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 .
Claims Status
Claims 1-15 are pending and rejected.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 9/30/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1:
Claims 1-5 are directed to a method, which is a process. Claims 6-10 are directed to a system, which is a machine. Claims 11-15 are directed to a non-transitory machine-readable information storage medium, which is an apparatus. Therefore, claims 1-15 are directed to one of the four statutory categories of invention.
Step 2A (Prong 1):
Representative claim 1 sets forth the following limitations which recite the abstract idea of providing product recommendations:
acquiring a plurality of metadata associated with each of a specific livestock embryo from a plurality of livestock embryos;
creating a Non-Fungible Token (NFT) from a plurality of NFTs for each of the specific livestock embryo from the plurality of livestock embryos over a blockchain based platform using the plurality of metadata of the plurality of livestock embryos;
generating a smart contract in a blockchain network defining a logic and functionality of the created NFT for each of the specific livestock embryo, a plurality of rules and conditions of ownership and one or more transactions associated with the plurality of NFTs for recording one or more new NFTs, transferring ownership, and managing associated data;
generating personalized recommendations for the plurality of NFTs of the plurality of livestock embryos to the one or more users, wherein the personalized recommendations are generated by using a machine learning based reinforcement (RF) model, and wherein the machine learning based reinforcement (RF) model is trained using a database on the plurality of NFTs, one or more policies of breeding, a domain knowledge on the plurality of livestock embryos, and one or more user preferences; and
enabling a plurality of transactions for a fair trading of the plurality of livestock embryos using a marketplace transaction system based on the generated personalized recommendations.
The recited limitations above set forth steps to provide product recommendations. These limitations amount to certain methods of organizing human activity, including commercial or legal interactions (e.g. advertising, marketing or sales activities or behaviors).
Such concepts have been identified by the courts as abstract ideas (see: MPEP 2106).
Step 2A (Prong 2):
Examiner notes that representative claim 1 recites additional elements such as a processor, etc.
When taken individually and as a whole, the additional elements of claim 1 do not integrate the recited judicial exception into a practical application of the exception. The claim merely includes instruction to implement an abstract idea on a computer, or to merely use a computer as a tool to perform an abstract idea, while the additional elements do no more than generally link the use of a judicial exception to a particular field of technological environment or field of use.
Furthermore, this is also because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement a judicial exception with a particular machine, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In view of the above, under Step 2A (Prong 2), claim 1 does not integrate the recited exception into a practical application (see again: MPEP 2106).
Step 2B:
When taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the steps 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. Certain additional elements also recite well-understood, routine, and conventional activity (See MPEP 2106.05(d)).
Even if considered as an ordered combination, the additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, claim 1 does not provide an inventive concept under step 2B, and is ineligible for patenting.
Dependent claims 2-5 recite further complexity to the judicial exception (abstract idea) of claim 1, such as by further defining the steps for providing product recommendations. Thus, each of claims 2-5 are held to recite a judicial exception under Step 2A (Prong 1) for at least similar reasons as discussed above.
Therefore, dependent claims 2-5 do not add “significantly more” to the abstract idea. The dependent claims recite additional functions that describe the abstract idea and only generally link the abstract idea to a particularly technological environment, and applied on a generic computer. Further, the additional limitations fail to provide an improvement to the functioning of the computer, another technology, or a technical field.
Even when viewed as an ordered combination, the dependent claims simply convey the abstract idea itself applied on a generic computer and are held to be ineligible under Steps 2A/2B for at least similar rationale as discussed above regarding claim 1.
The analysis above applies to all statutory categories of invention. Regarding independent claims 6 (system) and 11 (medium), the claims recite substantially similar limitations as set forth in claim 1. As such, claims 6 and 11 and their dependent claims 7-10 and 12-15 are rejected for at least similar rationale as discussed above.
Claim Rejections - 35 USC § 103
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 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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Regenor (U.S. Pre-Grant Publication No. 2022/0351165 A1), in view of Zaninovic et al. (U.S. Pre-Grant Publication No. 2021/0272282 A1) (“Zaninovic”).
Regarding claims 1, 6 and 10, Regenor teaches a processor implemented method (and related system and medium), comprising:
acquiring, via one or more hardware processors, a plurality of metadata associated with each of a specific livestock embryo from a plurality of livestock embryos (Fig. 12; para [0020], [0058], create a decentralized verifiable authenticity...animal's genetics 548 and medical history 550 can also be recorded in the NFT as an attestation of the value of the animal);
creating, via one or more hardware processors, a Non-Fungible Token (NFT) from a plurality of NFTs for each of the specific livestock embryo from the plurality of livestock embryos over a blockchain based platform using the plurality of metadata of the plurality of livestock embryos (Fig. 12; para [0020], [0058], create a decentralized verifiable authenticity of high value livestock and animal provenance and bloodline authenticity);
generating, via the one or more hardware processors, a smart contract in a blockchain network defining a logic and functionality of the created NFT for each of the specific livestock embryo, a plurality of rules and conditions of ownership and one or more transactions associated with the plurality of NFTs for recording one or more new NFTs, transferring ownership, and managing associated data (Fig. 12; para [0020], [0058], blockchain smart contracts may be employed to define the terms and conditions of insemination of the animal...Secure IP libraries of transactions and bloodlines can be created and maintained and the NFT structure of the animal's provenance); and
enabling, via the one or more hardware processors, a plurality of transactions for a fair trading of the plurality of livestock embryos using a marketplace transaction system based on the generated personalized recommendations.
