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 .
Receipt of Applicant’s Amendment filed April 24, 2026, is acknowledged.
Response to Amendment
Claims 1 and 14 have been amended. Claims 12 and 13 have been canceled. Claims 1-11 and 14-22 are pending and are provided to be examined upon their merits.
Response to Arguments
Applicant's arguments filed April 24, 2026, have been fully considered but they are not persuasive. A response is provided below in bold where appropriate.
Applicant argues 35 USC §101 Rejection, starting pg. 9 of Remarks:
Rejection under 35 U.S.C. 4 101
Claims 1-11 and 14-22 stand rejected under 35 U.S.C. § 101 as being directed to a judicial exception (i.e., an abstract idea) without reciting significantly more.
This rejection is respectfully traversed.
A complete discussion of the Examiner's rejection is set forth in the Office Action, and is not being repeated here.
Without admitting the Office Action's arguments as being correct, applicant has amended claim 1 to recite "the processing unit is further configured to: identify a plurality of second know- how information having a relationship with the first know-how information; dynamically determine a number of inputs and a number of outputs of the learned model based on a number of the identified plurality of second know-how information; and execute a compound process by inputting data into the learned model having the determined number of inputs and the determined number of outputs."
From amended Claim 14:
“identifying a plurality of second know-how information having a relationship with the first know-how information;
dynamically determining a number of inputs and a number of outputs of the learned model based on a number of the identified plurality of know-how information; and
executing a compound process by inputting data into the learned model having the determined number of inputs and the determined number of outputs.”
Respectfully, “dynamically determining a number of inputs and a number of outputs of the learned model” cannot be found in the written description.
These amendments cause claim 1 to be directed to a technical solution to a technological problem. The Examiner alleges that the features of claim 1 could be performed by a mental process. A human being cannot dynamically reconfigure their own neural biological pathways or mental inputs/outputs to perform simultaneous mathematical correlation analysis across multiple data streams in real-time. The amended features of claim 1 are, therefore, not directed to a mental process, but a technological solution.
Applicant’s argument above is not commensurate with the scope of the claims. The claims require dynamically determining a number of inputs and outputs based on identified know-how information. This is used as input into a learned model. A person in their mind or with pen and paper can determine a number of inputs/outputs to use for a learned model. The learned model itself does nothing, just receive inputs.
The Federal circuit in Koninklijke KPNNV v. Gemalto M2M GmbH, 942 F.3d 1143 (Fed. Cir. 2019) ruled that claims directed to "specific implementation of varying the way check data is generated that improves the ability of prior art error detection systems to detect systematic errors” and are patent eligible. In the same way that the claims at issue in Koninklijke KPN NV include varying methodology for improved results, the claims at issue in this application include varying the number of inputs and outputs by reciting "dynamically determine a number of inputs and a number of outputs of the learned model based on a number of the identified plurality of second know-how information; and execute a compound process by inputting data into the learned model having the determined number of inputs and the determined number of outputs." As described in paragraph [0251] of the application as filed, the "compound process" utilizing the relationship between multiple know-how sets improves the accuracy of processing. This is not a "high-level" recitation of AI; rather, it is a specific implementation where the model's topology (inputs/outputs) is dictated by the specific data relationships identified by the system.
From Applicant’s published specification (2023/0410988)
“For example, the processing unit 110 accepts the sensor information from the Device_p and the sensor information from the Device_q as inputs, and may determine whether “if_p” is satisfied and whether “if_q” is satisfied on the basis of both inputs. For example, the machine learning of the NN with two inputs and two outputs is performed using both the sample data and correct answer data collected for the P th know-how information and the sample data and correct answer data collected for the Q th know-how information. However, the second processing algorithm can be modified in various ways as described above.” [0250]
“In this way, the starting condition and assistance action can be determined after considering the relationship between the know-how information 121, thereby improving the accuracy of processing. Although an example of combining 2 pieces of the know-how information 121 has been described here, complex processing may be performed for 3 or more pieces of the know-how information 121.” [0251]
Respectfully, if the above is using correct information to improve the accuracy of a machine learning model, that is not improving machine learning technology. For example, using ground truth information is part of training a model to improve its accuracy. Further, there is no teaching in Applicant’s specification of an improvement to machine learning.
