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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite mathematical operations and mental processes of observation, evaluation and judgement. This judicial exception is not integrated into a practical application and does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of the claims are extra-solution activity, generic hardware and linking to particular technological field in combination to implement the abstract idea.
Claims 1, 10 and 19
Step 1: The claim recites a method, system and non-transitory computer readable medium and therefore, it falls into the statutory categories.
Step 2A Prong 1: The claim recites, inter alia:
filtering the 2-dimensional matrix based on map information; (This is mathematical operation can be performed with aid of pen and paper, see para. [0044] of instant application.)
converting the filtered 2-dimensional matrix to 1-dimensional data; (This is a mental process of observation, evaluation and judgement wherein a user converts the remaining 2D matrix cells to 1D data or a vector. Can be done with the aid of pen and paper. See para. [0045] of instant specification.)
converting the 1-dimensional data for future presence of objects to a 2-dimensional matrix representing the future presence of objects. (This is a mental process of observation, evaluation and judgement wherein a user converts the remaining 1D vector to a 2D matrix. Can be done with the aid of pen and paper. )
Step 2A Prong 2: This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
obtaining a 2-dimensional matrix representing presence of objects in an area, each of values of the 2-dimensional matrix representing presence of objects in corresponding sub-region of the area; (This is receiving data which is data collection and thus extra-solution activity, see MPEP 2106.05(g).)
inputting a series of the 1-dimensional data to a trained prediction machine learning model to obtain 1-dimensional data for future presence of objects; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
a controller (claim 10), a processor and non-transitory computer readable medium (claim 19) (This is generic hardware used to perform the abstract idea, see MPEP 2106.05(f).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere insignificant extra solution activity in combination of generic computer hardware performing generic functions that are implemented to perform the disclosed abstract idea above.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The additional elements of: “obtaining a 2-dimensional matrix representing presence of objects in an area, each of values of the 2-dimensional matrix representing presence of objects in corresponding sub-region of the area;” is data collecting and is well-understood, routine and conventional. See MPEP 2106.06(d)(II)(i) wherein it cites “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) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016)”. The limitations of “inputting a series of the 1-dimensional data to a trained prediction machine learning model to obtain 1-dimensional data for future presence of objects; and” is a high level citations of using a trained machine learning model by inputting already determined data to get an output, and is thus adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. The use of the controller, processor and non-transitory computer readable medium is also generic computer hardware used to implement the abstract idea, see MPEP 2106.05(f).
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claims 2 and 11
Step 2A Prong 1: The claim recites, inter alia:
Claims 2 and 11 inherits the abstract idea of claims 1 and 2.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a Long Short-Term Memory (LSTM) model, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere generic computer hardware performing generic functions that are implemented to perform the disclosed abstract idea above.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a Long Short-Term Memory (LSTM) model, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claims 3 and 12
Step 2A Prong 1: The claim recites, inter alia:
Claims 3 and 12 inherits the abstract idea of claim 1 and 10.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein each of the plurality of encoders compresses corresponding 1-dimensional data to output a set of vectors; the LSTM model receives a plurality of the sets of vectors as input and outputs another set of vectors; and the decoder decompresses the another set of vectors to obtain the 1-dimensional data for future presence of objects. (This amounts to linking the abstract idea to particular technological field, see MPEP 2106.05(h).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere linking the abstract idea to a particular technological field, machine learning.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein each of the plurality of encoders compresses corresponding 1-dimensional data to output a set of vectors; the LSTM model receives a plurality of the sets of vectors as input and outputs another set of vectors; and the decoder decompresses the another set of vectors to obtain the 1-dimensional data for future presence of objects. (This amounts to linking the abstract idea to particular technological field, see MPEP 2106.05(h).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere linking the abstract idea to a particular technological field, machine learning.
Claims 4 and 13
Step 2A Prong 1: The claim recites, inter alia:
Claims 4 and 13 inherits the abstract idea of claims 1 and 10.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein each of the set of vectors includes 8 vectors, and each of the another set of vectors includes 8 vectors. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere extra-solution activity that states the data takes a particular form.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein each of the set of vectors includes 8 vectors, and each of the another set of vectors includes 8 vectors. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as it is mere extra-solution activity that states the data takes a particular form and does not change the abstract idea.
Claims 5 and 14
Step 2A Prong 1: The claim recites, inter alia:
Claims 5 and 14 inherits the abstract idea of claims 1 and 10.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a transformer, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere generic computer hardware performing generic functions that are implemented to perform the disclosed abstract idea above.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a transformer, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claims 6 and 15
Step 2A Prong 1: The claim recites, inter alia:
filtering the 2-dimensional matrix based on the map information comprises selecting values in the 2-dimensional matrix corresponding to the drivable sub-regions and removing values in the 2-dimensional matrix corresponding to the non-drivable sub-regions. (This is a mathematical operation that can be performed with aid of pen and paper, see para. [0044] of instant application.)
