DETAILED ACTION
This non-final office action is in response to Applicant’s amendment and request for continued examination filed January 12, 2026. Applicant’s January 12th amendment amended claims 1, 8 and 11 and canceled claims 2-4, 7, and 10. Currently claims 1, 5, 6, 8, 9 and 11 are pending. Claims 1, 8 and 11 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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 January 12, 2026 has been entered.
Response to Amendment
The 35 U.S.C. 101 rejection of claims 1, 5, 6, 8, 9 and 11 in the previous office action is maintained.
Response to Arguments
Applicant's arguments filed January 12, 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 similar to McRO (Remarks: Last Paragraph, Page 9; Paragraph 1, Page 10); the claims are not directed to an abstract idea (e.g. specific machine implemented technical solution to a concrete problem in supply chain inventory management; non-generic machine learning pipeline cannot be equated to based demand forecasting, high-granularity data pre-processing and transformation steps; Remarks: Last Two Paragraphs, Page 10; Paragraphs 1-2, Page 11); the claims cannot be performed in human mind (e.g. Paragraphs 1-2, Page 11); the claims solve a technical problem of inefficient management of inventory (e.g. managed perishable inventory accounting for expiry dates and fluctuating demand; improved supply chain management; Specification: Paragraphs 2-7, 69, 70; Remarks: Page 11); the claims integrate the abstract idea into a practical application (e.g. specific technical improvement to inventory management; enables more granular inventory categorization; Specification: Paragraphs 57, 58, 66; Remarks: Page 12) and the claims recite significantly more than the abstract idea (e.g. additional elements, non-conventional arrangement of elements, etc.; Remarks: Pages 13, 14).
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims provide an improvement in computer related technology/similar to McRo, the examiner respectfully disagrees.
The argued technical problems/solutions (e.g. computer-based inventory management, manage perishable inventory accounting for expiry dates and fluctuating demand; improved supply chain management, etc.) are not technical problems. At best the argued improvements are improvements in the abstract idea itself – i.e. improvements in the fundamental economic practice of forecasting warehouse level inventory demand for a predefined period in time. Nowhere in Applicant’s disclosure is there a specific or detailed discussion of a technical problem, much alone a technical solution to a technical problem, addressed by the claimed or disclosed invention.
As made clear in Uniloc USA, Inc. v. LG Electronics USA, Appeal No. 19-1835 (Fed. Cir. Apr. 30, 2020), 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 fails to disclose, much alone claim, a technical solution to a technical problem; fails to disclose an improvement in computer or computer networks or computer related technology (e.g. none of the recite processor, memory, user equipment, or the like is improved in any way – each is recited at a high level of generality and the claims merely recite instructions to apply the abstract idea using the generic computers/generic AI engine comprising one or more machine learning models).
At best the claimed/disclosed may improve forecasting warehouse level inventory demand, however forecasting inventory demand, including doing so through the use of AI engine/machine learning models, Bayesian optimization, automatic selection of forecasting algorithms or the like does not improve any of the underlying technological elements/components nor does it improve another technical field (i.e. neither inventory management nor demand forecasting represent a technical field). None of the argued benefits represent an improvement in an underlying technology (e.g. the claims processors, memories, artificial intelligence engine (software per se), acquisition engine, etc.) or represent an improvement in another technical field (e.g. inventory management is a business field/problem, demand forecasting is a business field/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.
The claims do not recite a technical problem or technical solution necessarily rooted in computers, computer networks or another technical field.
As for Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are similar to McRo, the examiner respectfully disagrees.
As discussed above the claims are directed to a fundamental economic practice (inventory demand forecasting) as well as directed to a mental process, wherein the method steps can be readily performed in the human mind or via pen and paper. The claims do not recite or disclose improvements to a computer or any other technology (only a generic processor is disclosed), MPEP 2106.05(a). The claims do not apply or involve a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition. The claims do not apply or perform the abstract idea with a particular machine, MPEP 2106.06b. The claims to do transform or reduce a particular article to a different state or thing (data remains data when processed by a computer), MPEP 2106.05c. The claims do not apply or use the abstract idea in a meaningful way beyond generally linking the use of the abstract idea to a particular technological environment (i.e. a processor, memories, UE, AI engine comprising one or more machine learning models, etc.), such that the claims are a drafting effort to monopolize the abstract idea (i.e. the claims do not integrate the abstract idea into a practical application of the abstract idea).
