DETAILED ACTION
Notice of 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
Applicant’s Amendment and remarks dated 4/23/2026 have been considered. Claims 2, 9, and 16 are cancelled. New claims 21-23 are added. Claims 1, 3-8, 10-15, and 17-23 are pending.
Response to Arguments
On page 8 of Applicant’s 4/23/2026 Amendment and remarks, Applicant states that the amendments are supported by identified portions of the disclosure.
The examiner agrees that the portions of the disclosure identified by Applicant provide sufficient written description support for the claim amendments.
On pages 9-11 of Applicant’s 4/23/2026 Amendment and remarks, with respect to the rejections under 35 U.S.C. 103, Applicant argues that the amendments to the independent claims overcome all pending rejections.
The examiner agrees. All rejections under 35 U.S.C. 103 are hereby withdrawn.
On page 11 of Applicant’s 4/23/2026 Amendment and remarks, with respect to the rejections under 35 U.S.C. 101, with respect to Step 2A, Prong 2, Applicant argues:
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The examiner agrees that the specification sets forth a particular technical problem and solution. However, as explained by MPEP 2106.04(d)(1), such improvement needs to be reflected in the claims. As currently written, the independent claims do not require any improvement to the underlying hardware and software components. The claims simply cover the negotiations between a licensor and licensee, where configurations of hardware and software can be changed and adjusted for purposes of generating an offer to license, but there is no improvement to the hardware and/or software resources during deployment.
On page 12 of Applicant’s 4/23/2026 Amendment and remarks, with respect to the rejections under 35 U.S.C. 101, with respect to Step 2A, Prong 2, Applicant argues:
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The examiner respectfully disagrees. The “initiating one or more automated actions in response to at least one of the one or more uncertainty thresholds of the selected configuration being satisfied during the corresponding time interval, wherein the one or more automated actions comprise generating one or more updated configurations for a remaining portion of the particular period of time and adjusting at least a portion of the one or more of the hardware components and the software components associated with the request” are alternatives, so the “adjusting at least a portion...” claim language identified by Applicant is optional. Moreover, as noted in the prior rejection to dependent claim 3, adjusting at least a portion of the one or more of the hardware components and the software components associated with the request is a mental process, where a human such as a salesperson can adjust the hardware and/or software components used to fulfill the request (e.g., adjusting the number of servers and virtual machines licensed), without making any actual adjustments to the servers or virtual machines themselves.
On pages 12-13 of Applicant’s 4/23/2026 Amendment and remarks, with respect to the rejections under 35 U.S.C. 101, with respect to Step 2B, Applicant argues:
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The examiner respectfully disagrees. MPEP 2106.05(d) explains that the “well-understood, routine, conventional activity” consideration is merely a consideration and not a standalone test for eligibility. Applicant has provided only arguments, and no actual evidence, that the claims recite “unconventional” steps. However, the “predicting” and “generating a plurality of configurations” limitations are mental steps as explained before, and the “automatically adjusting the hardware and/or software components” language argued by Applicant is not in the actual claims themselves. The claims merely require updating configurations, or “adjusting at least a portion of the one or more hardware components and the software components”, which can be an adjustment to the amount (e.g., how many servers), rather than any actual adjustment to the hardware and software itself. Therefore, the examiner does not finds Applicant’s arguments under the “well-understood, routine, conventional activity” consideration” to be persuasive.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-8, 10-15, and 17-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Step 1 of the Alice/Mayo framework, Claims 1, 3-7, and 21 are directed to a method (a process), Claims 8, 10-14, and 22 are directed to a non-transitory processor-readable storage medium (an article of manufacture), and Claims 15, 17-20, and 23 are directed to an apparatus (a machine), which each fall within one of the four statutory categories of inventions.
Regarding Claim 1
Step 2A, prong 1 (Is the claim directed to a law of nature, a natural phenomenon or an abstract idea).
