DETAILED ACTION
Status of the Application
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This communication is a final action in response to amendments filed on 6/24/2026. Claims 1, 3, and 6-7 are currently pending and have been considered below.
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, and 6-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1, 3, and 6-7 are determined to be directed to an abstract idea.
The claims 1, 3, and 6-7 are directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea), without providing a practical application integration and without providing significantly more.
As per Step 1 of the subject matter eligibility analysis, Claims 1, 3 and 7 are directed to and a method and a computing device (i.e., apparatus) which are within the four statutory categories of invention. Claim 6 includes signals per se, and fails Step 1 of the analysis. To remedy this deficiency, Applicants can modify the claims to amend the product as non-transitory. (MPEP 2106.03)
As per Step 2A-Prong 1 of the subject matter eligibility analysis, Claims 1, 6 and 7 are directed specifically to the abstract idea of generating an algorithm for aiding a pilot of an aircraft in a complex and dynamic environment, the environment being an environment of the aircraft, comprising: providing a knowledge base comprising a plurality of logical rules, a logical rule being a logical function associating a piece of knowledge with one or a plurality of input variables, an input variable being a physical datum, each physical datum being a quantity whose instantaneous value is measured, and the plurality of physical data allowing the environment to be described, and each piece of knowledge being an interpretive element that enables an abstract representation of the environment, and the plurality of pieces of knowledge enables a high-level, objective representation of the environment; analyzing the knowledge base in order to extract a set of knowledge and a set of physical data, the analysis of the knowledge base extracting, for each piece of knowledge in the knowledge set, a set of causes for the piece of knowledge, the set of causes consisting of the physical data that are the direct or indirect causes of the piece of knowledge; developing a[n] algorithm for each piece of knowledge of the set of knowledge and for each physical datum of the set of physical data, calculating a relevance of the piece of knowledge and each [model] for each physical datum calculating a relevance of the physical datum, the relevancies being computed from a current situation, each relevance being defined by a variable ranging from 0 to 1, with a value close to 1 indicating that the relevance is established, the current situation being defined by the current values of each physical datum of the set of physical data; training the algorithm on a learning data including situations labelled with a true relevance for each piece of knowledge and for each physical datum, by applying a constraint based on the set of causes extracted in the analysis step, in order to obtain the decision-making aid algorithm; executing the decision-making aid algorithm on a new situation, in order to calculate the relevance of each piece of knowledge and of each physical datum in relation to the new situation; and providing the pilot with a list of pieces of knowledge and/or physical data that has been filtered and/or sorted based on their respective relevancies, in order to enhance a situational awareness of the pilot when making a decision; which include mental processes (observing and evaluating data for a judgement or opinion of data relevance to aid a pilot for decision making), mathematical concepts (using logic tensor neural network algorithm to analyze data for relevance to aid a pilot for decision making), and certain methods of organizing human activity based on managing personal behavior and interactions between people (following rules and instructions to analyze datasets for data relevance to aid a pilot for decision making). Claim 3 is directed to the abstract idea of claim 1 with further details on the parameters/attributes of the abstract idea which includes mental processes and certain methods of organizing human activity for similar reasons as provided above for claim 1. After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
As per Step 2A-Prong 2 of the subject matter eligibility analysis, while the claims 1, 3, and 6-7 recite additional limitations which are hardware or software elements, such as computer, onboard or remote system, automatically (i.e., using a computer/processor), logic tensor network including neural network, learning database, computer program product comprising software instructions which, when executed by a computer, implement a decision-making aid algorithm resulting from a method, decision-making aid computing device configured for executing the decision-making aid algorithm resulting from the method, these limitations are not enough to qualify as a practical application being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do not integrate an abstract idea into a practical application (MPEP 2106.05(f)&(h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
As per Step 2B of the subject matter eligibility analysis, while the claims 1, 3, and 6-7 recite additional limitations which are hardware or software elements, such as computer, onboard or remote system, automatically (i.e., using a computer/processor), logic tensor network including neural network, learning database, computer program product comprising software instructions which, when executed by a computer, implement a decision-making aid algorithm resulting from a method, decision-making aid computing device configured for executing the decision-making aid algorithm resulting from the method, these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do provide significantly more to an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Therefore, since there are no limitations in the claims 1, 3, and 6-7 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Response to arguments
Applicant’s arguments are fully considered. Details are provided below.
Arguments on rejections under 35 USC 101:
Applicant’s arguments are geared towards newly added limitations which are considered for the first time in the rejection sections of this Office action to which the applicant may refer for further clarification.
Arguments on rejections under 35 USC 102/103:
Rejections withdrawn based on applicant’s amendments. Closest prior art to the invention includes: Marshall (US 20210304234 A1) and Hwu et al (US 20210358314 A1) as detailed in the previous rejections. None of the prior art alone or in combination teaches the claimed invention.
Conclusion
Additional relevant art not relied upon includes:
Anderson (US 20190042894 A1), regarding “exemplary primitives include tensor convolutions, activation functions, and pooling, which are computational operations that are performed while training a convolutional neural network (CNN). ”
Chandrashekharaiah et al (US 20250328922 A1), regarding “identifying more relevant information (e.g., user-company, company-item, item-item hierarchy, item-alert, alert-attribution are the mappings being considered in the knowledge graph generation and/or updating). In some embodiments, an initial knowledge graph is established with a foundation of historical alerts utilizing sets of trained models. Knowledge graph embedding (KGE), through trained machine learning models (e.g., TransE, TransH, TransR and neural tensor network (NTN)) define distributed representations for entities and relations, sometimes referred to as entity embeddings and relation embeddings. ”
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 MEHMET YESILDAG whose telephone number is (571)272-3257. The examiner can normally be reached M-F 8:30 am - 5:00 pm.
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, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Sincerely,
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624
Prosecution Insights