Status of Claims
This action is in reply to the communications filed on 2/18/2025.
Claims 1, 10-11, and 20 have been amended.
Claims 1-4, 6-14, and 16-20 are currently pending and have been examined.
Response to Applicant’s Remarks
Applicant’s arguments and remarks filed on 2/18/2026, have been fully considered and each argument will be respectfully addressed in the following final office action.
Response to 35 U.S.C. § 101 Remarks
Applicant’s remarks filed on pages 9-17 of the Response concerning the 35 U.S.C. § 101 rejection of the claims have been fully considered but are found not persuasive and are moot in view of the amended rejection that may be found starting on page 20 of this final office action.
On pages 9-10 of the Response, the Applicant argues “Similar to Enfish, independent claim 1 includes computations that are not abstract, but are instead applied in a structural and integrated way that results in an improvement to computer-related technology…By executing moving algorithms in parallel threads, the method reduces computational load and processor cycles compared to sequential execution, thereby improving processing efficiency of a computer system. The processing time determination module ensures improved responsiveness of the computer system by permitting generation of the updated second models only while total processing time remains within a pre-configured threshold condition. This prevents infinite iterations and avoids computer system shutoff of spiraling loops that would otherwise degrade the computer performance and increase computational load and response time…Collectively, these features enhance computational efficiency, increase system responsiveness, and delivery practical improvements in vehicle dispatching and last-mile delivery operations”.
The Examiner respectfully disagrees that the independent claims recite additional elements that reflect an improvement to computer-related technology and integrate the abstract idea into a practical application. As currently drafted, the amended claim elements directed towards “continuing generating, via the model provision and generation module, an updated second model based on the second model if a processing time determination module determines that total processing time remains within a pre-configured threshold condition” are recited at a high level of generality such that they merely serve as generic computer instructions and tools to apply the abstract idea. As disclosed by the Applicant in the specification, the “design in this disclosure also achieves high performance, which means that is can obtain high quality solutions (as close to the optimal solution as possible) – within a reasonable time…. And resources (CPU and memory)” ¶ [0130]) and this “greatly speeds up the overall search algorithms and allows it to obtain a high-quality solution within a reasonable time” (¶ [0136]). Thus, the specification, at most, describes the inherent advantages of applying the abstract idea on a computer. The Examiner notes “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” (see MPEP 2106.05(f)(2)). Although limiting the amount of processing time to generate a model could result in a reduction of computing resources consumed, the specification, at most, describes this as an incidental result of applying the abstract idea to a technical environment using generic computer tools and instructions which inherently increases the speed and efficiency of performing the abstract idea. Furthermore, the Examiner notes, “The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets for an improvement but in a conclusory manner (i.e., a bare asserting of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.” MPEP 2106.04(d)(1).
Furthermore, the Examiner notes Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). In that case, similar to here, “[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement” because “[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning.” Id. at 12.
On page 11 of the Response, the Applicant argues that the features of amended independent claim 1 do not recite concepts of mental processes, commercial interactions, or mathematical concepts. The Examiner respectfully disagrees that the amended independent claims do not recite an abstract idea. The independent claims, as a whole, are directed towards identifying an optimal model by determining the effectiveness of various models based on particular inputs and parameters, selecting an initial optimal model based on effectiveness, generating a second model from the initial optimal model using a moving algorithm, determining whether an effectiveness of the second model is greater than that of the initial optimal model, adjusting weights of the models based on the determined effectiveness, continuing generating an updated second model, setting an updated second model as a current optimal model in response to a result of the determination to select an optimal route, and re-routing a vehicle to the selected optimal route in-real time. These limitations recite concepts of collecting information, comparing information, analyzing information, and displaying a particular result of the collection and analysis of information in a manner that is analogous to human mental work. The claim steps directed towards generating models using algorithms, evaluating/comparing effectiveness of the models, selecting models based on their effectiveness, and adjusting the models are currently recited at a high level of generality such that they could be practically performed by a human using mental steps as described above. Furthermore, the utilization of moving algorithms to generate mathematical models to minimize route expense parameters and adjusting weights of the mathematical models recite concepts of mathematical calculations and relationships. Furthermore, these limitations, as a whole, are directed towards identifying optimal models to reduce/minimize expense parameters associated with delivery routes, selecting optimal routes to locations, and re-routing vehicles to selected optimal routes. Thus, the claim recites concepts of commercial interactions in the form of business relations. This is further evidence by the specification at ¶ [0044].
