to using a computer with a generic neural network/reinforcement policy to apply the abstract idea.
Accordingly, the claims are not similar to those found patentable in Subject Matter Eligibility Example 47 and are therefore not patent eligible under 35 U.S.C. 101.
Claim Objections
Claim 14 is objected to because of the following informalities: claim 14 is incorrectly labeled as original instead of currently amended. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2, 9, 10 and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 2, 9, 10 and 16, the claims recite the limitation "the procurement inference engine" in claims 1, 8 and 15 respectively. There is insufficient antecedent basis for this limitation in the claim. Appropriate correction required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4 and 8-24 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.
Regarding independent Claims 1, 8 and 15, the claims are directed to the abstract idea of resource planning/management. This is a process (i.e. a series of steps) which (Statutory Category – Yes –process).
The claims recite a judicial exception, a method for organizing human activity, resource planning/management (Judicial Exception – Yes – organizing human activity). Specifically, the claims are directed controlling the item management activity by automatically adjusting at least ONE setting OR operation of the resource planning system to eliminate at least one deviation including initiating at least ONE automated transaction corresponding to at least ONE of a reorder or a substitute item or a restock or a recall (e.g. issuing a recall notification/alert), wherein resource planning/management is a fundamental economic practice that falls into the abstract idea subcategories of sales activities and/or commercial interactions. Further all of the steps of “diagnosing”, “training”, “correlating”, “comparing”, “adapting”, “repeating”, “terminating”, and “controlling” recite functions of the resource planning/management are also directed to an abstract idea that falls into the abstract idea subcategories of sales activities and/or commercial interactions. The intended purpose of independent claims 1, 8 and 15 appears enable a business to adapt/adjust settings OR operations to eliminate at least one deviation by initiating at least ONE automated transaction corresponding to at least ONE of a reorder or a substitute item or a restock or a recall.
Accordingly, the claims recite an abstract idea – fundamental economic practice, specifically in the abstract idea subcategories of sales activities and/or commercial interactions. The exceptions are the additional limitations of generic computer elements: one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se).
Accordingly, the claims recite an abstract idea under Step 2A, Prong One, we proceed to Step 2A, Prong Two. Considering whether the additional elements set forth in the claim integrate the abstract idea into a practical application, the previously identified non-abstract elements directed to generic computing components include: one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se). These generic computing components are merely used to process data as described extensively in Applicant’s specification (Specification: Figure 5).
Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Moreover, when viewed as a whole with such additional elements considered as an ordered combination, the claim modified by adding a generic computer would be nothing more than a purely conventional computerized implementation of applicant's resource planning in the general field of inventory management and would not provide significantly more than the judicial exception itself. Note McRo, Inc. v. Bandai Namco Games America Inc. (837 F.3d 1299 (Fed. Cir. 2016)), guides: "[t]he abstract idea exception prevents patenting a result where 'it matters not by what process or machinery the result is accomplished."' 837 F.3d at 1312 (quoting O'Reilly v. Morse, 56 U.S. 62, 113 (1854)) (emphasis added). The claims are not directed to a particular machine nor do they recite a particular transformation (MPEP § 2106.05(b)).
Additionally, the claims do not recite any specific claim limitations that would provide a meaningful limitation beyond generally linking the use of the judicial exception to a particular technological environment. Nor do the claims present any other issues as set forth the guidance regarding a determination of whether the additional generic elements integrate the judicial exception into a practical application. See Revised Guidance, 84 Fed. Reg. at 55. Rather, the claims merely use instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea. Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e)- (h)), Claims 1-4 and 8-24 do not integrate the judicial exception into a practical application.
Regarding the use of the generic (known, conventional) recited one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se)," the Supreme Court has held "the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice, 573 U.S. 208, 223. Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. The claims as a whole do not recite more than what was well-known, routine and conventional in the field (see MPEP § 2106.05(d)). In light of the foregoing and under the guidance, that each of the claims, considered as a whole, is directed to a patent-ineligible abstract idea that is not integrated into a practical application and does not include an inventive concept.
Regarding the recited one or more perception nodes comprising a neural network trained to correlate operating parameters with a critical parameter and generate a prediction indicating a deviation trained perception nodes/neural network (independent claims 1, 8, 15) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic trained perception nodes on a generic computer, also recited at a high level of generality. The trained perception nodes are used to generally apply the abstract idea without limiting how the trained perception nodes function. The trained perception nodes are described at a high level such that it amounts to using a generic computer with generic trained perception nodes to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Regarding the recited first/second/third machine learning models (dependent claims 2, 3, 9, 10, 16, 17, 21), the first/second/third ML models are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic first/second/third ML models on a generic computer, also recited at a high level of generality. The first/second/third ML models are used to generally apply the abstract idea without limiting how the first/second/third ML models function. The first/second/third ML models are described at a high level such that it amounts to using a generic computer with generic first/second/third ML models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Even upon reconsideration the additional elements (e.g. memory, processor, trained perception nodes, etc.) even when considered in combination represent mere instructions to apply the abstract idea and insignificant extra solution activity which cannot provide an inventive concept.