Claim 1 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components (e.g., “computer-implemented”, “processor”, “memory”, “machine learning-based process”).
determining that a value of a first parameter associated with the request varies over the particular period of time; (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can mentally determine that the price for cloud services will vary over a particular period of time)
predicting, ... the value of the first parameter over the particular period of time based at least in part on historical time-series data for the first parameter; (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can look at historical time-series data for the previous year for the same time period, and use such historical data to predict pricing for the following year)
generating a plurality of configurations for the request based at least in part on the predicted value of the first parameter, wherein each of the plurality of configurations corresponds to a different time interval within the particular period of time and comprises: (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can determine different configurations (or bundles) of services over different periods of time)
(i) a second parameter, associated with a type of resource, that is fixed over the corresponding time interval and (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can identify second parameters, such as cloud storage space, where the price is going to be fixed per GB over a time interval)
(ii) one or more uncertainty criteria comprising one or more uncertainty thresholds corresponding to the second parameter, wherein the one or more uncertainty criteria are based at least in part on at least one location associated with the at least one user and at least one type of the one or more of the hardware components and the software components; (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can determine “uncertainty criteria” such as the amount of storage actually used and whether it exceeds a certain storage threshold, and such criteria can be based at least in part on the location of the user because different locations may have different prices due to currency differences)
wherein the one or more (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a sales person can update the configurations for hardware and software for a particular period of time, and reflect such updated potential configuration in a price quote or sales order, and a human can mentally determine how to adjust at least a portion of the hardware components and the software components)
Claim 1 further recites the following limitations that each pertain to a method of organizing human activity, specifically “managing personal behavior or relationships or interactions between people,” which is another type of judicial exception as set forth by MPEP 2106.04(a). Such limitations also pertain to “commercial or legal interactions” which is another type of judicial exception as set forth by MPEP 2106.04(a).
obtaining a request from at least one user for one or more of hardware components and software components over a particular period of time (under the broadest reasonable interpretation, this pertains to the social activity of “providing information to a person” and also to the commercial interactions related to “marketing or sales activities or behaviors”)
obtaining, from the at least one user, a selection of one of the plurality of configurations; and (under the broadest reasonable interpretation, this pertains to the social activity of “providing information to a person” and also to the commercial interactions related to “marketing or sales activities or behaviors”)
Step 2A, prong 2 (Does the claim recite additional elements that integrate the judicial exception into a practical application?).
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements (e.g., “computer-implemented”, “processor”, “memory”, “machine learning-based process”) which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “using a machine learning-based process” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a machine-learning based process. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a machine-learning based process). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Regarding the “initiating one or more automated actions in response to at least one of the one or more uncertainty thresholds of the selected configuration being satisfied during the corresponding time interval, wherein the one or more automated actions comprise ... adjusting at least a portion of the one or more of the hardware components and the software components associated with the request” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation attempts to cover a solution to an identified problem with no restriction on how the result is accomplished, or provides no description of the mechanism for accomplishing the result. 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 (See MPEP 2106.05(f)). Moreover, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of an “automated action”. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (“automated action”). 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 (See MPEP 2106.05(f)).
Regarding the “wherein the method is performed by at least one processing device comprising a processor coupled to a memory” limitation, such limitations are recited at a high-level of generality and amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional elements of a processor and a memory. These additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the exception using generic computer components (a processor and a memory). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B (Does the claim recite additional elements that amount to significantly more than the judicial exception?)