On pages 12 of the Response, the Applicant argues that “some steps of amended independent claim 1 is similar to at least claim 1 of Example 40”. Furthermore, the Applicant argues, on page 13 of the Response, “Claim 1 of Example 40 not only collect data but utilizes the collected data to analyze the cause of abnormal condition for traffic volume on the network and hindrance of network performance. Similarly, amended independent claim 1 not only collects data regarding location and vehicle type and generates optimal models based on the collected data but also processes the collected data in a way that improves the performance of a computer system”.
The Examiner respectfully disagrees the amended independent claim 1 recites similar patent eligible features to those recited in claim 1 of Example 40. The patent eligible claim 1 of Example 40 provides a technical improvement in collecting traffic data by limiting the collection of additional Netflow protocol data to when the initially collected data reflects an abnormal condition, which avoids excess traffic volume on the network and hindrance of network performance. The collected data can then be used to analyze the cause of the abnormal condition, thus providing a specific technical improvement and solution to a problem rooted in technology.
Amended claim 1, however, describes high level steps for retrieving parameters to determine an effectiveness of each of the first models in minimizing route expense parameters, generating a second model from an initial optimal model by selecting a moving algorithm, comparing effectiveness of the models in reducing route expense parameters, adjusting weights of the models, and continuing generating an updated second model. As discussed above, these claim elements are considered to recite an abstract idea and, as such, are not considered as additional elements that reflect a technical improvement to the functioning of a computer. Furthermore, the amended independent claims, as currently drafted, merely describe collecting inputs (i.e. input data) and generating outputs/models at a high level of generality (i.e., “generating…a second model from the initial optimal model by executing a mover component to select a moving algorithm…the moving algorithm selected based on a weightage”, “continuing generating…an updated second model based on the second model if a processing time determination module determines that the total processing time remains within a pre-configured threshold condition”) without further technical details describing how the outputs (i.e., the models) are reached beyond generally asserting that they are generated based on a “moving algorithm selected based on a weightage…wherein the mover component executes the moving algorithm in a parallel thread”, “increasing the weightage”, and “continuing generating…an updated second model based on the second model if…total processing time remains within a pre-configured within a pre-configured threshold condition”. As such, the additional elements of the claim are considered to merely serve as generic computer tools and instructions to apply the abstract idea and, as such, cannot be considered to integrate the abstract idea into a practical application. See MPEP 2106.05(f).
On pages 13-14 of the Response, the Applicant argues “claim 1 reflect “an improvement in the functioning of a computer, or an improvement to other technology or technical field”…the claim elements, when considered as a whole and read in light of specification, reflect a specific and structure computer-implements technique that facilitates accurate and dynamic route optimization in real-time to increase responsiveness of the system to generate an optimal route without increasing computational load”.
The Examiner respectfully disagrees that the independent claims recite additional elements that reflect an improvement to the functioning of a computer. As discussed further above, as disclosed by the Applicant in the specification, the “design in this disclosure also achieves high performance, which means that is can obtain high quality solutions (as close to the optimal solution as possible) – within a reasonable time…. And resources (CPU and memory)” ¶ [0130]) and this “greatly speeds up the overall search algorithms and allows it to obtain a high-quality solution within a reasonable time” (¶ [0136]). Thus, the specification, at most, describes the inherent advantages of applying the abstract idea on a computer. Moreover, “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” (see MPEP 2106.05(f)(2)).
Furthermore, as discussed further above, the independent claim limitations directed towards identifying an optimal model by determining the effectiveness of various models based on particular inputs and parameters, selecting an initial optimal model based on effectiveness, generating a second model from the initial optimal model using a moving algorithm, determining whether an effectiveness of the second model is greater than that of the initial optimal model, adjusting weights of the models based on the determined effectiveness, continuing generating an updated second model, setting an updated second model as a current optimal model in response to a result of the determination to select an optimal route, and re-routing a vehicle to the selected optimal route in-real time are considered to be a part of the abstract idea itself and, as such, are not considered to reflect an improvement to technology.