In McRO, the Federal Circuit concluded that the claimed methods of automatic lip synchronization and facial expression animation using computer-implemented rules were not directed to an abstract idea. McRO, 837 F.3d at 1316, 120 USPQ2d at 1103. The basis for the McRO court's decision was that the claims were directed to an improvement in computer animation. The court relied on the specification's explanation of how the claimed rules enabled the automation of specific animation tasks that previously could not be automated. 837 F.3d at 1313, 120 USPQ2d at 1101. The McRO court found that the claims clearly improved the functioning of the claimed computer and that the claims directed to recite improvement (e.g. rules). Further the court found that the specification clearly disclosed that the claimed improvement improved the functioning of the computer.
In sharp contrast to the McRO decision the instant application merely claims to mere instructions to apply the abstract idea using conventional, routine, well-understood and widely used computers and generic machine learning models (AI engine). Further the claims merely recite a general linking to the use of the abstract idea to a particular technological environment (e.g. processor, memories, AI engine, etc.). The recite processor/computer merely performs generic computer functions of acquiring/retrieving, processing and outputting/transmitting data. The performance of the processor/computer is not improved in any way. Further Applicant’s disclosure lacks any discussion of improving the performance of the underlying technological environment. The processor/computer merely ‘executes’ the abstract idea and is used merely a tool. The claims are not directed to improving computer performance and do not recite any such benefit. Further Applicant’s specification does not disclose any teachings related to improving computer performance.
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 an abstract idea/cannot be performed in the human mind, the examiner respectfully disagrees.
Independent claims 1, 8 and 11 are directed to the well-known business practice (fundamental economic practice) of demand forecasting or more specifically forecasting inventory demand (Title: Systems and Methos for Forecasting Inventory). Forecasting demand is fundamental economic practice that fall into the abstract idea subcategories of sales activities and commercial interactions.
Additionally, the claims are directed to a mental process practically being capable of being performed in the human mind via observation, evaluation, judgement and opinion. Claims 1, 8 and 11, as argued by Applicant, are directed to computer-based inventory management and more specifically the claimed invention acquires at least ONE of sales or product or daily inventory or batch level inventory data (i.e. pre-solution insignificant activity, data input), processes data (pre-processes data parameters into batches, estimates a product demand, corrects a calculated demand forecast, classifies products into batches, categorizes inventory batches into buckets, forecast of warehouse level inventory demand) and outputs data (Claim 11 only – transmits categorized inventory data, demand forecast data and generates an alert)
The steps directed to estimate a demand by calculating a demand forecast using a forecasting algorithm, correcting the calculated demand forecast data using exogenous variables, and forecast a warehouse level inventory demand are directed to mathematical operation/concept and are therefore categorized in the mathematical grouping of abstract ideas as well as being capable of being performed in the human mind using evaluation. The steps directed to classify the product into different batches based on at least ONE of forecasted sales, historical sales OR exogenous variables is capable of being performed in the human mind using evaluation and judgement; categorize each batch of inventory into different buckets of products at a batch level is capable of being performed in the human mind via evaluation and judgement. The step of forecast a warehouse inventory demand is both a mathematical operation and capable of being performed in a human mind via evaluation. The recited generic system, acquisition engine (software per se), Artificial Intelligence engine (software per se), user equipment (UE), feature engineering module (software per se), event impact module (software per se), processors and memories are recited at a high level of generality and as such represent nothing more than mere instructions to apply the abstract idea using a generic computer. The mere nominal recitation of a generic processor does not take the claim limitation out of the mental processes grouping.
