DETAILED ACTION
The following is a Non-Final Office action in response to communications received 1/2/26. Claim(s) 5, 6, 13, 14, and 18 has(have) been canceled. Claim(s) 1, 9, and 17 has(have) been amended. Therefore, claim(s) 1-4, 7-12, 15-17, 19, and 20 is(are) pending and addressed below.
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 therefor, subject to the conditions and requirements of this title.
Claims 1-4, 7-12, 15-17, 19, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim(s) 1, 9, and 17 is(are) rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the limitation(s) of “parsing the user inquiry to identify an issue category”, “retrieving, from a troubleshooting database, a troubleshooting guide that: relates to the issue category”, “using the AI engine to associate each of the plurality of steps with one or more characteristics”, “using the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present”, “retrieving user data associated with the characteristics from a user database and/or user device”, “determining, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data”, “parsing the user data”, “verifying whether one or more parameters of the one or more characteristics are present in the user data”, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data”, and “determining a resolution to the issue based on the execution of the non-skipped consecutive steps” in claim 1,
“parses the user inquiry to identify an issue category”, “retrieves, from a troubleshooting database, a troubleshooting guide that: relates to the issue category”, “uses the AI engine to associate each of the plurality of steps with one or more characteristics”, “uses the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present”, “retrieves user data associated with the characteristics from a user database and/or user device”, “determines, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data”, “parsing the user data”, “verifying whether one or more parameters of the one or more characteristics are present in the user data”, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data”, and “determines a resolution to the issue based on the execution of the non-skipped consecutive steps” in claim 9, and
“parsing the user inquiry to identify an issue category”, “retrieving, from a troubleshooting database, a troubleshooting guide that: relates to the issue category”, “using the AI engine to associate each of the plurality of steps with one or more characteristics”, “using the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present”, “retrieving user data associated with the characteristics from a user database and/or user device”, “determining, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data”, “parsing the user data”, “verifying whether one or more parameters of the one or more characteristics are present in the user data”, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data”, “determining a resolution to the issue based on the execution of the non-skipped consecutive steps”, and “the parameter related information is used to verify the presence of the one or more characteristics associated with the step in which the prompt was executed” in claim 17. This/These limitation(s), as drafted, is(are) a process (processes) that, under its (their) broadest reasonable interpretation, cover(s) performance of the limitation(s) in the mind but for the recitation of generic computer components. That is, other than reciting “a processor” and “a non-transitory computer-readable medium” in claim 9, nothing in the claim elements precludes the steps from practically being performed in the mind. The mere nominal recitation of generic processing components does not take the claim limitation(s) out of the mental processes grouping.
The examiner notes that “parsing the user inquiry to identify an issue category” involves subjective choices as to the method and criteria used for parsing and the criteria and factors used to identify an issue “category” and includes the mental concepts of observation, evaluation, judgment, and opinion, “retrieving, from a troubleshooting database, a troubleshooting guide that: relates to the issue category” involves subjective choices as to what is retrieved, the determination of whether something “relates” to the subjectively determined “category” and includes the mental concepts of evaluation, judgment, and opinion, “using the AI engine to associate each of the plurality of steps with one or more characteristics” involves subjective choices as to the criteria and factors used in deciding which of the plurality of steps are to be associated with one or more characteristics and how many characteristics to associate and includes the mental concepts of evaluation, judgment, and opinion, “using the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present” involves subjective choices as to the criteria and factors used in deciding which characteristic is to be associated with one or more parameters and how many parameters to associate and includes the mental concepts of evaluation, judgment, and opinion, “retrieving user data associated with the characteristics from a user database and/or user device” involves a subjective evaluation of which user data is “associated” with the “characteristics” and includes the mental concepts of observation, evaluation, judgment, and opinion, “determining, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data” involves subjective choices as which steps to skip based on a set of subjective criteria and factors and includes the mental concepts of judgment and opinion, “parsing the user data” involves subjective choices as to the method and criteria used to parse the user data and includes the mental concepts of observation, evaluation, judgment, and opinion, “verifying whether one or more parameters of the one or more characteristics are present in the user data” involves evaluating the parameters of the characteristics by subjectively comparing them to a set of criteria and judging whether they match the criteria for verification and includes the mental concepts of evaluation and judgment, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data” involves subjective choices as to which steps to skip and the criteria and factors used to make the determination and includes the mental concepts of evaluation, judgment, and opinion, and “determining a resolution to the issue based on the execution of the non-skipped consecutive steps” involves subjective criteria and methods used to determine a resolution based on non-skipped steps and includes the mental concepts of observation, evaluation, judgment, and opinion in claim 1,