On page 14 of the Response, the Applicant argues “independent claim 1 recites a detailed workflow that adaptively identifies an optimal model to select an optimal route for a delivery location and re-route a vehicle to the optimal route to reach the delivery location without increasing computational load of the system…this reduces route expense parameters and computational load”. As discussed further above, the independent claim limitations directed towards identifying an optimal model by determining the effectiveness of various models based on particular inputs and parameters, selecting an initial optimal model based on effectiveness, generating a second model from the initial optimal model using a moving algorithm, determining whether an effectiveness of the second model is greater than that of the initial optimal model, adjusting weights of the models based on the determined effectiveness, continuing generating an updated second model, setting an updated second model as a current optimal model in response to a result of the determination to select an optimal route, and re-routing a vehicle to the selected optimal route in-real time are considered to be a part of the abstract idea itself and, as such, are not considered to reflect an improvement to technology. The additional elements of the amended independent claims, including “wherein the mover component executes the moving algorithm in a parallel thread” and “continuing generating, via the model provision and generation module, an updated second model based on the second model if a processing time determination module determines that total processing time remains within a pre-configured threshold condition” merely serve as high level, generic computer tools and instructions to apply the abstract idea.
On pages 15-17 of the Response, the Applicant argues that the amended independent claims amount to significantly more. Furthermore, on page 17 of the Response, the Applicant argues “amended independent claim 1 describes a non-conventional computer-implemented method for adaptively identifying an optimal routing model to route vehicle to a specific transport task in real-time … It provides a specific technical solution that improves delivery accuracy and enhances dynamic resource allocation that are critical for applications such as instant delivery platforms, thereby resulting in improved response time, and reduced computational loads”.
The Examiner respectfully disagrees that the amended independent claims recite additional elements that provide “significantly more” than the abstract idea. As discussed further above, the additional elements of amended independent claim 1 are considered to be recited at a high level of generality such that they merely serve as generic computer tools and instructions to apply the abstract idea. In particular, the additional elements of amended independent claim 1 include a “computing system comprising at least one processor and a memory, to implement a routing optimizer”, “a model provision and generation module”, “a parameter retrieval module”, “an optimal model selection module”, “processing time determination module”, steps involving “generating, via the model provision and generation module, a second model from the initial optimal model by executing a mover component to select a moving algorithm from a plurality of moving algorithms”, steps involving “the mover component execut[ing] the moving algorithm in a parallel thread”, and steps for “continuing generating, via the model provision and generation module, an updated second model based on the second model if a processing time determination module determines that total processing time remains within a pre-configured threshold condition”. These additional elements are not integrated into a practical application because the invention merely applies the abstract idea to generic computer technology, using the generic computer components to provide information (“providing… more than one first models…”), retrieve information (“retrieving… one or more first parameters…”), make selections (“selecting… an initial optimal model…”, “setting… the second model as a current optimal model…”), make determinations (“determining… if an effectiveness…”), execute high level instructions for generating a second model by executing a mover component that selects and executes a moving algorithm in a parallel thread, and execute high level instructions for continuing generating a second model based on a processing time threshold condition. Because the invention is using a computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. See MPEP 2106.05(f).
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements in combination are recited at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic computer components. Because merely “applying” the exception using generic computer components cannot provide an inventive concept, the additional elements do not recite significantly more than the judicial exception. See MPEP 2106.05(I)(A).
Response to 35 U.S.C. § 102 Remarks
Applicant’s remarks filed on pages 18-20 of the Response concerning the 35 U.S.C. § 102 rejection of claims have been fully considered and are considered to be persuasive. In view of the amendments, the independent claims and their dependents are found to overcome the prior art of record. The Examiner has provided a detailed explanation of why the claims are found to overcome the pertinent prior art of record on page 33 herein.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Regarding claims 1 and 11, the three prong test to determine if 35 U.S.C. § 112(f) can be invoked was applied.
Claim 1 recites the limitations (1.) “providing, via a model provision and generation module, more than one first models…”, (2.) “retrieving, via a parameter retrieval module, one or more first parameters…”, (3.) “selecting, via an optimal model selection module, an initial optimal model…”, (4.) “generating, via the model provision and generation module, a second model…”, (5.) “determining, via the optimal model selection module, if an effectiveness of the second model…”, (6.) “continuing generating, via the model provision and generation module, an updated second module…” and (7.) “dynamically setting, via the optimal model selection module, the second model…”. Thus, these limitations use generic placeholders for the term “means” for performing the claimed function of the respective limitations. The generic placeholder for the term “means” in each limitation is subsequently modified by the functional language “configured to”. The generic placeholder for the term “means” in each limitation is not modified by sufficient structure, material, or acts for performing the claimed functions.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “providing…. more than one first models…”. The limitation “providing, via a model provision and generation module, more than one first models…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”.