Claims 1 and 8 recite send an alert to one or more users (extra solution activity, insignificant post-solution activity – data output), wherein it is noted that the intended use of the alert “to act on product batches that are bound to expire or cause losses” is directed to an non-functional intended use of the alert and has not been given patentable weight (the alert may or may not actually received by the one or more users who may or may not actually act). Claim 11 additionally recites transmit pre-processed data comprising at least ONE of sales, product, daily inventory and batch level inventory data (pre-solution, extra solution activity, data gathering); receive an alert from the optimization system (post-solution, extra solution activity, data output). The claims merely recite transmitting and receiving data, readily capable of being performed in a human mind via observation, evaluation and opinion. The recite generic system, acquisition engine (software per se), Artificial Intelligence engine (software per se), user equipment (UE), feature engineering module (software per se), event impact module (software per se), processors and memories are recited at a high level of generality and as such represent nothing more than mere instructions to apply the abstract idea using a generic computer. The mere nominal recitation of a generic processor/computer does not take the claim limitation out of the mental processes grouping.
More specifically artificial intelligence engine comprising one or more machine learning models (software per se; Specification: Paragraphs 52, 53), is recited at a high level of generality and is used by a generic computer/processor, also recited at a high level of generality, to estimate/calculate product demand (mental step, mathematical concept), select an optimal forecast algorithm (mental step, mathematical operation), and categorize batch inventory into buckets amounts to no more than mere instructions to implement an abstract idea on a generic computer. The artificial intelligence engine is used to generally apply the abstract idea without limiting how the artificial intelligence engine functions. The artificial intelligence engine (software per se) is described at a high level such that it amounts to using a computer with a generic artificial intelligence engine to apply the abstract idea. The recitation of an artificial intelligence engine comprising one or more machine learning models (also recited at a high level of generality) in the claims does not negate the mental nature of these limitations because the artificial intelligence engine is merely used at a tool to perform an otherwise mental process. The generic computer and generic artificial intelligence engine are used for their old, well-known, routine and conventional purposes - in this case performing a series of method steps readily performed by a human/via pen and paper.
Accordingly, the claims are directed to both a fundamental economic practice and a mental process without significantly more and 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 solve a technical problem of inefficient management of inventory, the examiner respectfully disagrees.
As discussed above the argued ‘technical’ problems/solutions (e.g. manage perishable inventory accounting for expiry dates and fluctuating demand; improved supply chain management, etc.) are not technical problems much alone represent technical solutions to technical problems. At best improved supply chain management for perishable inventory may be an improvement in the abstract idea itself (i.e. a business solution to a clearly business problem). Nothing in Applicant’s disclosure discusses at any level of detail technical solution/problem nor discloses an improvement in an underlying technology nor discloses an improvement in another technical field. The claims merely use conventional computer technology (e.g. processor, memory, etc.) to perform a series of method steps directed to forecasting warehouse level demand and sending an alert to a human user (Claims 1 and 8) or transmit data (categorized inventory data, demand forecast data) to user equipment and generate an alert (which may or may not actually be sent/transmitted, received or acted upon) – the alert/transmitted data is merely insignificant extra-solution/post-solution activity (i.e. data output).
Accordingly, neither Applicant’s disclosure nor the claimed invention provides a technical solution to a technical problem as argued and therefore are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s arguments that the claims are patent eligible under 35 U.S.C. 101 because the claims integrate the abstract idea into a practical application, the examiner respectfully disagrees.
As discussed above the claims are directed to forecasting warehouse level inventory demand. While the claims may represent an improvement to the business process of forecasting warehouse level demand they in no way either claimed or disclosed represent a practical application.
Under 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 guidance, 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 user (a human) and the generic computing elements: system, acquisition engine (software per se), Artificial Intelligence engine (software per se), user equipment (UE), feature engineering module (software per se), event impact module (software per se), processors and memories. These generic computer hardware merely performs generic computer functions of acquiring/retrieving, processing and transmitting data and represent a purely conventional implementation of applicant’s demand forecasting in the general field of inventory 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 guidance 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.
