DETAILED ACTION
This FINAL office action is in response to Applicant’s amendment filed April 14, 2025. In Applicant’s April 14th amendment Applicant amended claims 1 and 26 and canceled claims 2-10, 12, 15-21, 25, 27, 29, 36. Claims 1, 11, 13, 14, 22-24, 26, 28 and 30-35 are pending. Claims 1 and 26 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The 35 U.S.C. 112a rejection of claims 2-4 in the previous office action is withdrawn in response to Applicant's cancelation of claims 2-4 and 27-29.
The 35 U.S.C. 112b rejection of claims 2 and 4 in the previous office action is withdrawn in response to Applicant's cancelation of claims 2, 4, 27 and 29.
The 35 U.S.C. 101 rejection of claims 1, 11, 13, 14, 22-24, 26, 28 and 30-35 in the previous office action is maintained.
Response to Arguments
Examiner notes that none of the claims were rejected under 35 U.S.C. 112(f) in the previous office action (Remarks: Pages 8, 9), accordingly these arguments are not applicable the current or previous grounds of rejection and will not be addressed.
Applicant's arguments filed April 14, 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 not directed to an abstract idea/cannot be performed mentally (e.g. AI/ML steps cannot be practically performed in human mind, inherently computational operations that require machine execution; Remarks: Last Paragraph, Page 16; Paragraphs 1-2, Page 17); claims integrate the abstract idea into a practical application (e.g. improvement in the machine learning MODEL itself, creates a more computationally efficient model, identifying and eliminating inputs that cause degradation that measurable reduces processing demand, model refinement, post simulation action - automatically select a carrier - concrete application affecting the movement of physical goods; Specification: Paragraphs 5, 6, 70, 71, 75 Remarks: Last Paragraph, Page 17; Pages 18-20); the claims recite significantly more than the abstract idea (e.g. sensors constitute particular machines, claimed elements are not well-understood, routine, conventional, more than data processing, non-conventional arrangement; Specification: Paragraphs 34, 37; Remarks: Last Two Paragraphs, Page 20; Pages 21, 22); and the claims
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 practically performed mentally, the examiner notes that the claims are not rejected under 35 U.S.C. 101 as being directed to a mental process. The claims are rejected under 35 U.S.C. 101 as being directed to a method of organizing human activity – specifically logistics planning/management wherein the recited invention is directed to the well-known economic practice – logistics modeling/simulation (e.g. CPC G06Q10/08 – logistics) – in this case providing a substantially real time visualization of a set of value chain entities and a simulation data of a future state of at least one of the supply chain entities to a human user as well as generate/transmit an automated control signal to a logistics management application to select a carrier for a physical shipment within the value chain (e.g. see CPC G06Q10/0834 – choice of carriers; CPC G06Q10/083 - shipping). See detailed discussion below.
Accordingly, the claims 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 are directed to a practical application the examiner respectfully disagrees.
The claims are directed to a well-known business practice – logistics modeling/simulation – in this case ‘automatically’ selecting a carrier for a physical shipment within a value chain by generating and transmitting an automated control signal to a logistics management application. While the claims may represent an improvement to the business process of selecting a carrier for a physical shipment within a value chain they in no way either claimed or disclosed represent a practical application. At best the claimed invention is directed to an improvement in the abstract idea itself – selecting a carrier for a shipment and does not disclose or recite an improvement in any of the underlying technological elements (e.g. sensor, processor, etc.), does not disclose or recite an improvement in another technological field (e.g. digital twin, machine learning, etc.) and does not provide a technical solution to a technical problem inherent in computers or computer networks.
Under PEPE 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 MPME 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 processor, adaptive intelligence system (software per se), digital replica (software per se) and logistics management application (software per se). These generic computer hardware merely performs generic computer functions of receiving, processing and providing data and represent a purely conventional implementation of applicant’s value chain entities carrier selection in the general field of modeling/simulating logistics 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 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 machine learned model that is trained/refined in order to ‘transform’ sensor data into simulation data and the digital replica (digital twin) of the value chain entities – each of the machine learning (ML) and digital replicate (DR)/digital twin (DT) are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic machine learned model and/or digital replica on a generic computer/processor, also recited at a high level of generality. The ML and DR/DT are used to generally apply the abstract idea without limiting how the machine learned model or digital replica functions. The machine learned model and digital replica are each described at a high level such that it amounts to using a generic computer with a generic machine learned model and digital replica 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, 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., processor, sensor, 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
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 the claims beyond the abstract idea is a processor, sensors, adaptive intelligence system (software per se) and artificial intelligence system (software per se), logistics management application (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.