The term “parameter retrieval module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “parameter retrieval module” is modified by the functional language “retrieving…one or more first parameters…”. The limitation “retrieving, via a parameter retrieval module, one or more first parameters…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “selecting… an initial optimal model…”. The limitation “selecting, via an optimal model selection module, an initial optimal model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0084] as “the optimal model selection module 208 is configured to select one of the one or more first models based on its effectiveness, e.g., one that has a highest effectiveness among all first models, and identify it as the optimal model”.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “generating… a second model…”. The limitation “generating, via the model provision and generation module, a second model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0088] as “the new model is one of many new models and the model provision and generation module 202 is configured to generate the new model (i.e., the one of the many new models) from the optimal model based a weightage. More particularly, the new model having a highest weightage as compared to that of the remaining new models are identified”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “determining… if an effectiveness of the second model…”. The limitation “determining, via the optimal model selection module, if an effectiveness of the second model… has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0088] as “the optimal model selection module is configured to set the new model as the new optimal model in response to determining that the effectiveness of the new model is also greater than the effectiveness of the previously generated new model”.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “continuing generating […] an updated second module…”. The limitation “continuing generating, via the model provision and generation module, an updated second module…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0091] as “The model provision and generation module 202 is configured to continue generating a new model based on the updated optimal model if the processing time determination module 220 determines that the total processing time does not exceed the pre-configured threshold condition”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “dynamically setting… the second model…”. The limitation “dynamically setting, via the optimal model selection module, the second model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0085] as “the optimal model selection module 208 set/update the new model as the new/updated optimal model in response to a result of the determination, for example that the effectiveness of the new model is indeed greater than that of the optimal model in minimizing the route expense parameter”.
Claim 11 recites the limitations (1.) “provide, via a model provision and generation module, more than one first models…”, (2.) “retrieve, via a parameter retrieval module, one or more first parameters…”, (3.) “select, via an optimal model selection module, an initial optimal model…”, (4.) “generate, via the model provision and generation module, a second model…”, (5.) “determine, via the optimal model selection module, if an effectiveness of the second model…”, (6.) “continue generating, via the model provision and generation module, an update second model…” and (7.) “dynamically set, via the optimal model selection module, the second model…”. Thus, these limitations use generic placeholders for the term “means” for performing the claimed function of the respective limitations. The generic placeholder for the term “means” in each limitation is subsequently modified by the functional language “configured to”. The generic placeholder for the term “means” in each limitation is not modified by sufficient structure, material, or acts for performing the claimed functions.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “provide…. more than one first models…”. The limitation “provide, via a model provision and generation module, more than one first models…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”.
The term “parameter retrieval module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “parameter retrieval module” is modified by the functional language “retrieve…one or more first parameters…”. The limitation “retrieve, via a parameter retrieval module, one or more first parameters…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “select… an initial optimal model…”. The limitation “select, via an optimal model selection module, an initial optimal model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0084] as “the optimal model selection module 208 is configured to select one of the one or more first models based on its effectiveness, e.g., one that has a highest effectiveness among all first models, and identify it as the optimal model”.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “generate… a second model…”. The limitation “generate, via the model provision and generation module, a second model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0088] as “the new model is one of many new models and the model provision and generation module 202 is configured to generate the new model (i.e., the one of the many new models) from the optimal model based a weightage. More particularly, the new model having a highest weightage as compared to that of the remaining new models are identified”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “determine… if an effectiveness of the second model…”. The limitation “determine, via the optimal model selection module, if an effectiveness of the second model… has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0088] as “the optimal model selection module is configured to set the new model as the new optimal model in response to determining that the effectiveness of the new model is also greater than the effectiveness of the previously generated new model”.
The term “model provision and generation module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “model provision and generation module” is modified by the functional language “continue generating […] an updated second module…”. The limitation “continue generating, via the model provision and generation module, an updated second module…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0091] as “The model provision and generation module 202 is configured to continue generating a new model based on the updated optimal model if the processing time determination module 220 determines that the total processing time does not exceed the pre-configured threshold condition”.
The term “optimal model selection module” is considered to be a generic placeholder for the term “means” for performing the claimed function of the limitation. The generic placeholder “optimal model selection module” is modified by the functional language “dynamically set… the second model…”. The limitation “dynamically set, via the optimal model selection module, the second model…” has therefore been interpreted under 35 U.S.C. 112(f) as a means plus function limitation. The corresponding structure or acts being recited in specification ¶ [0183] as a “model identification server”, and the corresponding algorithm recited in specification ¶ [0085] as “the optimal model selection module 208 set/update the new model as the new/updated optimal model in response to a result of the determination, for example that the effectiveness of the new model is indeed greater than that of the optimal model in minimizing the route expense parameter”.