For the above reasons, claim 1 is directed to a technological solution to a technological problem and an improvement in the functioning of a computer. Claim 1 is directed to patent eligible subject matter under step 2A prong one of the Alice/Mayo test.
Alternatively, claim 1 is directed to significantly more than the alleged abstract idea. As mentioned above, the amended features of claim 1 cannot be performed by a mental process. Further, the amended features of claim 1 include limitations directly linking the claims to the technological field of learned models. The features of claim 1 represent an unconventional and non-generic computer configuration. There is no evidence in the prior art that such dynamic model scaling based on "know-how relationships" was routine or conventional. Thus, claim 1 is directed to significantly more than the alleged abstract idea and is directed to patent eligible subject matter under step 2B of the Alice/Mayo test.
Prior art evidence is a novelty consideration under 35 USC 102/103, not a statutory consideration for patent eligibility under 35 USC 101.
Claim 14 has been amended similarly to claim 1 and is similarly directed to a patent eligible technological solution to a technological problem under step 2A prong one of the Alice/Mayo test, or alternatively, significantly more than the alleged abstract idea under step 2B of the Alice/Mayo test.
Claims 1 and 14 and their dependent claims are directed to patent eligible subject matter. Reconsideration and withdrawal of this rejection are respectfully requested.
The rejection is respectfully maintained but modified for the claim amendments.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 and 14-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-11 and 14-22 are directed to a system or method, which are statutory categories of invention. (Step 1: YES).
The Examiner has identified method Claim 14 as the claim that represents the claimed invention for analysis and is similar to system Claim 1.
Claim 14 recites the limitations of:
An information processing method comprising:
receiving, by an information processing device, a registration request of a know-how information including information which associates condition information representing a starting condition and assistance information representing an assistance action to be performed if the starting condition is satisfied; and
outputting to a display the know-how information stored based on the registration requests as a search result based on a search request received from a user of an information processing device, the search request including information to identify either one of the starting condition and the assistance actions, wherein
the plurality of the know-how information includes a first know-how information including information which associates first condition information representing a first starting condition and first assistance information representing a first assistance action to be performed in response to the first starting condition being satisfied, and
the method further comprising determining whether the first condition is satisfied by inputting data from acquiring devices into a learned model, and
the method further comprising identifying a type of acquiring device required to determine the first condition from a text content of the first condition,
the method further comprises:
identifying a plurality of second know-how information having a relationship with the first know-how information;
dynamically determining a number of inputs and a number of outputs of the learned model based on a number of the identified plurality of know-how information; and
executing a compound process by inputting data into the learned model having the determined number of inputs and the determined number of outputs.
These above limitations, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. The claim recites elements, in non-bold above, which covers performance of the limitation as managing personal behavior (e.g., an assistance action to be performed if a starting condition is satisfied) and interactions between people including teaching and following rules or instructions (e.g., outputting know-how information to identifying starting condition and assistance actions, identifying a type of acquiring device required to determine the first condition). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as managing personal behavior or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Claim 1 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
The claims are also abstract under Mental Processes grouping of abstract ideas. Receiving a request of information and outputting know-how information stored as a result of a search result could be performed in the mind of a person or with pen and paper (e.g., a person can receive a request for information and provide know-how information, see for example para. [0103] and [0124] where knowledge is being provided to less-skilled workers from skilled workers.). For example, as a manual process, a person can receive a request for information that is associated with starting condition (help, I’m lost) or assistance information, output with pen and paper after searching (search filing cabinet/libraries/mind/etc.) either starting condition (yes you are lost) or assistance actions, where the information includes assistance action (you are lost in a room of your house, go left and outside), and determine if the condition is satisfied by a person inputting (typing in information) data acquired from outside sources into a learned model, where the learned model as claimed could be a person (learning does not require a machine). A person can identify (in their mind) a type of acquiring device (camera) required to determine a first condition based on text content of a first condition (someone texts help I’m falling). A person can read and interpret in their mind a “text content” that identifies a type of acquiring device (e.g. camera) required for a first condition (face wobbles). A person can have a learning model (read instructions) to determine if a condition is satisfied and to take two inputs and outputs and determine a determine a starting condition and assistance action using a relationship (a person can perform with pen and paper conditional logic). A person in their mind or with pen and paper can identify second know-how information related to first know-how information and execute a compound process (e.g. if bleeding, go to bathroom for band-aide, if bleeding not stopped, call family member). Further, using a processing device to perform a judicial exception has been shown not to be enough to make abstract claims statutory (see MPEP 2106.04(a)(2) III C), and it is not even required in Claim 14.
