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 .
Claim Rejections - 35 USC § 112
2. 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.
3. Claims 15 and 28 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”.
4. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
5. Claims 12 – 14 and 25 – 27 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 12 recites the limitation "the first language" and “the second language” in lines 2 and 3. There is insufficient antecedent basis for this limitation in the claim. Claims 13 and 14 are rejected for their dependency on claim 12 and use of the same verbiage which lacks antecedent basis.
Claim 25 recites the limitation "the first language" and “the second language” in lines 2 and 3. There is insufficient antecedent basis for this limitation in the claim. Claims 26 and 27 are rejected for their dependency on claim 25 and use of the same verbiage which lacks antecedent basis.
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 – 7, 15, 18 – 20, and 28 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 facilitating interoperability between first (700a, figure 1b utilized in 1c where the elements of 200, figure 2 are also seen in 700a) and second (700b, figure 1a utilized in 1c where the elements of 200, figure 2 are also seen in 700a) different programs in an automatic or substantially automatic manner, comprising: one or more first hyper objects (hyper parameters for 700a, paragraph 105) each having 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 first rules defining a first data function and a first communication transfer (training cycles withing the system 200, figure 2), 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 (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); a first communication transfer for first data reading and data writing for the first program (written for first programmed AI model 106 in light of 700a, figure 2); one or more second hyper objects (hyper parameters for 700b, paragraph 105) 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 (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 second data function including a second conversion function of second data structures and second data formats between a second program and the 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); a second communication transfer for second data reading and data writing for the second program (written for second programmed AI model 106 in light of 700b, figure 2); and a communication link coupled between the first and the second programs (the link is seen between the API 211 and 221, figure 2) and conveying exchange information between the first and the second programs 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).
9. As per claims 15 and 28, Brown teaches a system and method for facilitating interoperability between first (700a, figure 1b utilized in 1c where the elements of 200, figure 2 are also seen in 700a) and second (700b, figure 1a utilized in 1c where the elements of 200, figure 2 are also seen in 700a) different programs in an automatic or substantially automatic manner, comprising: one or more first hyper objects (hyper parameters for 700a, paragraph 105) each having first rules comprising one or more first functions or actions executing a first process or method (rules executed according to flow for AI Engine in figure 7), 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 (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); a first communication transfer for first data reading and data writing for the first program (written for first programmed AI model 106 in light of 700a, figure 2); one or more second hyper objects (hyper parameters for 700b, paragraph 105) 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 (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 second data function including a second conversion function of second data structures and second data formats between a second program and the 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); a second communication transfer for second data reading and data writing for the second program (written for second programmed AI model 106 in light of 700b, figure 2); and artificial intelligence network configured or trainable to facilitate the interoperability between the first and second programs (training the AI model based upon data structures for each program paragraphs 105 – 108), the artificial intelligence network includes: first artificial intelligence configured or trainable to determine at least one of: data structures, data formats or read/write data (software reading/writing to generate a trained AI model, paragraph 105) for at least one of: the first or second programs, and second artificial intelligence configured or trainable to facilitate searching for data meanings for data stored in at least one of: the first or second programs (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).
10. As per claims 5 and 18, Brown teaches a system and method, further comprising a read group of hyper objects (software reading to generate a trained AI model, paragraph 105).
11. As per claims 6 and 19, Brown teaches a system and method, wherein the read group of hyper objects conveys information to a first program data group of hyper objects (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).
12. As per claims 7 and 20, Brown teaches a system and method, wherein the first program data group of hyper objects forms a first part of an exchange standard data transform (the hyper parameters are conveyed from the hyper learner 225, figure 2, paragraph 105) and conveys the transformed data to the communication link (the link is seen between the API 211 and 221, figure 2).
Allowable Subject Matter
13. Claims 2-4, 8 - 14, 16, 17, 21 - 27, 29 - 40 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
14. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Reddy teaches a plurality of languages utilized. Biyani/Dolan/Johnson/Kelgere/Moustafa/Murrish/Shen has teachings of AI training for data communication between program models.
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AH
/HENRY TSAI/Supervisory Patent Examiner, Art Unit 2184