Therefore, the limitations discussed above are considered to have invoked 35 U.S.C. § 112(f) and should be treated accordingly. Furthermore, no other terms in claims exist that would impart structure to the aforementioned generic placeholder terms to remove these limitations from 35 U.S.C. § 112(f).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 6-14, and 16-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
First of all, claims must be directed to one or more of the following statutory categories: a process, a machine, a manufacture, or a composition of matter. Claims 1-4 and 6-10 are directed to a process (“a method”) and claims 11-14 and 16-20 are directed to a machine (“a system”).
Thus, claims 1-4, 6-14, and 16-20 satisfy Step One because they are all within one of the four statutory categories of eligible subject matter. Claims 1-4, 6-14, and 16-20, however, are directed to an abstract idea without significantly more.
Regarding independent claim 1, the specific limitations that recite an abstract idea are:
Providing […] more than one first models based on a routing characteristic associated with input data, wherein the input data comprises the location and a vehicle type;
Retrieving […] one or more first parameters associated with the routing characteristic to determine an effectiveness of each of the first models in minimizing a route expense parameter;
Selecting […] an initial optimal model from the one or more first models based on the effectiveness.
Generating […] a second model from the initial optimal model […] select a moving algorithm from a plurality of moving algorithms, the moving algorithm selected based on a weightage, wherein the second model is one of a plurality of second models […];
Determining […] if an effectiveness of the second model in minimizing the route expense parameter is greater than that of the initial optimal model; and
Increasing the weightage of the second model and decreasing the weightage of the initial model based on the determined effectiveness;
Continuing generating […] an updated second model based on the second model […];
Dynamically setting based on the updated weightage […] the updated second model as a current optimal model in response to a result of the determination to select the optimal route to the location in real-time.
Re-routing a vehicle to the selected optimal route to the location in real-time.
Therefore, claims 1 and 2-4, 6-10, by virtue of dependence, recite features for collecting information (providing more than one first models based on a routing characteristic associated with input data, retrieving one or more first parameters to determine an effectiveness of each of the first models in minimizing a route expense parameter), organizing information (generating a second model by selecting a moving algorithm from a plurality of algorithms based on a weightage wherein the second model is one of a plurality of second models, and continuing generating an updated model based on the second model), and evaluating information to make a judgement (selecting an initial optimal model based on the effectiveness, determining if an effectiveness of the second model in minimizing the route expense parameter is greater than that of the initial optimal model, and dynamically setting, based on an updated weightage, an updated second model as a current optimal model in response to a result of the determination), which is the abstract idea of mental processes. These limitations are recited at a high level of generality and, as such, a human using mental steps would be reasonably capable of performing them as currently drafted. Furthermore, these limitations, as a whole, are directed towards identifying optimal models to reduce/minimize expense parameters associated with delivery routes and selecting optimal routes to locations and re-routing a vehicle to a selected optimal route in real-time. Thus, the claim recites concepts of commercial interactions in the form of business relations. This is further evidence by the specification at ¶ [0044]. Furthermore, the limitations directed towards generating a second model from an initial model by selecting a moving algorithm and adjusting weightages of the models based on determined effectiveness recite concepts of mathematical calculations and relationships.
The judicial exception recited above is not integrated into a practical application. The additional elements of the claims are various generic technologies and computer components to implement the abstract idea (“computing system comprising at least one processor and a memory, to implement a routing optimizer”, “a model provision and generation module”, “a parameter retrieval module”, “an optimal model selection module”, “processing time determination module”, steps involving “generating, via the model provision and generation module, a second model from the initial optimal model by executing a mover component to select a moving algorithm from a plurality of moving algorithms”, steps involving “the mover component execut[ing] the moving algorithm in a parallel thread”, and steps involving “continuing generating, via the model provision and generation module, an updated second model based on the second model if a processing time determination module determines that total processing time remains within a pre-configured threshold condition”). These additional elements are not integrated into a practical application because the invention merely applies the abstract idea to generic computer technology, using the generic computer components and instructions to provide information (“providing… more than one first models…”), retrieve information (“retrieving… one or more first parameters…”), make selections (“selecting… an initial optimal model…”, “setting… the second model as a current optimal model…”), make determinations (“determining… if an effectiveness…”), execute high level instructions for generating a second model by executing a mover component that executes a moving algorithm in a parallel thread, and execute high level instructions for continuing generating a second model based on a processing time threshold condition. Because the invention is using a computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. See MPEP 2106.05(f).
