Detailed Action:
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 therefore, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-20 are directed to a judicial exception (i.e., a law of nature, natural phenomenon, or abstract idea) without significant more. Claims 1-20 are directed to the abstract idea of computer aided mental process.
Part I. 2A-prong one (Identify the Abstract Ideas)
The Alice framework, step 2A-Prong One (part 1 of Mayo test), here, the claims are analyzed to determine if the claims are directed to a judicial exception. MPEP §2106.04(a). In determining whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception (Prong One of Step 2A), and whether the claims recite additional elements that integrate the judicial exception into a practical application (Prong Two of Step 2A). See 2019 Revised Patent Subject Matter Eligibility Guidance (“PEG” 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (Jan. 7, 2019)).
Independent claims 1, 12, and 16 when “taken as a whole,” are directed to the abstract idea of a computer aided mental process.
Under step 2A-Prong One (part 1 of Mayo test), here, the claimed invention in claims 1, 16, and 12 are directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The above claim falls within a computer aided mental process, and thus, the claims are directed to an abstract idea under the first prong of Step 2A.)
Part II. 2A-prong two (additional elements that integrate the judicial exception into a practical application)
Under step 2A-Prong two (part 1 of Mayo test), this judicial exception is not integrated into a practical application under the second prong of Step 2A. In particular, the claims recite the additional elements beyond the recited abstract idea. Such as, “…a computer-readable media…user interface…memory…machine learning algorithm…artificial intelligence application…”
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) as well-understood, routine, conventional. (MPEP 2106.05(d))
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. The claims are directed at an abstract idea without any significant more elements.
As a result, Examiner asserts that claims 2-11, 13-15, and 17-20 are similarly directed to the abstract idea. Since these claims are directed to an abstract idea, the Office must determine whether the remaining limitations “do significantly more” than describe the abstract idea.
Part III. Determine whether any Element, or Combination, Amounts to“Significantly More” than the Abstract Idea itself
The Alice framework, we turn to step 2B (Part 2 of Mayo) to determine if the claim is sufficient to ensure that the claim amounts to “significantly more" than the abstract idea itself. These additional elements recite conventional computer components and conventional functions of:
Claims 1-20 do not include any limitations, amounting to significantly more than the abstract idea, alone.
Claims 1, 12, and 16 do include various elements that are not directed to the abstract idea. These elements include, “…a computer-readable media…user interface…memory…processor…machine learning algorithm…artificial intelligence application…”
These amounts to generic computing elements performing generic computing functions and a high level of generality.
In addition, Fig.1 of the Applicant’s specifications details any combination of a generic computer system program to perform the system. Generically recited computer elements do not add a meaningful limitation to the abstract idea because the Alice decision noted that generic structures that merely apply abstract ideas are not significantly more than the abstract ideas.
The dependent claims further limit the abstract idea without adding significantly more. Accordingly, the Examiner concludes that there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claim amounts to significantly more than the judicial exception itself.
Further, Examiner notes that the additional limitations, when considered as an ordered combination, add nothing that is not already present when looking at the additional elements individually.
Claims 2-11, 13-15, and 17-20 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to independent claims 1, 12, and 16.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Specifically, the following claims/limitations are indefinite:
estimating, with an artificial intelligence process, a current status of the process, producing a current status estimate, wherein the estimating comprises estimating the status of the machine learning algorithm.
The Examiner is unable to adequately interpret the above limitation, because it simply does not make sense to the Examiner. To be exact, the function doesn't make sense, because the claim limitation is using the very estimating and the verb producing it in the same limitation. Clarification is required. For purposes of examination, the Examiner will interpret the limitation to mean estimating a current status of the process in association with the machine learning algorithm.
predicting, with the artificial intelligence process, the current status of the process when there is no actual knowledge of the process due to operation of the machine learning algorithm
The Examiner is unable to adequately interpret the above limitation, because it also does not make sense to the Examiner. How can something predict something with no actual knowledge of it? Clarification is required. For purposes of examination, the Examiner will interpret the limitation to mean predicting the status of the process in association with the machine learning algorithm.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability should not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Boileau et al. (US Pub. No. 2018/0053127) (Hereinafter, Boileau) in view of Boulineau et al. (US Pub. No. 2008/0313595) (Hereinafter, Boulineau).
