DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
2. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 5 – 8, 10, 23, 27 – 30, 32 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 6 – 9, 11, 28, 32 – 35, and 37 of co-pending Application No. 18/826,626. Although the claims at issue are not identical, they are not patentably distinct from each other because the instant claims are anticipated by the more detailed co-pending application claims as seen in the mapping below.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Instant Application
Co-pending Application 18/826,626
1. A system for enabling a first computer program to communicate with a second computer program, comprising: one or more hyper objects including one or more first rules comprising one or more first functions or actions executing a first process or method; the one or more first functions or actions comprising at least one of a data conversion function or data communication function for the first computer program and for a data exchange standard; another of the one or more hyper objects including one or more second rules comprising one or more second functions or actions executing a second process or method for the second computer program; and whereby a communication with the second computer program is facilitated to provide interoperability between the first computer program and the second computer program using the data exchange standard.
1. A system for facilitating interoperability between first and second different programs in an automatic or substantially automatic manner, comprising: one or more first hyper objects each having first rules comprising one or more first functions or actions executing a first process or method, the first rules defining a first data function and a first communication transfer, the first data function including a first conversion function of first data structures and second data formats between a first program and an exchange standard; a first communication transfer for first data reading and data writing for the first program; one or more second hyper objects each having second rules comprising one or more second functions or actions executing a second process or method, the second rules defining a second data function and a second communication transfer, the second data function including a second conversion function of second data structures and second data formats between a second program and the exchange standard; a second communication transfer for second data reading and data writing for the second program; and a communication link coupled between the first and the second programs and conveying exchange information between the first and the second programs to facilitate the interoperability between the first and second programs.
5. The system of claim 4, wherein the read group of hyper objects conveys information to a first computer program data group of hyper objects.
6. The system of claim 5, wherein the read group of hyper objects conveys information to a first program data group of hyper objects.
6. The system of claim 5, wherein the program data group forms a part of an ES data transform and conveys the transformed data to the bidirectional link.
7. The system of claim 6, wherein the first program data group of hyper objects forms a first part of an exchange standard data transform and conveys the transformed data to the communication link.
7. The system of claim 6, wherein a second program data group of hyper objects forms a part of the ES data transform and conveys information from the bidirectional link.
8. The system of claim 7, wherein a second program data group of hyper objects forms a second part of the exchange standard data transform and conveys information from the communication link.
8. The system of claim 7, wherein information from the second program data group of hyper objects is conveyed to a write group of hyper objects.
9. The system of claim 8, wherein information from the second program data group of hyper objects is conveyed to a write group of hyper objects.
10. The system of claim 9, wherein the groups of hyper objects are executed under the control of a server.
11. The system of claim 8, wherein the first and second groups of hyper objects are executed under a control of a server.
23. A method for enabling a first computer program to communicate with a second computer program, comprising: providing one or more hyper objects including one or more first rules comprising one or more first functions or actions executing a first process or method, the one or more first functions or actions comprising at least one of a data conversion function or data communication function for the first computer program and for a data exchange standard; providing another of the one or more hyper objects including one or more second rules comprising one or more second functions or actions executing a second process or method for the second computer program; facilitating a communication with the second computer program to provide interoperability between the first computer program and the second computer program using the data exchange standard; and providing at least one neural network trainable to facilitate the interoperability between the first and second programs, the neural network includes an artificial intelligence configured or trainable to determine at least one of: data structures, data formats or read/write data for each of the first and second programs, the neural network further includes the artificial intelligence configured or trainable to facilitate searching for data meanings for data stored in at least one of the first and second programs.
28. A method for facilitating interoperability between first and second different programs in an automatic or substantially automatic manner, comprising: providing one or more first hyper objects each having first rules comprising one or more first functions or actions executing a first process or method, the first rules defining a first data function and a first communication transfer, the first data function including a first conversion function of first data structures and second data formats between a first program and an exchange standard, providing a first communication transfer for first data reading and data writing for the first program; providing one or more second hyper objects each having second rules comprising one or more second functions or actions executing a second process or method, the second rules defining a second data function and a second communication transfer, the second data function including a second conversion function of second data structures and second data formats between a second program and the exchange standard; providing a second communication transfer for second data reading and data writing for the second program; and providing at least one neural network trainable to facilitate the interoperability between the first and second programs, the neural network includes an artificial intelligence configured or trainable to determine at least one of: data structures, data formats or read/write data for each of the first and second programs, the neural network further includes the artificial intelligence configured or trainable to facilitate searching for data meanings for data stored in at least one of the first and second programs.
27. The method of claim 26, wherein the read group of hyper objects conveys information to a first computer program data group of hyper objects.
32. The method of claim 31, wherein the read group of hyper objects conveys information to a first program data group of hyper objects.
28. The method of claim 27, wherein the program data group forms a part of an ES data transform and conveys the transformed data to the bidirectional link.
33. The method of claim 32, wherein the first program data group of hyper objects forms a first part of an exchange standard data transform and conveys the transformed data to a communication link.
29. The method of claim 28, wherein a second program data group of hyper objects forms a part of the ES data transform and conveys information from the bidirectional link.
34. The method of claim 33, wherein a second program data group of hyper objects forms a second part of the exchange standard data transform and conveys information from the communication link.
30. The method of claim 29, wherein information from the second program data group of hyper objects is conveyed to a write group of hyper objects.
35. The method of claim 34, wherein information from the second program data group of hyper objects is conveyed to a write group of hyper objects.
32. The method of claim 31, wherein the groups of hyper objects are executed under the control of a server.
37. The method of claim 36, wherein the first and second groups of hyper objects are executed under a control of a server.
Claim Rejections - 35 USC § 112
3. 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.