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements in combination are recited at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic computer components. Because merely “applying” the exception using generic computer components cannot provide an inventive concept, the additional elements do not recite significantly more than the judicial exception. See MPEP 2106.05(I)(A). Thus, claim 1 is not patent eligible.
Regarding independent claim 11, the specific limitations that recite an abstract idea are:
Provide […] first models based on a routing characteristic associated with input data, wherein the input data comprises a location and a vehicle type;
Retrieve […] one or more first parameters associated with the routing characteristic to determine an effectiveness of each of the first models in minimizing a route expense parameter;
Select […] the optimal model from the one or more first models based on the effectiveness.
Generate […] a second model from the initial optimal model […] select a moving algorithm from a plurality of moving algorithms, the moving algorithm selected based on a weightage, wherein the second model is one of a plurality of second models […];
Determine […] if an effectiveness of the second model in minimizing the route expense parameter is greater than that of the initial optimal model;
Increase the weightage of the second model and decrease the weightage of the initial model based on the determined effectiveness;
Dynamically set based on the updated weightage […] the updated second model as a current optimal model in response to a result of the determination to select the optimal route to the location in real-time; and
Re-route a vehicle to the selected optimal route to the location in real-time.
Therefore, claims 11 and 12-14, 16-20, by virtue of dependence, recite features for collecting information (providing more than one first models based on a routing characteristic associated with input data, retrieving one or more first parameters to determine an effectiveness of each of the first models in minimizing a route expense parameter), organizing information (generating a second model by selecting a moving algorithm from a plurality of algorithms based on a weightage wherein the second model is one of a plurality of second models, and continuing generating an updated second model based on the second model), and evaluating information to make a judgement (selecting an initial optimal model based on the effectiveness, determining if an effectiveness of the second model in minimizing the route expense parameter is greater than that of the initial optimal model, and dynamically setting, based on an updated weightage, an updated second model as a current optimal model in response to a result of the determination), which is the abstract idea of mental processes. These limitations are recited at a high level of generality and, as such, a human using mental steps would be reasonably capable of performing them as currently drafted. Furthermore, these limitations, as a whole, are directed towards identifying optimal models to reduce/minimize expense parameters associated with delivery routes and selecting optimal routes to locations and re-routing a vehicle to a selected optimal route in real-time. Thus, the claim recites concepts of commercial interactions in the form of business relations. This is further evidence by the specification at ¶ [0044]. Furthermore, the limitations directed towards generating a second model from an initial model by selecting a moving algorithm and adjusting weightages of the models based on determined effectiveness recite concepts of mathematical calculations and relationships.
The judicial exception recited above is not integrated into a practical application. The additional elements of the claims are various generic technologies and computer components to implement the abstract idea ( “system”, “processor”, “memory including computer program code”, “a model provision and generation module”, “a parameter retrieval module”, “an optimal model selection module”, “generating, via the model provision and generation module, a second model from the initial optimal model by executing a mover component to select a moving algorithm from a plurality of moving algorithms”, steps involving “the mover component execut[ing] the moving algorithm in a parallel thread”, and steps involving “continuing generating, via the model provision and generation module, an updated second model based on the second model if a processing time determination module determines that total processing time remains within a pre-configured threshold condition”). These additional elements are not integrated into a practical application because the invention merely applies the abstract idea to generic computer technology, using the generic computer components and instructions to provide information (“provide… first models…”), retrieve information (“retrieve… one or more first parameters…”), make selections (“select…an initial optimal model from the first models…”, “set …the second model as a current optimal model…”), make determinations (“determine… if an effectiveness…”), execute high level instructions for generating a second model by executing a mover component that executes a moving algorithm in a parallel thread, and execute high level instructions for continuing generating a second model based on a processing time threshold condition. Because the invention is using a computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. See MPEP 2106.05(f).
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements in combination are recited at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic computer components. Because merely “applying” the exception using generic computer components cannot provide an inventive concept, the additional elements do not recite significantly more than the judicial exception. See MPEP 2106.05(I)(A). Thus, claim 11 is not patent eligible.