As per claim 1,
Boileau teaches,
A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:
(Abstract)
providing a graphical user interface on a display device for interaction with a first user associated with a process to be performed.
(Paragraph 10, noting “…. there is provided a method of presenting to a user a graphical user interface (GUI) relating to visualizing tasks relating to a project the user is associated with…”)
receiving, from the first user, information defining one or more tasks, the one or more tasks to perform the process.
(paragraph 10, noting “…, the data relating to each task comprising at least an identity of the task, a resource associated with the task, and timing information relating to the task…”)
Boileau does not explicitly teach, however, Boulineau does teach,
receiving, from a second user associated with respective tasks of the one or more tasks, respective rulesets associated with the respective tasks, each respective ruleset defining procedures to complete a respective task, one or more of the respective rulesets implementing a machine learning algorithm to complete the respective task.
(paragraphs 85-87, discussing rules and parameters with paragraph 184 discussing ML and AI)
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to incorporate the teachings of Boulineau within the invention of Boileau with the motivation of generating a tool that can quickly perform within the boundaries of rules/parameters the process.
Boileau teaches,
displaying information about one or more tasks on the graphical user interface during performance of the process.
(paragraph 75, noting “…For example, as a user moves a task from “In Progress” to “Done” NEWTOOL has this task linked to subsequent tasks such that NEWTOOL automatically moves another task from “Planned” to “To Do” or “In Progress” for example and may also bring other tasks on subsequent linked stages from hidden or out of sight to the user on this current time base to the “Planned” or “To Do” columns for example…”)
estimating, with an artificial intelligence process, a current status of the process, producing a current status estimate, wherein the estimating comprises estimating the status of the machine learning algorithm.
(Examiner Noting: This section of the claim is further rejected based on 112b, see above for further detail and clarification; Examiner further noting: the limitation is for current examination purposes interpreted to be the estimation and production of the current status of the business process with machine learning algorithm. This is similar to claims 12 and 16 interpretation.)
(see Boileau teaching, status of business process, paragraph 75 with Boulineau teaching with the machine learning algorithm paragraph 184).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to incorporate the teachings of Boulineau within the invention of Boileau with the motivation of generating a tool that can quickly perform within the boundaries of rules/parameters the process.
Boileau teaches,
displaying process status information on the graphical user interface wherein the process status information is based on the current status estimate
(Figs. 3-5, noting element “313” and “In Progress”)
As per claim 2,
Boileau does not explicitly teach, however, Boulineau does teach,
the non-transitory machine-readable medium of claim 1, wherein the receiving information defining one or more tasks comprises:
receiving information defining task dependency.
(paragraph 45, 61, and 174 with Fig. 10)
and
in response to a user inquiry by the first user, displaying on the graphical user interface a visual indication of the task dependency
(paragraph 45, 61, and 174 with Fig. 10).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to incorporate the teachings of Boulineau within the invention of Boileau with the motivation of generating a tool that can quickly perform within the boundaries of rules/parameters the process.
As per claim 3,
Boileau teaches,
the non-transitory machine-readable medium of claim 2, wherein the operations further comprise:
displaying graphical objects on the graphical user interface, each graphical object corresponding to a task, without displaying graphical information about the respective rulesets associated with the tasks.
(Fig. 8 and corresponding text)
receiving a click actuation on the graphical user interface from the first user, the click actuation identifying a task of interest.
(Figs. 6 & 7, noting on Fig. 6 the mouse cursor elements; noting in Fig. 7 the “links” element)
and
Boileau does not explicitly teach, however, Boulineau does teach,
displaying, on the graphical user interface, interconnections between graphical objects, the interconnections indicative of the task dependency
(Fig. 1E and corresponding text)
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to incorporate the teachings of Boulineau within the invention of Boileau with the motivation of generating a tool that can quickly perform within the boundaries of rules/parameters the process.
As per claim 4,
Boileau teaches,
the non-transitory machine-readable medium of claim 1, wherein the operations further comprise:
receiving, for each respective task,
identification information for the respective tasks,
(paragraph 115)
task state information defining a state for the respective task,
(paragraphs 114 & 115)
information defining task dependencies for the respective task
(paragraph 45)
arranging the information about the one or more tasks on the graphical user interface according to the task state information so that tasks having a common state are displayed on the graphical user interface together
(Figs. 3-5 and corresponding text).