This judicial exception is not integrated into a practical application. In particular, the claims only recite: processing unit, storage unit, display, outside devices (Claim 1); processing device, display, outside devices (Claim 14). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The storage unit and display are computer components. The learned model is recited at a high level of generality, there is no improvement to the learned model itself, and there is no machine learning so a person can learn (use a “learn model”) and perform the steps. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1 and 14 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Applicant’s specification para’s. [0021] and [0032] about using various computing devices and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Steps such as receiving, storing, and transmitting are steps that are considered insignificant extra solution activity and mere instructions to apply the exception using general computer components (see MPEP 2106.05(d), II). Thus claims 1 and 14 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 2-11 and 15-22 further define the abstract idea that is present in their respective independent claims 1 and 14 and thus correspond to Certain Methods of Organizing Human Activity and Mental Processes and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Claims 5-8, 13, and 17-20 determine similarity, which is abstract under Mathematical Concepts grouping of abstract ideas as this requires calculating an algorithm. Claims 2, 3, 12, 13 further recite device at a high level of generality and the device appears to be a generic device performing judicial exceptions. Claims 21 recites neural network and claim 23 recites outside devices. which are generic devices and applied at a high level of generality. Therefore, the claims 2-11 and 15-22 are directed to an abstract idea. Thus, the claims 1-11 and 14-22 are not patent-eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-11 and 14-22 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 14 recites “dynamically determining a number of inputs and a number of outputs of the learned model based on a number of the identified plurality of know-how information; and
executing a compound process by inputting data into the learned model having the determined number of inputs and the determined number of outputs” where dynamically determining number of inputs and a number of outputs of the learne model based on a number of identified know-how information cannot be found in the written disclosure.
The specification teaches (from Applicant’s Pub. No. 2023/0410988):
“However, the processing of this embodiment is not limited to this. For example, if the P th know-how information is similar to the Q th know-how information, “if_p” and “then_q” may have some relevance. Similarly, “if_q” and “then_p” may have some relevance. Therefore, rather than processing these independently, compound processing may be performed.” [0249]
“For example, the processing unit 110 accepts the sensor information from the Device_p and the sensor information from the Device_q as inputs, and may determine whether “if_p” is satisfied and whether “if_q” is satisfied on the basis of both inputs. For example, the machine learning of the NN with two inputs and two outputs is performed using both the sample data and correct answer data collected for the P th know-how information and the sample data and correct answer data collected for the Q th know-how information. However, the second processing algorithm can be modified in various ways as described above.” [0250]
Therefore, a machine learning model can receive two inputs, but there is no teaching of dynamically determining a number of input and outputs based on a number of know-how information. Claim 1 has a similar problem.
Claims 2-11, and 15-22 are further rejected as they depend from their respective independent claims 1 and 14.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for amendments to claims should Applicant amend. The purpose of this is to reduce potential 35 U.S.C. §112(a) or §112 1st paragraph issues that can arise when claims are amended without support in the specification. The Examiner thanks the Applicant in advance.
Prior Art
A prior art search update was conducted but does not result in a prior art rejection at this time. The best prior art found to date is Pub. No. US 2011/0276396 to Rathod. Rathod teaches providing resources but does not teach the combination of claimed elements such as identifying a type of acquiring device required to determine a first condition from a text content of the first condition. See also PCT/JP2021/024602 written opinion pg. 4 regarding prior art.
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 KENNETH BARTLEY whose telephone number is (571)272-5230. The examiner can normally be reached Mon-Fri: 7:30 - 4:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SHAHID MERCHANT can be reached at (571) 270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KENNETH BARTLEY/Primary Examiner, Art Unit 3684
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