The recited artificial intelligence engine comprising machine learning models (software per se) is recited at a high level of generality and is used by a generic computer/processor, also recited at a high level of generality, to estimate/calculate product demand (mental step, mathematical concept), select an optimal forecasting algorithm (mental step, mathematical concept), and amounts to no more than mere instructions to implement an abstract idea on a generic computer. The artificial intelligence engine is used to generally apply the abstract idea without limiting how the artificial intelligence engine functions. The artificial intelligence engine comprising machine learning models (software per se) is described at a high level such that it amounts to using a computer with a generic artificial intelligence engine to apply the abstract idea. The recitation of an artificial intelligence engine in the claims does not negate the mental nature of these limitations because the artificial intelligence engine is merely used at a tool to perform an otherwise mental process. The limitations only recite outcomes 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.
For the reasons outlined above, that claims 1, 8 and 11 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 (e.g., processor, memory, user equipment, AI engine, 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, 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.
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 claims 1, 8 and 11 beyond the abstract idea are the processors, memory, artificial intelligence engine (software per se), acquisition engine (software per se), feature engineering module (software per se), event impact module (software per se), and user equipment (generic computer),” 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 AI engine comprising one or more machine learning models for calculating a demand forecast, select an optimal forecast algorithm and categorize each batch of inventory into difference buckets, the AI engine comprising one or more machine learning models is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using generic machine learning models network on a generic computer, also recited at a high level of generality. The AI engine comprising one or more machine learning models is used to generally apply the abstract idea without limiting how the AI engine. The AI engine comprising one or more machine learning models is described at a high level such that it amounts to using a generic computer with generic machine learning models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. Further the recitation of an AI engine comprising one or more machine learning models in the claims does not negate the mental nature of these limitations because the AI engine is merely used at a tool to perform an otherwise mental process.
With regards to Applicant’s argument that the claimed invention provides a specific technical improvement to inventory management, enables more granular inventory categorization and the like these argued ‘practical’ applications and/or ‘improvements’ are at best improvements in the abstract idea itself (i.e. business solution to business problems). The argued wished-for benefits do not integrate the abstract idea into a practical application, do not provide a technical solution to a technical problem, do not improve the underlying technology (e.g. process, memory, AI, etc.) and does not improve another technical field (e.g. inventory management, demand forecasting, etc. are not technical fields, they are well-known, established, conventional and routine economic practices).
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).
Accordingly, the claims do not integrate the abstract idea into a practical application and 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.
As discussed above, the claims are directed to both a fundamental economic practice (demand forecasting, alerting) as well as directed to a series of mental process steps readily capable of being performing by a human mind or via pen and paper. At best the recited generic computing elements (e.g. processor, memories, AI engine, etc.) are mere instructions to apply the abstract idea and merely involve generic computers performing generic computer functions of retrieving, processing and outputting data. 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 demand forecasting in the general field of inventory forecasting/management and would not provide significantly more than the judicial exception itself. The recitation of a generic computer in these claims does not negate the mental nature of these limitations because the generic computing elements are merely used at a tool to perform an otherwise mental process.
Automating the selection of a forecasting algorithm nor utilizing a well-known mathematical approach (Bayesian) to categorize inventory into buckets is not enough for eligibility when it is recited at this level of generality without technical implementation details. See Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (generic speed and efficiency increases from applying a computer to a task do not improve computer functioning); Cel/spin Soft, Inc. y. Fitbit, Ine., 927 F.3d 1306, 1316 (Fed. Cir. 2019) (“But the need to perform tasks automatically is not a unique technical problem.”); Credit Acceptance Corp. v. Westlake Servs., 859 F.3d 1044, 1055 (Fed. Cir. 2017) (“[A]utomation of manual processes using generic computers does not constitute a patentable improvement in computer technology.”’); O/P Techs., 788 F.3d at 1363 (“But relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible.”’).
The claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of demand forecasting (Claims 1, 8) or data processing (Claim 11). 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 independent claims 1, 8 and 11 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.