Examiner suggests Applicant review the recently updated MPEP § 2106.04(d)(1), the recent published Appeals Review Panel review of Ex parte Desjardins et al. decision and the recently posted 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (2024 AI SME Update) in the Federal Register on July 17, 2024 (https://www.federalregister.gov/public-inspection/2024-15377/guidance-2024-update-on-patent-subject-matter-eligibility-including-on-artificial-intelligence ) and specifically review the three new examples 47-49 announced by the 2024 AI SME Update which provide exemplary SME analyses under 35 U.S.C. 101 of hypothetical claims related to AI inventions (https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf).
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
Additionally, the claims recite a judicial exception, a mental processes, which can be performed in the human mind or via pen and paper (Judicial Exception – Yes – mental process).
The claimed steps of diagnosing a condition of a case, training one or more perception nodes comprising a neural network, correlating at least one more operating parameter with at least one critical parameter, comparing the at least one critical parameter to a threshold (also a mathematical operation), adapting at least one of a correlation module OR the neural network, repeating the training/correlating, terminating the training, and controlling an item management by automatically adjusting at least ONE of a setting OR an operation activity all describe the abstract idea. These limitations as drafted are directed to a process that under its reasonable interpretation covers performance of the steps in the mind but for the recitation of the generic computer components. Other than the recitation of one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se) nothing in the claimed steps precludes the step from practically being performed in the mind. The claims do not recite additional elements that are sufficient to amount to significantly more than the abstract idea. The mere nominal recitation of a generic processor/computer and trained neural network does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process. (Judicial Exception recited – Yes – mental process).
The claims do not integrate the abstract idea into a practical application. The generic one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se) are recited at a high level of generality merely performs generic computer functions of processing data. The generic processor/computer merely applies the abstract idea using generic computer components. The elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims do not recite improvements to the functioning of a computer or any other technology field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, the claims to do apply the abstract idea with a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (e.g. data remains data even after processing; MPEP 2106.05(c)), the claims no not apply or use the abstract idea in some other meaningful way beyond generally linking the user of the abstract idea to a particular technological environment (i.e. a generic computer) such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea (MPEP 2106.05(e)). The recited generic computing elements are no more than mere instructions to apply the exception using a generic computer component.
Regarding the recited one or more perception nodes comprising a neural network trained to correlate operating parameters with a critical parameter and generate a prediction indicating a deviation trained perception nodes/neural network (independent claims 1, 8, 15) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic trained perception nodes on a generic computer, also recited at a high level of generality. The trained perception nodes are used to generally apply the abstract idea without limiting how the trained perception nodes function. The trained perception nodes are described at a high level such that it amounts to using a generic computer with generic trained perception nodes to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. The recitation of trained perception nodes in the claims does not negate the mental nature of these limitations because the trained perception nodes is merely used at a tool to perform an otherwise mental process.
Regarding the recited first/second/third machine learning models (dependent claims 2, 3, 9, 10, 16, 17, 21), the first/second/third ML models are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic first/second/third ML models on a generic computer, also recited at a high level of generality. The first/second/third ML models are used to generally apply the abstract idea without limiting how the first/second/third ML models function. The first/second/third ML models are described at a high level such that it amounts to using a generic computer with generic first/second/third ML models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. The recitation of a first/second/third ML models in the claims does not negate the mental nature of these limitations because the first/second/third ML models is merely used at a tool to perform an otherwise mental process.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. (Integrated into a Practical Application – No).
As discussed above the additional elements in the claims amount to no more than a mere instruction to apply the abstract idea using generic computing components, wherein mere instructions to apply an judicial exception using generic computer components cannot integrate a judicial exception into a practical application or provide an inventive concept. For the receiving, storing and obtaining steps that were considered extra-solution activity, this has been re-evaluated and determined to be well-understood, routine, conventional activity in the field. Applications specification does not provide any indication that the computer/processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions (MPEP 2106.05(d)(II)) 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). For these reasons, there is no inventive concept. The claim is ineligible (Provide Inventive Concept – No).
Accordingly, the claims are ineligible under 35 U.S.C. 101 as being directed to an abstract idea without significantly more.
Regarding dependent claims 2-4, 9-14 and 16-24, the claims are directed to the abstract idea of resource planning and merely further limit the abstract idea claimed in independent claims 1, 8 and 15.