Dependent claims 2-4, 6-10, 12-14, and 16-20 have been given the full two part analysis, analyzing the additional limitations both individually and in combination. The dependent claims, when analyzed individually and in combination, are also held to be patent ineligible under 35 U.S.C. § 101.
Regarding claim 2, the claim recites steps for collecting information (retrieving one or more first parameters associated with a routing characteristics), analyzing information, and displaying a particular result of the collection and analysis (“for each of the first models, generating at least one of a first route … and wherein the step of selecting the initial optimal model from the first models comprises: identifying that at least one of the first route to the location…of one of the first models as those of the current optimal model”) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 3, the claim recites steps for collecting information (wherein the first parameters comprises at least one of a location coordinate…) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 4, the claim recites steps for collecting information (the steps of retrieving one or more first parameters) and analyzing information (“for the each of the first models, determining a value of the routing expense parameter based on the one or more first parameters of the each of the one or more first models, a high value in the route expense parameter indicating a low effectiveness in minimizing the route expense parameter, wherein the step of selecting the initial optimal model from the one or more first models is based on the value of the route expense parameter”) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 6, the claim recites steps for collecting information, analyzing information, and displaying a particular result of the collection and analysis (“the step of generating the second model from the initial optimal model comprises: generating at least one of a second route to the location, a second vehicle type, a second distance, a second time and a second load of the location”; “wherein the step of setting the second model as the current optimal model in response to a result of the determination comprises: identifying the at least one of the second route to the location, the second vehicle type, the second distance, the second time and the second load of the location of the second model as those of the current optimal model”) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 7, the claim recites steps for collecting information, analyzing information, and displaying a particular result of the collection and analysis (“the step of generating the second route to the location comprises one of:(a) adding a new location to the route; or (b) wherein the location is one of a plurality of locations and the route to the location selected by the current optimal model is a route connecting the plurality of locations in a sequence, removing the location from the route, or switching the sequence of the location and another location of the plurality of locations”) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claims 1 and 6 from which the claim depends.
Regarding claim 8, the claim recites steps for evaluating and comparing information (“determining if the effectiveness of the second model is greater than an effectiveness of a previously generated second model”) - which further describes the abstract idea of mental processes and commercial interactions. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 9, the claim further recites steps for collecting and evaluating information (“wherein the plurality of moving algorithms are each associated with a dynamically updated selection weight based on prior effectiveness in minimizing the route expense parameter”) - which further describes the abstract idea of mental processes and mathematical calculations. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claims 1 from which the claim depends.
Regarding claim 10, the claim recites steps for collecting information, analyzing information, and displaying a particular result of the collection and analysis (“determining if a total number of second models generated or a total processing time exceed the pre-configured threshold condition, the total processing time representing a total time spent in adaptively identifying the current optimal model to select the route to the location, wherein the generation of the second model from the initial optimal route is carried out in response to determining the total number of second models or the total processing time does not exceed the pre- configured threshold condition”)- which further describes the abstract idea of mental processes and mathematical calculations. See MPEP 2106.04(a)(2)(III). The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Regarding claim 12, the limitations are substantially similar and analogous to the limitations of claim 2. Accordingly, claim 12 is found to recite the same abstract idea as discussed above with regard to claim 2. Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 13, the limitations are substantially similar and analogous to the limitations of claim 3. Accordingly, claim 13 is found to recite the same abstract idea as discussed above with regard to claim 3. The limitations of this claim fail to integrate the abstract idea into a practical application because this claim does not introduce or recite additional elements other than the generic computer components of claim 11 discussed above, by virtue of dependence. This dependent claim, therefore, also amounts to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional elements of this dependent claim fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 14, the limitations are substantially similar and analogous to the limitations of claim 4. Accordingly, claim 14 is found to recite the same abstract idea as discussed above with regard to claim 4. Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 16, the limitations are substantially similar and analogous to the limitations of claim 6. Accordingly, claim 16 is found to recite the same abstract idea as discussed above with regard to claim 6. Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 17, the limitations are substantially similar and analogous to the limitations of claim 7. Accordingly, claim 17 is found to recite the same abstract idea as discussed above with regard to claim 7. Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 18, the claim recites steps for collecting information, analyzing information, and displaying a particular result of the collection and analysis (“determining if the effectiveness of the second model is greater than an effectiveness of a previously generated second model”; “wherein the setting of the second model as the current optimal model is carried out in further response to determining the effectiveness of the second model being greater than the effectiveness of the previously generated second model”), which is the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III). Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 19, the limitations are substantially similar and analogous to the limitations of claim 9. Accordingly, claim 19 is found to recite the same abstract idea as discussed above with regard to claim 9. The limitations of this claim fail to integrate the abstract idea into a practical application because this claim does not introduce or recite additional elements other than the generic computer components of claim 11 discussed above, by virtue of dependence. This dependent claim, therefore, also amounts to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional elements of this dependent claim fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Regarding claim 20, the limitations are substantially similar and analogous to the limitations of claim 10. Accordingly, claim 20 is found to recite the same abstract idea as discussed above with regard to claim 10. Furthermore, the additional elements of this claim fail to integrate the abstract idea into a practical application because the additional elements of the claim are generic computer components and tools to implement the abstract idea (“the at least one memory and the computer program code configured to, with the at least one processor, cause the server at least to…”). Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application. Finally, the additional elements of this dependent claim fail to establish that the claim provides an inventive concept because claims that merely use generic computer components as a tool to perform the abstract idea cannot provide an inventive concept. See MPEP 2106.05(I)(A).