With regards to Applicant’s argument that they newly recite step directed to generating/transmitting an automated control signal to a logistics management application integrates the abstract idea into a practical application (e.g. post simulation action, concrete application affecting the movement of goods), the examiner respectfully disagrees. Representative claim 1 recites “wherein the at least one processor is further configured to: generate, based on the simulation of the possible future state, an automated control signal; and transmit the automated control signal to a logistics management application to automatically select a carrier for a physical shipment within the value chain.”), wherein this method step merely recites insignificant post-solution/extra solution activity. The claims do not positively recite or require that the generated/transmitted ‘automated control signal’ is actually received by the logistics management application. The claims do not positively recite or require that the generated/transmitted ‘automated control signal’ actually causes the logistics management application to actually select a carrier. The claims do not positively recite or require selected carrier actually ships or transports a physical shipment of any kind. As such the transmitted ‘automated control signal’ is mere data output.
Even if Applicant were to amend the claims to positively recite that the automated control signal actually resulted physically transporting of an item/product by a selected carrier based on the simulation of a future possible state, the claims would merely be directed to an insignificant application of the abstract idea. Selecting a carrier, even based on a forecasted/simulated/projected/estimated, future state of a value chain is old, well-known, conventional and routine.
See discussion in at least in MPEP 2106.05(g) (Insignificant application: Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016)). As well as described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must “play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly”).
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Other examples where the courts have found the additional elements to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process include: vi. A method of assigning hair designs to balance head shape with a final step of using a tool (scissors) to cut the hair, In re Brown, 645 Fed. App'x 1014, 1017 (Fed. Cir. 2016).
With regards to Applicant’s argument that the newly recited claims improve the machine learning model by identifying and eliminating inputs that cause model degradation (i.e. degrade the accuracy of the model, refine the model) the examiner agrees that the disclosed invention may result in an improvement to the machine learning model’s ability to transform sensor data into simulation data. This is an improvement in the abstract idea and is not directed to an improvement to the general field of machine learning itself. Nowhere is there any support in applicant’s disclosure that the method steps improve the machine learning model/refined machine learning model which is recited at a very high level of generality. Nowhere in Applicant’s disclosure is there any support for Applicant’s argument that the improvement in the machine learning model creates a more computationally efficient model or reduces processing demand. Improving the accuracy of a model is not the same as improving machine learning itself – MPEP § 2106.04(d)(1) with regards to Ex Parte Desjardins, Appeal No. 2024-000567 as well as Subject Matter Eligibility Examples 47-49.
Argued Specification Paragraph 5 discloses that with the advent of smart connected devices, wearable technologies and the Internet of Things the amount of data available to organizations planning, overseeing, managing and operating a value chain network have increased dramatically and that organizations also need to access a wide array of other large data sets. This paragraph does not disclose a technical solution to a technical problem. This paragraph does not disclose an improvement in the functioning of any of the claimed technological elements (e.g. sensors, processor, etc.). This paragraph does not discuss at any level an improvement in another technical field (e.g. digital twin, machine learning). This paragraph does not disclose that the claimed invention integrates the abstract idea into a practical application as claimed.
Argued Specification Paragraph 6, discloses the mode data and new data types offer opportunities for organizations to achieve competitive advantages (a wished-for business benefit) and that users can be overwhelmed with and missing opportunities/needs insights. This paragraph does not disclose a technical solution to a technical problem. This paragraph does not disclose an improvement in the functioning of any of the claimed technological elements (e.g. sensors, processor, etc.). This paragraph does not discuss at any level an improvement in another technical field (e.g. digital twin, machine learning). This paragraph does not disclose that the claimed invention integrates the abstract idea into a practical application as claimed.
Argued Specification Paragraphs 70 and 71 disclose that one of the embodiments of the invention is providing recommendations for designing a logistics system using machine learning, artificial intelligence and digital twins including a logistics system design output (not claimed) or a graphical representation of the digital twin/simulation in order to provide a proposed logistic solution to a user/organization for the purposes of minimizing delay (shipment delay) and comply with regulatory requirements. . This paragraph does not disclose a technical solution to a technical problem. This paragraph does not disclose an improvement in the functioning of any of the claimed technological elements (e.g. sensors, processor, etc.). This paragraph does not discuss at any level an improvement in another technical field (e.g. digital twin, machine learning). This paragraph does not disclose that the claimed invention integrates the abstract idea into a practical application as claimed.