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the map information includes information about drivable sub-regions and information about non-drivable sub-regions in the area; and (This is extra-solution activity of what form the data to be manipulated or used takes, see MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as it is mere extra-solution activity of what form the data to be manipulated takes.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the map information includes information about drivable sub-regions and information about non-drivable sub-regions in the area; and (This is extra-solution activity of what form the data to be manipulated or used takes, see MPEP 2106.05(g).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as it is mere extra-solution activity of what form the data to be manipulated takes.
Claims 7 and 16
Step 2A Prong 1: The claim recites, inter alia:
Claim 7 and 16 inherits the abstract idea of claim 6 and 15.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the 1-dimensional data includes the selected values. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere extra-solution activity that states the data takes a particular form.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the 1-dimensional data includes the selected values. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as it is mere extra-solution activity that states the data takes a particular form and does not change the abstract idea.
Claim 8 and 17
Step 2A Prong 1: The claim recites, inter alia:
Claims 8 and 17 inherits the abstract idea of claim 1 and 10.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
training a prediction machine learning model to obtain the trained prediction machine learning model by: reducing sizes of middle layers of the prediction machine learning model while an input to the prediction machine learning model matches with an output of the prediction machine learning model. (This amounts to training a machine learning model and is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of how an already trained machine learning model was trained. )
the controller; (This is generic computer hardware use to perform the abstract idea, see MPEP 2106.05(f).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as it is mere use a generic tool used to implement the abstract idea.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
training a prediction machine learning model to obtain the trained prediction machine learning model by: reducing sizes of middle layers of the prediction machine learning model while an input to the prediction machine learning model matches with an output of the prediction machine learning model. (This amounts to training a machine learning model and is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of how an already trained machine learning model was trained. )
the controller; (This is generic computer hardware use to perform the abstract idea, see MPEP 2106.05(f).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as it is mere use a generic tool used to implement the abstract idea.
Claims 9 and 18
Step 2A Prong 1: The claim recites, inter alia:
Claims 9 and 18 inherits the abstract idea of claims 1 and 10.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the each of values of the 2-dimensional matrix represents a number of vehicles in corresponding sub-region of the area. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere extra-solution activity that states the data takes a particular form.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the each of values of the 2-dimensional matrix represents a number of vehicles in corresponding sub-region of the area. (This is extra-solution of what form the data to manipulated or used take, see MPEP 2106.05(g).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as it is mere extra-solution activity that states the data takes a particular form and does not change the abstract idea.
Claim 20
Step 2A Prong 1: The claim recites, inter alia:
Claim 20 inherits the abstract idea of claims 19.
Step 2A Prong 2:
This judicial exception is no integrated into a practical application. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a Long Short-Term Memory (LSTM) model, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
wherein each of the plurality of encoders compresses corresponding 1-dimensional data to output a set of vectors; the LSTM model receives a plurality of the sets of vectors as input and outputs another set of vectors; and the decoder decompresses the another set of vectors to obtain the 1-dimensional data for future presence of objects. (This amounts to linking the abstract idea to particular technological field, see MPEP 2106.05(h).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere generic computer hardware in combination with linking to particular technological field that are implemented to perform the disclosed abstract idea above.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Aside from the limitations above, the claim recites:
wherein the trained prediction machine learning model includes a plurality of encoders, a Long Short-Term Memory (LSTM) model, and a decoder. (This is cited at high level of generality resulting in adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level application of a previously trained model to make a prediction);
wherein each of the plurality of encoders compresses corresponding 1-dimensional data to output a set of vectors; the LSTM model receives a plurality of the sets of vectors as input and outputs another set of vectors; and the decoder decompresses the another set of vectors to obtain the 1-dimensional data for future presence of objects. (This amounts to linking the abstract idea to particular technological field, see MPEP 2106.05(h).)
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere generic computer hardware in combination with linking to particular technological field that are implemented to perform the disclosed abstract idea above.
Allowable Subject Matter
Claims 1-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
None of the cited prior art references alone or in combination disclose the claim limitations of converting the 2D matrix to a 1D data vector, inputting the 1D vector to a machine learning model to predict future presence of objects and converting the 1D data back to a 2D presence matrix.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAULINHO E SMITH whose telephone number is (571)270-1358. The examiner can normally be reached Mon-Fri. 10AM-6PM CST.
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, Abdullah Kawsar can be reached at 571-270-3169. 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.
/PAULINHO E SMITH/Primary Examiner, Art Unit 2127
Prosecution Insights