Examiner Notes
Independent claims 1 and 11 have been found to overcome the cited art of record. Further, claims 2-3, 6-10, 12-14, and 16-20, by virtue of dependence, recite the same limitations as claims 1 and 11 that overcome the cited art of record. The following is a statement of reasons for the indication of claims 1 and 11 being found to overcome the cited art of record. None of the prior art of record, taken individual or in combination, teach or suggest the specific series of logical operations of independent claims 1 and 11. Further, it would not have been obvious to one of ordinary skill in the art to have combined the teachings or suggestions of the prior art of record without the benefit of hindsight.
The prior art references most closely resembling the Applicant’s claimed invention are as follows:
Zhang et al. U.S. Publication No. 2020/0124429;
Hart et al. U.S. Patent No. 10,452,993;
Leach et al. U.S. Patent No. 11,526,261;
Zhang discloses a computer implemented method and apparatus for determining routing using reinforcement learning (RL). The apparatus is configured to initialize a state of an RL model based on a routing solution comprising one or more routes, and apply improvement and perturbation actions to the state in order to reduce a cost of a routing solution. The RL models may utilize any combination of optimization algorithms from among various algorithms to apply the improvement actions. Moreover, the method may use a plurality of different RL models to calculate an optimal routing solution, where each RL model is trained using different state representations that have different emphasis when suggesting actions to take. Multiple RL models may run in parallel, where each RL model may be iteratively updated with improvement actions until the cost of the routing solutions cannot be reduced further and the best routing solution can be identified from the multiple RL models. Zhang, however, does not explicitly teach the specific series of logical operations recited in independent claims 1 and 11. In particular, Zhang does not teach increasing the weightage of a second model and decreasing the weightage of an initial model based on a determined effectiveness and continuing generating an updated second model based on the second model if a module determines that total processing time remains within a pre-configured threshold condition.
Hart discloses a system and method for applying personalized machine learning models. The system may leverage multiple algorithms to update and retrain the machine learning models during specified time intervals/windows. Parameters which determine window width and time to retrain models may be fixed or adaptive. Hart, however, does not explicitly teach the specific series of logical operations recited in independent claims 1 and 11. In particular, Hart does not teach increasing the weightage of a second model and decreasing the weightage of an initial model based on a determined effectiveness and continuing generating an updated second model based on the second model if a module determines that total processing time remains within a pre-configured threshold condition.
Leach discloses a system that enables users to apply one or more different statistical forecasting models to input data, and providing the user with the ability to select the best types of forecasting models to apply the input data. The system may further tune selected parameters (e.g., hyperparameters) for different model types, such as to train or modify one or more parameters of the forecasting models to increase or enhance the accuracy of their predictions. The models may be adjusted by changing one or more model coefficients. Leach, however, does not explicitly teach the specific series of logical operations recited in independent claims 1 and 11. In particular, Leach does not teach increasing the weightage of a second model and decreasing the weightage of an initial model based on a determined effectiveness and continuing generating an updated second model based on the second model if a module determines that total processing time remains within a pre-configured threshold condition.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORGE G DEL TORO-ORTEGA whose telephone number is (571)272-5319. The examiner can normally be reached Monday-Friday 9:00AM-6:00PM.
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/JORGE G DEL TORO-ORTEGA/Examiner, Art Unit 3628
/JEFF ZIMMERMAN/Supervisory Patent Examiner, Art Unit 3628
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