Argued Specification Paragraph 75 discloses that one of the invention embodiments is configured to learn which sensors provide ‘relevant’ data and that the machine learning model is configured to make suggests to a user regarding potential changes to the plurality of sensors that would improve the simulation (e.g. prioritize collection and transmission of sensor data relevant to the dynamics of the value chain entities/simulation, not claimed). This paragraph does not disclose a technical solution to a technical problem. This paragraph does not disclose an improvement in the functioning of any of the claimed technological elements (e.g. sensors, processor, etc.). This paragraph does not discuss at any level an improvement in another technical field (e.g. digital twin, machine learning). This paragraph does not disclose that the claimed invention integrates the abstract idea into a practical application as claimed.
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.
Initially in response to applicant's argument that the recited sensors are particular machines including camera systems, vibration/temperature/pressure monitoring, machine visioning, LIDAR, radiograph, etc. (Remarks: Second to Last Paragraph, Page 20) it is noted that the features upon which applicant relies are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). As representative claim 1 makes clear the claimed sensors are anything position in, on or near physical value chain entities that collect data (“a plurality of sensors positioned at least one of in, on, or near a set of physical value chain entities of the plurality of value chain entities and configured to collect sensor data related to the set of value chain entities, the sensor data being substantially real-time sensor data” -i.e. any and all sensors of any kind, type, class, etc. – as defined by Miriam Webster a sensor is a device that responds to a physical stimulus (such as heat, light, sound, pressure, magnetism, or a particular motion) and transmits a resulting impulse (as for measurement or operating a control). In other words the disclosed and claimed invention merely use sensors for the well-known, conventional, routine and generic function and nothing more. Further nowhere in Applicant’s disclosure is there any discussion at any level of a new or unconventional sensor, using a conventional sensor in a unconventional way or providing a technical solution to a technical problem associated with sensors or a technical improvement to sensors.
Accordingly, the claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of modeling/simulating logistics. In re TLI Commc’ns LLC Pat. Litig., 823 F.3d 607, 612 (Fed. Cir. 2016). The recited technology (e.g. 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”).
Similar to the Uniloc USA, Inc. v. LG Electronics USA, Appeal No. 19-1835 (Fed. Cir. Apr. 30, 2020), in which 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 neither discloses nor claims improvements to computer, computer networks or other technical field.
Regarding the recited machine learned model that is trained/refined in order to ‘transform’ sensor data into simulation data and the digital replica (digital twin) of the value chain entities – each of the ML and DR/DT are recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic machine learned model and/or digital replica on a generic computer/processor, also recited at a high level of generality. The ML and DR/DT are used to generally apply the abstract idea without limiting how the machine learned model or digital replica functions. The machine learned model and digital replica are each described at a high level such that it amounts to using a generic computer with a generic machine learned model and digital replica 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.
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, 11, 13, 14, 22-24, 26, 28 and 30-35 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 and 26, the claims is directed to the abstract idea of logistics modeling/simulation. 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, modeling/simulating value chain logistics (carrier selection) (Judicial Exception – Yes – organizing human activity). Specifically, the claims are directed to in this case provide a substantially real time visualization of a set of value chain entities and a simulation data of a future state of at least one of the supply chain entities as well as generate/transmit an automated control signal to a logistics management application to select a carrier for a physical shipment within the value chain, wherein modeling/simulating logistics (data visualization, carrier selection) is a fundamental economic practice. See MPEP 2106.05. Further all of the steps of “a plurality of sensors…configured collect sensor data…”, “receive the sensor data”, “provide the sensor data”, “input the second training set”, “trained”, “refining”, “generating additional corresponding outputs”, “comparing the current output”, “generating a refined machine learning model”, “transform the sensor data”, “create a digital replica”, “provide a substantially real-time representation”, “generate…an automated control signal” and “transmit the automated control signal” recite functions of the modeling/simulating logistics (data visualization, carrier selection) are also directed to an abstract idea. The intended purpose of independent claims 1 and 26 appears to provide value chain data to a human user/business by providing a substantially real time visualization of a set of value chain entities and a simulation data of a future state of at least one of the supply chain entities as well as generate/transmit an automated control signal to a logistics management application to select a carrier for a physical shipment within the value chain.
Accordingly, the claims recite an abstract idea – fundamental economic practice. The exceptions are the supply chain entities (businesses, organizations, people, suppliers, etc.) and additional limitations of generic computer elements: processor, information technology system (software per se), sensors, adaptive intelligence system (software per se), artificial intelligence system (software per se), digital twin system (software per se) and logistics management application (software per se).
As for the recited machine learning model and refined machine learning/learned model these method steps are recited at a high level of generality and amount to no more than mere instructions to apply the abstract idea using generic machine learning model using a generic computer/computing elements. The machine learning model and refined machine learning model providing nothing more than mere instructions to implement the abstract idea on a generic computer. The machine learning model and refined machine learning model are used to generally apply the abstract idea without limiting how the trained/refined machine learning model function. The machine learning model and refined machine learning model are described at a high level such that it amounts to using a generic computer with a generic machine learning model and refined machine learning model to apply the abstract idea.