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements (e.g., “computer-implemented”, “processor”, “memory”, “machine learning-based process”) are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “using a machine learning-based process” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding the “initiating one or more automated actions in response to at least one of the one or more uncertainty thresholds of the selected configuration being satisfied during the corresponding time interval, wherein the one or more automated actions comprise ... adjusting at least a portion of the one or more of the hardware components and the software components associated with the request” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation attempts to cover a solution to an identified problem with no restriction on how the result is accomplished, or provides no description of the mechanism for accomplishing the result. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)). Moreover, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding the “wherein the method is performed by at least one processing device comprising a processor coupled to a memory” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 3
Step 2A, Prong 1
sending an alert to the at least one user (under the broadest reasonable interpretation, this pertains to the social activity of “providing information to a person” under the “managing personal behavior or relationships or interactions between people” category of abstract ideas)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 4
Step 2A, Prong 1
obtaining additional time-series data for the first parameter over at least a portion of the time interval corresponding to the selected configuration; and (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human can mentally predict time-series prices over a portion of the time interval corresponding to the selected configuration)
updating the predicted value of the first parameter based at least in part on the additional time-series data. (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can mentally update total pricing predictions)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 5
Step 2A, Prong 2
Regarding the “wherein the machine learning-based process comprises at least one of a linear regression model and an autoregressive model” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a machine learning based process using a particular type of model. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a machine learning based process). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)). Moreover, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Step 2B
Regarding the “wherein the machine learning-based process comprises at least one of a linear regression model and an autoregressive model” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)). Moreover, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding Claim 6
Step 2A, Prong 1
wherein the at least one location is located within a first country, and wherein at least one second location associated with an entity providing the one or more of the hardware components and the software components is located within a different, second country. (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can mentally consider pricing constraints based on the user being in a first country and the hardware/software components being in a different country)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 7
Step 2A, Prong 1
wherein the one or more uncertainty criteria are further based on a type of the at least one user. (under the broadest reasonable interpretation, this limitation can be performed mentally, for example, a human such as a salesperson can mentally base uncertainty criteria on a type of user, such as a large corporation vs. a university user)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 8
Step 2A, Prong 1
Claim 8 recites a non-transitory processor-readable storage medium that corresponds to the method of claim 1, and therefore the analysis under Step 2A, Prong 1 with respect to claim 1 also applies to this claim 8. While claim 8 recites additional generic computing components (“non-transitory processor-readable storage medium”, “processing device”, “program code”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2A, Prong 1.
Step 2A, Prong 2
Claim 8 recites a non-transitory processor-readable storage medium that corresponds to the method of claim 1, and therefore the analysis under Step 2A, Prong 2 with respect to claim 1 also applies to this claim 8. While claim 8 recites additional generic computing components (“non-transitory processor-readable storage medium”, “processing device”, “program code”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2A, Prong 2.
Step 2B
Claim 8 recites a non-transitory processor-readable storage medium that corresponds to the method of claim 1, and therefore the analysis under Step 2B with respect to claim 1 also applies to this claim 8. While claim 8 recites additional generic computing components (“non-transitory processor-readable storage medium”, “processing device”, “program code”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2B.
Claims 10-14 depend from claim 8 and correspond to the methods of claims 3-7, respectively, and are therefore rejected for the same reasons above with respect to claim 8 and claims 3-7, respectively.
Regarding Claim 15
Step 2A, Prong 1
Claim 15 recites an apparatus that corresponds to the method of claim 1, and therefore the analysis under Step 2A, Prong 1 with respect to claim 1 also applies to this claim 15. While claim 15 recites additional generic computing components (“processing device”, “processor”, “memory”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2A, Prong 1.
Step 2A, Prong 2
Claim 15 recites an apparatus that corresponds to the method of claim 1, and therefore the analysis under Step 2A, Prong 2 with respect to claim 1 also applies to this claim 15. While claim 15 recites additional generic computing components (“processing device”, “processor”, “memory”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2A, Prong 2.
Step 2B
Claim 15 recites an apparatus that corresponds to the method of claim 1, and therefore the analysis under Step 2B with respect to claim 1 also applies to this claim 15. While claim 15 recites additional generic computing components (“processing device”, “processor”, “memory”, and “machine learning-based process”), such additional generic computing components do not change the analysis under Step 2B.
Claims 17-20 depend from claim 15 and correspond to the methods of claims 3-6, respectively, and are therefore rejected for the same reasons above with respect to claim 15 and claims 3-6, respectively.