“parses the user inquiry to identify an issue category” involves subjective choices as to the method and criteria used for parsing and the criteria and factors used to identify an issue “category” and includes the mental concepts of observation, evaluation, judgment, and opinion, “retrieves, from a troubleshooting database, a troubleshooting guide that: relates to the issue category” involves subjective choices as to what is retrieved, the determination of whether something “relates” to the subjectively determined “category” and includes the mental concepts of evaluation, judgment, and opinion, “uses the AI engine to associate each of the plurality of steps with one or more characteristics” involves subjective choices as to the criteria and factors used in deciding which of the plurality of steps are to be associated with one or more characteristics and how many characteristics to associate and includes the mental concepts of evaluation, judgment, and opinion, “uses the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present” involves subjective choices as to the criteria and factors used in deciding which characteristic is to be associated with one or more parameters and how many parameters to associate and includes the mental concepts of evaluation, judgment, and opinion, “retrieves user data associated with the characteristics from a user database and/or user device” involves a subjective evaluation of which user data is “associated” with the “characteristics” and includes the mental concepts of observation, evaluation, judgment, and opinion, “determines, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data” involves subjective choices as which steps to skip based on a set of subjective criteria and factors and includes the mental concepts of judgment and opinion, “parsing the user data” involves subjective choices as to the method and criteria used to parse the user data and includes the mental concepts of observation, evaluation, judgment, and opinion, “verifying whether one or more parameters of the one or more characteristics are present in the user data” involves evaluating the parameters of the characteristics by subjectively comparing them to a set of criteria and judging whether they match the criteria for verification and includes the mental concepts of evaluation and judgment, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data” involves subjective choices as to which steps to skip and the criteria and factors used to make the determination and includes the mental concepts of evaluation, judgment, and opinion, and “determines a resolution to the issue based on the execution of the non-skipped consecutive steps” involves subjective criteria and methods used to determine a resolution based on non-skipped steps and includes the mental concepts of observation, evaluation, judgment, and opinion in claim 9, and
“parsing the user inquiry to identify an issue category” involves subjective choices as to the method and criteria used for parsing and the criteria and factors used to identify an issue “category” and includes the mental concepts of observation, evaluation, judgment, and opinion, “retrieving, from a troubleshooting database, a troubleshooting guide that: relates to the issue category” involves subjective choices as to what is retrieved, the determination of whether something “relates” to the subjectively determined “category” and includes the mental concepts of evaluation, judgment, and opinion, “using the AI engine to associate each of the plurality of steps with one or more characteristics” involves subjective choices as to the criteria and factors used in deciding which of the plurality of steps are to be associated with one or more characteristics and how many characteristics to associate and includes the mental concepts of evaluation, judgment, and opinion, “using the AI engine to associate each characteristic with one or more parameters, the presence of the one or more parameters indicating the characteristic is present” involves subjective choices as to the criteria and factors used in deciding which characteristic is to be associated with one or more parameters and how many parameters to associate and includes the mental concepts of evaluation, judgment, and opinion, “retrieving user data associated with the characteristics from a user database and/or user device” involves a subjective evaluation of which user data is “associated” with the “characteristics” and includes the mental concepts of observation, evaluation, judgment, and opinion, “determining, by the AI engine before execution of the plurality of steps, one or more of the plurality of consecutive steps to skip based on the retrieved user data” involves subjective choices as which steps to skip based on a set of subjective criteria and factors and includes the mental concepts of judgment and opinion, “parsing the user data” involves subjective choices as to the method and criteria used to parse the user data and includes the mental concepts of observation, evaluation, judgment, and opinion, “verifying whether one or more parameters of the one or more characteristics are present in the user data” involves evaluating the parameters of the characteristics by subjectively comparing them to a set of criteria and judging whether they match the criteria for verification and includes the mental concepts of evaluation and judgment, “skipping each step of the plurality of consecutive steps associated with the characteristic whose associated parameters were verified to be present in the parsed user data” involves subjective choices as to which steps to skip and the criteria and factors used to make the determination and includes the mental concepts of evaluation, judgment, and opinion, and “determining a resolution to the issue based on the execution of the non-skipped consecutive steps” involves subjective criteria and methods used to determine a resolution based on non-skipped steps and includes the mental concepts of observation, evaluation, judgment, and opinion, and “the parameter related information is used to verify the presence of the one or more characteristics associated with the step in which the prompt was executed” involves subjective choices in determining a correspondence of the parameter used to verify the presence of characteristics by subjectively comparing them to a set of criteria and judging whether they match the criteria for verification and includes the mental concepts of evaluation, judgment, and opinion in claim 17. Thus, the claim(s) recite(s) a mental process, concepts that may be performed in the human mind, in this case being observation, evaluation, judgment, and opinion.