Claim 2, 8 and 16 further limits the abstract idea by obtaining a first/second plurality of inference results generated by first/second/third machine learning model wherein the first/second/third ML are part of a group of ML models (a more detailed abstract idea remains an abstract idea). Claims 3, 9 and 17 further limit the abstract idea by a first ML model to diagnose an item substitution, a second ML model to diagnose a new item, a third ML model to diagnose a recall, determining an action to date for an available substitute item, a new item or a recall item (a more detailed abstract idea remains an abstract idea). Claims 4, 10 and 18 further limit the abstract idea by forming the operating parameter from at least ONE specified field to at least ONE critical parameter including at least ONE of: new product benefits or used products or whether a product can replace a current item (a more detailed abstract idea remains an abstract idea). Claims 12 and 19 further limit the abstract idea by generating or configuring at least one of an intercompany action, external actions, response management or resolution deployment (a more detailed abstract idea remains an abstract idea). Claims 13 and 20 further limit the abstract idea by limiting the escalated call to actions to include a recall alert after a predefined time or after a predetermined threshold (a more detailed abstract idea remains an abstract idea). Claim 14 further limits the abstract idea by limiting the call to action to include recalls for a product device including one or more of an authenticated notification of a defect, defect alert or substitute item recommendation (a more detailed abstract idea remains an abstract idea). Claim 21 further limits the abstract idea by determining a first/second/third response corresponding to the first/second/third ML models, selecting one or the first- or second-ML model, and redistributing inference requests (a more detailed abstract idea remains an abstract idea). Claim 22 further limits the abstract idea by limiting the at least one critical parameter to safety-related associated with a recall and wherein controlling includes automatic generation of a recall notification (a more detailed abstract idea remains an abstract idea). Claim 23 further limits the abstract idea by monitoring recall acknowledgement status and inventory records and updating a recall stage status and escalated recall notification (a more detailed abstract idea remains an abstract idea). Claim 24 further limits the abstract idea by training using historical recall transaction and acknowledgement data, generating a predicted time to acknowledgement and initiating an escalation call-to action recall notification (a more detailed abstract idea remains an abstract idea).
None of the limitations considered as an ordered combination provide eligibility because taken as a whole the claims simply instruct the practitioner to apply the abstract idea to a generic computer.
Further regarding Claims 1-4 and 8-24, Applicant’s specification discloses that the claimed elements directed to a one or more processors, memory, computer readable medium having instructions, resource planning system (software per se), correlation module (software per se), procurement inference engine (software per se) at best merely comprise generic computer hardware which is commercially available (Specification: Figure 5). More specifically Applicant’s claimed features directed to a system do not represent custom or specific computer hardware circuits, instead the terms merely refers to commercially available software and/or hardware. Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims merely recite manipulating data utilizing generic computer hardware (e.g. memory, processor, etc.). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Further the lack of detail of the claimed embodiment in Applicant’s disclosure is an indication that the claims are directed to an abstract idea and not a specific improvement to a machine.
Applicant has not demonstrated that a special purpose machine/computer is required to carry out the claimed invention. A special purpose machine is now evaluated as part of the significantly more analysis established by the Alice decision and current 35 U.S.C. 101 guidelines. It involves/requires more than a machine only broadly applying the abstract idea and/or performing conventional functions.
Applicant’s specification discloses that the claimed elements directed to a system, processor, interface, component and memory merely comprise generic computer hardware which is commercially available (Specification: Figure 5). More specifically Applicant’s claimed features directed to a system and components do not represent custom or specific computer hardware circuits, instead the term system merely refers to commercially available software and/or hardware Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims merely recite manipulating data utilizing generic computer hardware (e.g. memory, processor, etc.). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Further the lack of detail of the claimed embodiment in Applicant’s disclosure is an indication that the claims are directed to an abstract idea and not a specific improvement to a machine.
Accordingly given the broadest reasonable interpretation and in light of the specification the claims are interpreted to include the process steps being performed by a human mind or via pen and paper. The claim limitations which recite a memory, processor, interface or similar generic computer structures which at best recite generic, well-known hardware. However, the recited generic hardware simply performs generic computer function of processing data. Generic computers performing generic, well known computer functions, alone, do not amount to significantly more than the abstract idea. Further the recited memories are part of every conventional general-purpose computer.
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 SCOTT L JARRETT whose telephone number is (571)272-7033. The examiner can normally be reached M-TH 6am-4:30PM.
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SCOTT L. JARRETT
Primary Examiner
Art Unit 3625
/SCOTT L JARRETT/Primary Examiner, Art Unit 3625