Although Regenor teaches the above method (and related system and medium), Regenor does not explicitly teach generating, via the one or more hardware processors, personalized recommendations for the plurality of NFTs of the plurality of livestock embryos to the one or more users, wherein the personalized recommendations are generated by using a machine learning based reinforcement (RF) model, and wherein the machine learning based reinforcement (RF) model is trained using a database on the plurality of NFTs, one or more policies of breeding, a domain knowledge on the plurality of livestock embryos, and one or more user preferences.
In a similar field of endeavor, Zaninovic teaches:
generating, via the one or more hardware processors, personalized recommendations for the plurality of NFTs of the plurality of livestock embryos to the one or more users, wherein the personalized recommendations are generated by using a machine learning based reinforcement (RF) model, and wherein the machine learning based reinforcement (RF) model is trained using a database on the plurality of NFTs, one or more policies of breeding, a domain knowledge on the plurality of livestock embryos, and one or more user preferences (para [0002]-[0003], [0007]; para [0011]-[0014], output an identity of each of the selected graded AF embryos and a number of the selected graded AF embryos to be recommended to be implanted in the gestating female based on a desired outcome input into the embryo selection module following implantation… the deep neural network is a convolutional neural network; para [0029], [0038], [0040], [0055]-[0056]);
Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the noted limitations as taught by Zaninovic in the method of Regenor, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Namely, an improved system using objective measures to reliably predict quality of embryos without human intervention (See Zaninovic: para [0002]).
Regarding claims 2, 7 and 12, Regenor and Zaninovic teach the above method, system and medium of claims 1, 6 and 11. Regenor also teaches wherein the generated smart contract ensures security, authenticity, and enforceability of the plurality of NFTs on the blockchain network (para [0020], [0058], decentralized verifiable authenticity of high value livestock and animal provenance and bloodline authenticity).
Regarding claims 3, 8 and 13, Regenor and Zaninovic teach the above method, system and medium of claims 1, 6 and 11. Zaninovic also teaches wherein the machine learning based reinforcement learning (RF) model generates personalized recommendations by:
predicting a breeding outcomes for each available livestock embryo from the plurality of livestock embryos (para [0003], probability that a given graded AF embryo will result in a successful pregnancy after the given AF embryo is implanted in a gestating female for each of the AF embryos; para [0075], using STORK to classify the fair-quality embryo images … embryos were predicted to be good-quality and poor-quality);
assigning a rank to each available livestock embryo from the plurality of livestock embryos based on the predicted breeding outcomes with most favorable livestock embryos given higher rankings (para [0003], based on a grade of the given AF embryo and clinical parameters associated with the gestating female); and
generating personalized recommendations for the plurality of livestock embryos based on the rank (para [0003], Graded AF embryos to be recommended to be implanted in the gestating female are selected from the set based on the probability of successful pregnancy and an outcome desired).
Regarding claims 4, 9 and 14, Regenor and Zaninovic teach the above method, system and medium of claims 1, 6 and 11. Regenor also teaches wherein the plurality of transactions enabled by the marketplace transaction system for the plurality of livestock embryos include at least one of (i) an auction, (ii) exchange of the plurality of livestock embryos, (iii) consignment sales, (iv) future contracts, and (v) options contracts (para [0020]-[0021], [0058]-[0059], blockchain smart contracts may be employed to define the terms and conditions of insemination of the animal or use of the animal's semen for insemination. This enables secure libraries of transactions and bloodlines… Blockchain smart contracts may be employed for remuneration of fees to the rights owners and to define the terms and conditions to lessee, consigner, or owner).
Regarding claims 5, 10 and 15, Regenor and Zaninovic teach the above method, system and medium of claims 1, 6 and 11. Regenor also teaches wherein the plurality of transactions enabled by the marketplace transaction system for the plurality of livestock embryos ensure (i) flexibility due to preservation of the plurality of livestock embryos for longer duration using cryogenics process, and (ii) matchmaking for selling to include one or more schemes and constrained selling (Fig. 2; para [0046], unique digital asset ID code is linked with the unique user ID code of first user 12 and a first transaction block is created in a distributed blockchain ledger in blockchain network 16. The blockchain ledger thereby records possession of the cryptographic digital asset and the respective physical asset with first user 12. The digital asset may then be placed within a digital marketplace or store at step 118 whereby possession and/or ownership of the digital asset and physical asset may be freely transferred to a second part).
Conclusion
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/ANAND LOHARIKAR/Primary Examiner, Art Unit 3689