This judicial exception is not integrated into a practical application because the additional elements recited are recited at a high level of generality, i.e., as generic processor performing generic computer functions. These generic processor limitations are no more than mere instructions to apply the exception using a generic computer component. The examiner notes that while “determining a resolution to the issue” could possibly improve the functioning of a computer, it does not perform, execute, or implement the resolution. It only determines it, and even if the resolution were performed or executed to resolve the issue, it is not a particular solution to a specific problem (An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome, see MPEP 2106.05(a), The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it", see MPEP 2106.05(f)), but instead a generic solution to any general problem. In this case the generic and all encompassing “issue” and “resolution” can represent any issue, problem, or error and a simply “applying” of a generic “resolution” to any possible issue. 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. Therefore, the additional elements fail to improve the functionality of the computer itself.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology or effects a transformation or reduction of a particular article to a different state or thing. Their collective functions merely provide conventional computer implementation. Furthermore, the applicant’s own specification details the generic nature of the computing components, which also precludes them from presenting anything significantly more ([0039-0060], fig. 1, 2).
Claim(s) 2-4, 7, 8, 10-12, 15, 16, 19, and 20 do(es) not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Claims 2 and 10 involve a mental process of a user observing the outcome of the non-skipped step, evaluating it’s effectiveness, and using judgment and opinion to determine if it was effective and to what degree it was effective and do(es) not provide a practical application and also do(es) not provide significantly more in that the computer system is not improved or even affected.
Claims 3 and 11 simply use the user response to train the AI engine and do(es) not provide a practical application and also do(es) not provide significantly more in that the computer system is not improved or even affected.
Claims 4 and 12 involve a mental process in the verification of the presence of an intervening characteristic and the correspondence between them and do(es) not provide a practical application and also do(es) not provide significantly more in that the computer system is not improved or even affected.
Claims 7, 15, and 19 involve mental processes in analyzing, associating, analyzing, associating, and validating given the subjective choices involves in each and do(es) not provide a practical application and also do(es) not provide significantly more in that the computer system is not improved or even affected.
Claims 8, 16, and 20 involve a mental process in the determination of what comprises a “correct” match and do(es) not provide a practical application and also do(es) not provide significantly more in that the computer system is not improved or even affected.
Claims 1-4, 7-12, 15-17, 19, and 20 is(are) therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Response to Arguments
Applicant's arguments filed 1/2/26 have been fully considered but they are not persuasive.
In response to applicant’s argument (see p. 12 of remarks) that the claims “provide an improvement to an automated user troubleshooting system” and “that the systems and methods provide an improvement to a computer system”, the examiner respectfully disagrees.
The examiner notes that performing the steps of the independent claims would determine a resolution, but the computer would not be improved afterwards given that the resolution is not implemented and as such would be in the same state as before the steps of the claims were performed. Additionally, the examiner notes that while “determining a resolution to the issue” could possibly improve the functioning of a computer, it does not perform, execute, or implement the resolution. It only determines it, and even if the resolution were performed or executed to resolve the issue, it is not a particular solution to a specific problem (An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome, see MPEP 2106.05(a), The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it", see MPEP 2106.05(f)), but instead a generic solution to any general problem. In this case the generic and all encompassing “issue” and “resolution” can represent any issue, problem, or error and a simply “applying” of a generic “resolution” to any possible issue. 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. Therefore, the additional elements fail to improve the functionality of the computer itself.
In response to applicant’s argument (see p. 12 of remarks) that the claims “cannot merely be performed in the mind”, the examiner respectfully disagrees.
The examiner notes that “claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations” and “claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions” (MPEP 2106.04(a)(2)(III)(A)).
The examiner notes that one limitation comprising a mental process indicates the claim recites a mental process. The additional elements are then evaluated to determine if they provide a practical application of the exception or significantly more than the exception. In this case the claims recite multiple limitations comprising mental processes (as listed in the rejection above). The examiner also notes that the training of the model is not indicated as comprising a mental process.
Conclusion
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/JOSHUA P LOTTICH/ Primary Examiner, Art Unit 2113