Regarding Claim 21
Step 2A, Prong 1
wherein adjusting the at least a portion of the one or more of the hardware components and the software components comprises modifying at least one of: (i) a type, (ii) a number, and (iii) a size of the one or more of the hardware components and the software components. (under the broadest reasonable interpretation, a human such as a salesperson can mentally adjust the configurations of the type, number, and or size of hardware and/or software components used to fulfill the request, such as by modifying the types of servers (e.g., Dell vs. HP), the number of servers (e.g., 2 vs. 3), the size of storage (e.g., 1 TB vs. 2 TB), without actually adjusting or making any improvements to the hardware and software components themselves; in other words, there is a mental decision about whether to utilize more/less hardware and software components, without any actual changes or improvements to the hardware and software components themselves)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Claim 22 depends from claim 8 and claims a non-transitory processor-readable storage medium that corresponds to claim 21, and is therefore rejected for the same reasons explained with respect to claims 8 and 21.
Claim 23 depends from claim 15 and claims an apparatus that corresponds to claim 21, and is therefore rejected for the same reasons explained with respect to claims 15 and 21.
Allowable Subject Matter
Claims 1, 3-8, 10-15, and 17-23 would be allowed over the prior art, provided that the rejections under 35 U.S.C. 101 are overcome.
The following is an examiner’s statement of reasons for allowance:
Independent claims 1, 8, and 15 would be considered allowable, provided that the rejections under 35 U.S.C. 101 are overcome, because none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in the independent claims, including at least:
(ii) one or more uncertainty criteria comprising one or more uncertainty thresholds corresponding to the second parameter
initiating one or more automated actions in response to at least one of the one or more uncertainty thresholds of the selected configuration being satisfied during the corresponding time interval, wherein the one or more automated actions comprise generating one or more updated configurations for a remaining portion of the particular period of time and adjusting at least a portion of the one or more of the hardware components and the software components associated with the request
The closest prior art of record discloses:
US 20140278807 A1, hereinafter referenced as BOHACEK, discloses a Cloudamize dashboard for enabling users to customize cloud configurations. (para. 0062). Pricing varies according to demand and other factors. (paras. 0003, 0043). An administrative server can predict the performance and cost of cloud services in the future. (para. 0051).
US 20170213266 A1, hereinafter referenced as BALESTRIERI, discloses generating price quotes for a particular period of time. (para. 0039).
Baldominos Gómez, Alejandro, et al. "AWS PredSpot: Machine learning for predicting the price of spot instances in AWS cloud." (2022), hereinafter referenced as BALDOMINOS, discloses using machine learning models to predict spot prices for Amazon EC2 prices. (p. 65, section I, p. 68, section IV.B.2, and p. 69, section VI).
US 20190243547 A1, hereinafter referenced as DUGGAL, discloses “When, for example, the price to rent a node falls below a user-configured threshold price, the system may initiate replication. Instead or additionally, when, for example, the price to rent a node is above a user-configured threshold price, the system may halt or pause replication even if a replication job is not complete. In this case, the replication job may resume after the price falls below the threshold price.” (para. 0110).
US 20150156266 A1, hereinafter referenced as GUPTA, discloses cost-based thresholds for clouds services. (para. 0094).
However, the examiner has found that the distinct feature of the Applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in independent claims 1, 8, and 15. In particular, one of ordinary skill in the art would not have been motivated to modify the prior art of record to utilize “one or more uncertainty thresholds” and trigger certain automated actions based on the “uncertainty thresholds’ being satisfied, without the hindsight aid of Applicant’s disclosure. Therefore, because the prior art of record does not anticipate nor make obvious claims 1, 8, and 15, those claims would be allowed if the rejections under 35 U.S.C. 101 are overcome.
Dependent claims 3-7, 10-14, and 17-23 would each be allowed over the prior art for depending from an allowed independent base claim, provided that the rejections under 35 U.S.C. 101 are overcome.
Conclusion
THIS ACTION IS MADE FINAL. 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 MICHAEL C LEE whose telephone number is (571)272-4933. The examiner can normally be reached M-F 12:00 pm - 8:00 pm ET.
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, Omar Fernandez Rivas can be reached at 571-272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL C. LEE/Examiner, Art Unit 2128
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