Similarly, the recited digital twin and digital replica are recited at a high level of generality and amount to no more than mere instructions to implement/apply the abstract idea using a generic digital twin/replica/simulation using a generic computer. The digital twin, digital replica and simulation are used to generally apply the abstract idea without limiting how the digital twin, digital replica and simulation function. The digital twin, digital replica and simulation are described at a high level such that it amounts to using a generic computer with a generic digital twin, digital replica and simulation to apply the abstract idea.
As for the recited generation and transmission of an automated control signal to a logistics management application to automatically select a carrier for a physical shipment within the value chain, this method step merely recites insignificant post-solution/extra solution activity. The claims do not positively recite or require that the generated/transmitted ‘automated control signal’ is actually received by the logistics management application. The claims do not positively recite or require that the generated/transmitted ‘automated control signal’ actually causes the logistics management application to actually select a carrier. The claims do not positively recite or require selected carrier actually ships or transports a physical shipment of any kind. As such the transmitted ‘automated control signal’ is mere data output.
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: processor, information technology system (software per se), sensors, adaptive intelligence system (software per se), artificial intelligence system (software per se), digital twin system (software per se) and logistics management application (software per se). These generic computing components are merely used to obtain/receive and process information as described extensively in Applicant’s specification (Specification: Paragraphs 1576, 1578).
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 modeling/simulating logistics (data visualization, carrier selection) 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 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, 11, 13, 14, 22-24, 26, 28 and 30-35 do not integrate the judicial exception into a practical application. Regarding the use of the generic (known, conventional) recited " processor, information technology system (software per se), sensors, adaptive intelligence system (software per se), artificial intelligence system (software per se), digital twin system (software per se) and logistics management application (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, 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.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
Regarding dependent claims 4, 11, 13, 14, 22-24, 28 and 30-35, the claims are directed to the abstract idea of modeling/simulating logistics (data visualization, carrier selection) and merely further limit the abstract idea claimed in independent claims 1 and 26.
Claims 11 and 30 further limit the abstract idea by limiting model success to at least one of least noise or lowest cost (a more detailed abstract idea remains an abstract idea). Claims 13 and 31 further limit the abstract idea by identifying impacts on model effectiveness (a more detailed abstract idea remains an abstract idea). Claims 14 and 31 further limits the abstract idea by identifying an input that generates a lower cost model (a more detailed abstract idea remains an abstract idea). Claims 22 and 33 further limits the abstract idea by implementing testing with concept activation vectoring functionality to refine the machine learned model (a more detailed abstract idea remains an abstract idea). Claims 23 and 34 further limit the abstract idea by limiting the digital twin to at least ONE of a warehousing, delivery, product twin corresponding to a physical warehouse, delivery system or product in the value chain (a more detailed abstract idea remains an abstract idea). Claims 24 and 35 further limit the abstract idea by generating a logistics system design recommendation based on the simulation (a more detailed abstract idea remains an abstract idea). Claims 25 and 36 further limits the abstract idea by generating and transmitting an automated control signal to automatically select a carrier for shipment (insignificant post solution activity – data output; 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, 11, 13, 14, 22-24, 26, 28 and 30-35, Applicant’s specification discloses that the claimed elements directed to an processor, information technology system (software per se), sensors, adaptive intelligence system (software per se), artificial intelligence system (software per se), machine learning system (software per se), a digital twin system (software per se), and logistics management application at best merely comprise software executed on generic computer hardware which is commercially available (Specification: Paragraphs 1576, 1578). 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. 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 an processor, information technology system (software per se), sensors, adaptive intelligence system (software per se), artificial intelligence system (software per se), digital twin system (software per se) and logistics management application (software pe merely comprise generic computer hardware which is commercially available (Specification: Paragraphs 1576, 1578). 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. information system, machine learning system – software per se). 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.
Conclusion
The instant application may disclose patentable subject matter however not all of the disclosed potentially patentable subject matter is recited in the claims. An interview with the examiner may be productive. Examiner suggest Applicant review co-pending application numbers 18525831 and 18525816.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Walet et al., U.S. Patent Publication No. 20260065176 discloses a logistics planning system and method comprising pruning inputs from a simulation set/inputs.
Albright et al. 20030093388, discloses a logistics planning system and method including selecting a carrier/delivery option and pruning inefficient delivery options
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.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Beth Boswell can be reached on (571) 272-6737. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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SCOTT L. JARRETT
Primary Examiner
Art Unit 3625
/SCOTT L JARRETT/Primary Examiner, Art Unit 3625
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