Examiner suggest Applicant review the recent 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/documents/2024/07/17/2024-15377/2024-guidance-update-on-patent-subject-matter-eligibility-including-on-artificial-intelligence) and the three new Subject Matter Eligibility Examples 47-49 (https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf).
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, 5, 6, 8, 9 and 11 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 11, the claims are directed to the abstract idea of forecast (inventory) demand. 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, forecasting (inventory) demand (Judicial Exception – Yes – organizing human activity). Specifically, the claims are directed to forecasting warehouse level inventory demand (Claims 1, 8) or transmitting categorized inventory data and demand forecast data and generating an alert (Claim 11), wherein forecasting (inventory) demand are a fundamental economic practice that fall into the abstract idea subcategories of sales activities and commercial interactions. Further all of the steps of “retrieve”, “pre-process”, “estimate”, “correct”, adjust”, “classify”, “categorize”, “forecast”, and “send” (Claims 1, 8) and “retrieve”, “pre-process”, “estimate”, “correct”, “adjust”, “classify”, “categorize”, “transmit” and “generate” (Claim 11) recite functions of the demand forecasting are also directed to an abstract idea that falls into the abstract idea subcategories of sales activities and commercial interactions. The intended purpose of independent claims 1, 8 and 11 to generate a warehouse level inventory demand forecast.
Accordingly, the claims recite an abstract idea – fundamental economic practice, specifically in the abstract idea subcategories of sales activities and commercial interactions. The exceptions are the user (who is a human, claims 1 and 8 only) and the additional generic computer elements: one or more processors, memory comprising process-executable instructions, user equipment, system, artificial intelligence engine comprising one or more machine learning models (software per se; Specification: Paragraphs 52, 53; Figure 2, Element 214; Figure 4, Element 400), acquisition engine (software per se) , feature engineering module (software per se), event impact module (software per se) and user equipment (Specification: Paragraph 47 – generic computer).
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 comprising process-executable instructions, artificial intelligence engine comprising one or more machine learning models (software per se), acquisition engine (software per se), feature engineering module (software per se), event impact module (software per se) and user equipment. These generic computing components are merely used to acquire/retrieve, process and output/transmit data as described extensively in Applicant’s specification (Figures 2, 10). 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 forecasting in the general field of business 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 in the guidance 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. Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e)- (h)), claims 1, 5, 6, 8, 9 and 11 do not integrate the judicial exception into a practical application.
Regarding the use of the generic (known, conventional) recited one or more processors, memory comprising process-executable instructions, artificial intelligence engine (software per se), acquisition engine (software per se), feature engineering module (software per se), event impact module (software per se) and user equipment 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 AI engine comprising one or more machine learning models for calculating a demand forecast, select an optimal forecast algorithm and categorize each batch of inventory into difference buckets, the AI engine comprising one or more machine learning models is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using generic machine learning models network on a generic computer, also recited at a high level of generality. The AI engine comprising one or more machine learning models is used to generally apply the abstract idea without limiting how the AI engine. The AI engine comprising one or more machine learning models is described at a high level such that it amounts to using a generic computer with generic machine learning models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
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 pre-process the set of data parameters, estimate a demand associated with a product by calculating a demand forecast, correct the calculated demand forecast, automatically select an optimal forecast algorithm, adjust the forecasted demand, classify the product into different batches, categorize the inventory into different buckets and forecast a warehouse level inventory demand (Claims 1, 8); and pre-process the set of data parameters, estimate a demand associated with a product by calculating a demand forecast, correct the calculated demand forecast, automatically select an optimal forecast algorithm, classify the product into different batches, and categorize the inventory into different buckets (Claim 11) 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 a one or more processors, memory comprising process-executable instructions, artificial intelligence engine comprising one or more machine learning models (software per se), feature engineering module (software per se), event impact module (software per se) and user equipment 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 because the steps of receiving a set of data parameters from a data base recites insignificant pre-solution activity (i.e. data gathering). The step of send an alert to one or more users (Claims 1, 8) transmit the categorized inventory data and the demand forecast data (Claim 11) and generate an alert at the UI (Claim 11) recite insignificant post-solution activity (i.e. data output) – wherein it is noted that the intended use of the alert of claims 1 and 8 “to act on product batches that are bound to expire or cause losses” is directed to an non-functional intended use of the alert and has not been given patentable weight (the alert may or may not actually received by the one or more users who may or may not actually act) and the alert generated at the UE and the data transmitted to the UE of Claim 11 may or may not actually received or viewed or acted upon a user/human (mere data on a screen, non-functional descriptive material, extra-solution activity). The mere nominal recitation of a generic processor/computer 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).