As per claim 5,
Boileau teaches,
the non-transitory machine-readable medium of claim 4, wherein the operations further comprise:
receiving from a particular ruleset an indication that task state information for a particular task has changed, wherein the particular ruleset is uniquely associated with the particular task.
(paragraph 75)
generating new task information based on the indication.
(paragraph 75)
updating the state information responsive to the new task information for the particular task; and
updating the graphical user interface based on updated state information
(paragraph 75).
As per claim 6,
Boileau teaches,
the non-transitory machine-readable medium of claim 1, wherein the operations further comprise:
prompting, via the graphical user interface, the first user to specify dependencies among various tasks of the one or more tasks by dragging-and-dropping display items
(paragraph 72).
As per claim 7, Examiner Noting: 112b Rejection
Boileau teaches,
the non-transitory machine-readable medium of claim 1, wherein the operations further comprise:
predicting, with the artificial intelligence process, the current status of the process when there is no actual knowledge of the process due to operation of the machine learning algorithm
(see Boileau teaching, status of business process, paragraph 75 with Boulineau teaching with the machine learning algorithm paragraph 184).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to incorporate the teachings of Boulineau within the invention of Boileau with the motivation of generating a tool that can quickly perform within the boundaries of rules/parameters the process.
As per claim 8,
Boileau teaches,
the non-transitory machine-readable medium of claim 7, wherein the operations further comprise:
training the artificial intelligence process on inputs and output of the machine learning algorithm to make future predictions about operation of the machine learning algorithm
(paragraph 74).
As per claim 9,
Boileau teaches,
the non-transitory machine-readable medium of claim 1, wherein the operations further comprise:
receiving, from the artificial intelligence process, information about an error condition of a failed ruleset; and
displaying, on the graphical user interface for the first user, an indication of the error condition of the failed ruleset with a task associated with the failed ruleset of the process on the graphical user interface
(paragraph 120).
As per claim 10,
Boileau teaches,
the non-transitory machine-readable medium of claim 1, wherein the operations further comprise:
displaying the graphical user interface to enable the first user to monitor and interact visually with the one or more tasks via the graphical user interface,
(Figs. 6 & 7).
wherein the graphical user interface includes an operator selectable popup menu, wherein the operator selectable popup menu is presented to the first user to select the one or more tasks.
(paragraph 74).
As per claim 11,
Boileau teaches,
the non-transitory machine-readable medium of claim 10, wherein the operations further comprise:
prompting, via the graphical user interface, the first user to drag-and-drop to instantiate tasks for the process, wherein the graphical user interface allows the first user to specify dependencies among various tasks of the one or more tasks
(paragraphs 72, 76,89, and 97).
As per claim 12-14:
Claims 12-14 disclose similar limitations as the claims above, however, in a product form. Boileau and Boulineau disclose their inventions in such a form, see, at least claim 8. Therefore, claims 12-14 are rejected based on the same rationale as claims 1-11 above.
As per claim 15,
Boileau teaches,
the device of claim 14, wherein the operations further comprise:
receiving, from the artificial intelligence process, information about an error
condition of a failed ruleset; and
(paragraph 120)
displaying, on the graphical user interface for the first user, an indication of the
error condition of the failed ruleset with a task associated with the failed ruleset of the
process on the graphical user interface
(paragraph 120).
As per claims 16-20:
Claims 16-20 disclose similar limitations to claims 1-11 above, however, in a method form. Boileau teaches their inventio in such a form, see at least claim 1. Therefore, claims 16-20 are rejected based on similar rationale as claims 1-11 above.
Examiner Noting on claims 16-20:
The Examiner would like to note that, in particular claim 16, discloses “high level” input information for processing. The high-level information input could be managerial information/tasks as disclosed by the Applicant’s Specification paragraph 29. Boileau discloses similar semantics given to the prior art invention on paragraph 62.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZAHRA ELKASSABGI whose telephone number is (571)270-7943. The examiner can normally be reached Monday through Friday 11:30 to 8:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached at 571.272.6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ZAHRA . ELKASSABGI
Examiner
Art Unit 3623
/RUTAO WU/Supervisory Patent Examiner, Art Unit 3623
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