4. Claims 13, 16 – 22, and 23 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 enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. The claims recite “artificial intelligence” however the specification does not recite the verbiage “artificial intelligence”.
Claim Objections
5. Claims 6, 7, 28, and 29 are objected to because of the following informalities: the claims recite “ES data” wherein the first instance in a series of claims an abbreviation must be clearly identified and corrected to reflect “exchange standard (ES)”.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
6. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
7. Claims 1 – 5, 11, 12, 23 – 27 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Brown et al. (US Publication Number 2018/0357047, hereinafter “Brown”).
8. As per claim 1, Brown teaches a system for enabling a first computer program (700a, figure 1b utilized in 1c where the elements of 200, figure 2 are also seen in 700a) to communicate with a second computer program (700b, figure 1a utilized in 1c where the elements of 200, figure 2 are also seen in 700a), comprising: one or more hyper objects (hyper parameters for 700a, paragraph 105) including one or more first rules comprising one or more first functions or actions executing a first process or method (training the AI model 106 features hyper objects/parameters configured into the hyper-learner 225 which consists of rules for the first function, figure 2, paragraph 105); the one or more first functions or actions comprising at least one of a data conversion function or data communication function for the first computer program and for a data exchange standard (the first computer program is a function of 700a in which a model is trained according to a set of trained AI objects, additionally it can be coded with additional function of data conversion by figure 6a, paragraphs 105 – 107); another of the one or more hyper objects (hyper parameters for 700b, paragraph 105) including one or more second rules comprising one or more second functions or actions executing a second process or method for the second computer program (training the AI model 106 features hyper objects/parameters configured into the hyper-learner 225 which consists of rules for the first function, figure 2, paragraph 105); and whereby a communication with the second computer program is facilitated to provide interoperability between the first computer program (the interoperability is assisted by the API 211 see in figures 1c and 2, paragraphs 69 – 73) and the second computer program using the data exchange standard (the second computer program is a function of 700b in which a model is trained according to a set of trained AI objects, additionally it can be coded with additional function of data conversion by figure 6b, paragraphs 105 – 107, seen in light of figure 1c both 700a and 700b consist of the structure seen in figure 2 element 200 with its objective of generating a trained AI model 106 in each).
9. As per claim 23, Brown teaches a method for enabling a first computer program (700a, figure 1b utilized in 1c where the elements of 200, figure 2 are also seen in 700a) to communicate (communicate via API 211, figures 1c and 2) with a second computer program (700b, figure 1a utilized in 1c where the elements of 200, figure 2 are also seen in 700a), comprising: providing one or more hyper objects (hyper parameters for 700a, paragraph 105) including one or more first rules comprising one or more first functions or actions executing a first process or method, the one or more first functions or actions comprising at least one of a data conversion function or data communication function for the first computer program and for a data exchange standard (training the AI model 106 features hyper objects/parameters configured into the hyper-learner 225 which consists of rules for the first function, figure 2, paragraph 105); providing another of the one or more hyper objects (hyper parameters for 700b, paragraph 105) including one or more second rules comprising one or more second functions or actions executing a second process or method for the second computer program (training the AI model 106 features hyper objects/parameters configured into the hyper-learner 225 which consists of rules for the first function, figure 2, paragraph 105); facilitating a communication with the second computer program to provide interoperability between the first computer program and the second computer program using the data exchange standard; and providing at least one neural network (neural network AI model, paragraphs 37 and 38) trainable to facilitate the interoperability between the first and second programs (the interoperability is assisted by the API 211 see in figures 1c and 2, paragraphs 69 – 73), the neural network includes an artificial intelligence configured or trainable to determine at least one of: data structures, data formats or read/write data for each of the first and second programs (training the AI model based upon data structures for each program paragraphs 105 – 108), the neural network further includes the artificial intelligence configured or trainable to facilitate searching for data meanings for data stored in at least one of the first and second programs (the second computer program is a function of 700b in which a model is trained according to a set of trained AI objects, additionally it can be coded with additional function of data conversion by figure 6b, paragraphs 105 – 107, seen in light of figure 1c both 700a and 700b consist of the structure seen in figure 2 element 200 with its objective of generating a trained AI model 106 in each).
10. As per claims 2 and 24, Brown teaches a system and method, wherein the rules include the first function, the data reading and the data writing (software reading/writing to generate a trained AI model, paragraph 105).
11. As per claims 3 and 25, Brown teaches a system and method, further including a communication link for communication for conveying information of the data exchange standard (the link is seen between the API 211 and 221, figure 2).
12. As per claims 4 and 26, Brown teaches a system and method, wherein the adapter includes a read group of hyper objects configured to receive information from a first bidirectional link which is coupled to the first program (bidirectional link seen in c/d/f/g figure 2, which is seen in the first program).
13. As per claims 5 and 27, Brown teaches a system and method, wherein the read group of hyper objects conveys information to a first computer program data group of hyper objects (the hyper parameters are conveyed from the hyper learner 225, figure 2, paragraph 105).
14. As per claim 10, Brown teaches a system, wherein the groups of hyper objects are executed under the control of a server (hyper parameter processing is seen to be handled via server systems, paragraph 166 highlights the server processing data flow seen in figure 7 for the AI Engine).
15. As per claim 11, Brown teaches a system, wherein the at least one of a data conversion function or data communication function comprising data structures and/or data formats (the first and second programs have data communication function comprising data structures seen in figures 6a and 6b utilized in the training of the AI program model).
Allowable Subject Matter
16. Claims 6 – 10, 13 – 22, and 28 – 32 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.
Conclusion
17. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Biyani/Dolan/Johnson/Kelgere/Krishnamoorthy/Moustaga/Murrish/Reddy/Shen have teachings of program communication and data transfer with AI training handling therein.
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AH
/HENRY TSAI/Supervisory Patent Examiner, Art Unit 2184