As for the recited artificial intelligence engine comprising one or more machine learning models (software per se), the AI engine is recited at a high level of generality and is used by a generic computer/processor, also recited at a high level of generality, to estimate/calculate product demand (mental step, mathematical concept), automatically select a forecasting algorithm and categorize each batch of inventory into different buckets and amounts to no more than mere instructions to implement an abstract idea on a generic computer. The artificial intelligence engine is used to generally apply the abstract idea without limiting how the artificial intelligence engine functions. The artificial intelligence engine comprising one or more machine learning models (software per se) is described at a high level such that it amounts to using a computer with a generic artificial intelligence engine/one or more machine learning models to apply the abstract idea. The recitation of an artificial intelligence engine in the claims does not negate the mental nature of these limitations because the artificial intelligence engine is merely used at a tool to perform an otherwise mental process. The limitations only recite outcomes without any details about how the outcomes are accomplished.
The claims do not integrate the abstract idea into a practical application. The generic one or more processors, memory comprising process-executable instructions, artificial intelligence engine comprising one or more machine learning models (software per se) and user equipment are recited at a high level of generality merely performs generic computer functions of acquire/retrieve, process and output/transmit 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.
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 retrieve and transmit 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).
Regarding the recited AI engine comprising one or more machine learning models for calculating a demand forecast, select an optimal forecast algorithm and categorize each batch of inventory into difference buckets, the AI engine comprising one or more machine learning models is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using generic machine learning models network on a generic computer, also recited at a high level of generality. The AI engine comprising one or more machine learning models is used to generally apply the abstract idea without limiting how the AI engine. The AI engine comprising one or more machine learning models is described at a high level such that it amounts to using a generic computer with generic machine learning models to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. Further the recitation of an AI engine comprising one or more machine learning models in the claims does not negate the mental nature of these limitations because the AI engine is merely used at a tool to perform an otherwise mental process.
The claims are ineligible under 35 U.S.C. 101 as being directed to an abstract idea without significantly more.
Regarding dependent claims 5, 6, and 9, the claims are directed to the abstract idea of forecasting and/or alerting and merely further limit the abstract idea claimed in independent claims 1, 8 and 11.
Claim 5 further limits the abstract idea by estimate a future category of inventory level based on the forecasted demand (a more detailed abstract idea remains an abstract idea). Claim 6 further limits the abstract idea by providing and updating key metrics (a more detailed abstract idea remains an abstract idea). Claim 9 further limits the abstract idea by predicting demand forecast data for one or more upcoming weeks (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, 5, 6, 8, 9 and 11, Applicant’s specification discloses that the claimed elements directed to a user (human) and the additional generic computing elements comprising processor, memory, AI engine (software per se) acquisition engine (software per se), feature engineering module (software per se), event impact module (software per se) and user equipment at best merely comprise generic computer hardware which is commercially available (Figures 2, 10). 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.
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 computer implemented method is at best recite generic, well-known hardware. However, the recited generic hardware simply performs generic computer function of storing, accessing, displaying or 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.
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 one or more processors, memory comprising process-executable instructions, artificial intelligence engine (software per se) and user equipment merely comprise generic computer hardware which is commercially available (Specification: Figures 2, 10; Paragraphs 52, 53; Figure 4, Element 400). 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.
Conclusion
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SCOTT L. JARRETT
Primary Examiner
Art Unit 3625
/SCOTT L JARRETT/Primary Examiner, Art Unit 3625