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 .
Applicant’s response does not contain any arguments to respond to. The rejection is updated below.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: Machine Learning to Estimate the Weight of Groups of Fish Using Distributional Data About Weights of Fish.
Claim Objections
The below claims are objected to because of the following informalities:
Claims 23, 30, and 37 are objected to for reciting “foe.”
The examiner notes that canceling all of the claims and entering new claims makes it harder to identify this type of issue.
Appropriate correction is required.
Drawings
As shown below, the figures refer to X Development LLC instead of TidalX AI. Correction is optional.
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Double Patenting
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 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of each of U.S. Patent Nos. 12322173, 12272169, 12254712, 12229937 and 12131568 in view of the 102(a)(1) prior art, as applied below.
Both the pending claims and the conflicting patents are all directed to machine learning for pictures of fish, generally for estimating the weight of the fish. Therefore, all of the conflicting patents are directed to the same problem as the present application. Further, any differences between the present claims and the claims in any of the conflicting patents are obvious in view of the 102(a)(1) prior art as applied below. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine102(a)(1) prior art with any of the conflicting patents because the 102(a)(1) prior art is the actual implementation of this technology.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“locomotion devices” in claims 21, 28, and 35.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
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.
Claims 1 and 21-39 (all claims) 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 written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 27, and 34 recite “generating a predicted distribution of biomass values … ,” but this is unlimited functional claiming due to the wide variety of machine learning techniques. MPEP 2173.05(g). Limiting the claim to a particular architecture, such as a convolutional neural network, is expected to overcome this rejection (the reference to a CNN is illustrative, the examiner did not find this term in the specification). Additionally, to overcome the rejection, the claimed architecture needs to be suitable for what is claimed, such as operating on distributions rather than individual values.
Claims 1, 27, and 34 recite “obtaining actual distribution of biomass values for the population of the fish.” However, this claim encompasses two approaches, both weighing the fish as a group (e.g., everything in the fishnet) and weighing the fish individually. The specification is directed to the first approach, and specifically disclaims the latter approach. See, e.g., “The solution described herein … without being trained using training data that uses weight of individual fish.” Specification, [0005]. Therefore, as per Lizardtech, there is not written description support for the full scope of the claim. MPEP 2163(II)(A)(3)(a)(ii).
Claims 1, 27, and 34 recite “updating one or more parameters,” but this is unlimited functional claiming due to the wide variety of machine learning techniques. MPEP 2173.05(g). Limiting the claim to a particular technique, such as backpropagation, is expected to overcome this rejection (the reference to backpropagation is illustrative, the examiner did not find this term in the specification). Additionally, to overcome the rejection, the claimed architecture needs to be suitable for what is claimed, such as operating on distributions rather than individual values.
Claims 21, 28, and 35 are rejected as a formality because the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph language in these claims does not have sufficient structure in the specification. This rejection matches the below indefiniteness rejection for the same language. Once that rejection is overcome, this one will be as well.
Claims 26 and 33 recite “wherein the predicted distribution of biomass values are generated from the truss length measurements of each fish in the population.” However, the specification teaches that individual measurements (such as the truss length) are not used. “A solution described in this specification includes techniques to enable the use of images from actual environments in training data by using fish population data as ground truth data instead of individual fish measurements.” Specification, [0005].
Dependent claims are likewise rejected.
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.
Claims 1 and 21-39 (all claims) 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.
Claims 1, 27, and 34 recite “a predicted distribution of biomass values.” However, the singular ‘a’ conflicts with the specification’s teaching that the distribution is of various predictions. See, e.g., specification [0084] and Figs. 4A and 4B.
Claim limitation “locomotion devices” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Here, the detailed description only references “locomotion” once, in specification [0012], but does not identify any examples. Therefore, claims 21, 28, and 35 are indefinite and rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Dependent claims are likewise rejected.
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 and 21-39 (all claims) are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental process) without significantly more.
Step 1: Claim 1 (and its dependents) recite a method, and processes are eligible subject matter.
Claim 27 (and its dependents) recite a non-transitory computer-readable medium, and manufactures are eligible subject matter.
Claim 35 recites a system, and machines are eligible subject matter.
Step 2A, prong one: All of the elements of claims 1 and 21-39 (all claims) are a mental process because training a machine learning model is a mental process. Further, the various models are also mental processes, see example 47, claim 2, element (d) (from the July 2024 AI subject matter eligibility examples). MPEP 2106.04(a)(2)(III)(C) explains that use of a generic computer or in a computer environment is still a mental process. In particular, this section begins by citing Gottschalk v. Benson, 409 US 63 (1972). “The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea.” In Benson the Supreme Court did not separately analyze the computer hardware at issue; the specifics of what hardware was claimed is only included in an appendix to the decision.
Because there are no additional elements, no further analysis is required for Step 2A, prong two or Step 2B.
Examiner Note
In the interest of compact prosecution, the examiner asserts that the below 102(a)(1) prior art was widely used far enough before the priority date to qualify as well-understood, routine, conventional (note that the prior art one year grace period does not apply to eligibility analyses and that machine learning is a fast moving field). Additionally, the pertinent art in the conclusion includes an article from CNET from March 2020.
Claim Rejections - 35 USC § 102
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.
Claims 1 and 21-39 (all claims) are rejected under 35 U.S.C. 102(a)(1) based upon a public use or sale or other public availability of the invention.
Overview
As is detailed below, TidalX (then part of Alphabet, Google’s parent company) developed this technology in approximately 2018 (and stated that it was developed in early 2020). By early 2021, one of the world’s largest seafood companies (and specifically the world’s largest producer of Atlantic salmon with harvest volumes of 475,000 tons in 2023) had rolled out this technology to over 100 sites where it farmed fish that it sold. The seafood company touted the success of this roll out at their capital markets day – all more than one year before the earliest asserted priority date.
This application is filed by TidalX AI Inc. The examiner’s review of the prior art shows that this technology was commercially exploited by Mowi ASA, a Norwegian seafood company. The analysis proceeds in three parts. First, the examiner reviews the relationship between TidalX AI and Mowi. Second, the examiner shows that Mowi was commercially exploiting this technology early enough to be prior art. Third, the examiner compares Mowi’s activities to the present specification.
Relationship between TidalX AI and Mowi ASA
Reference A:
TidalX AI’s homepage (https://www.tidalx.ai/en) states “Tidal’s AI models were trained through an extensive partnership with the world's largest Atlantic salmon producer. They have been refined by testing in hundreds of commercial pens across diverse geographies and extreme environmental conditions.”
A screenshot of the homepage is attached. The examiner believes that the partnership was with Mowi (e.g., https://mowi.com/about-us/ describes the company as “the world’s largest producer of Atlantic salmon.”)
Reference B:
IEEE Spectrum has an article written by the CEO of TidalX AI, the global director of sales and marketing for TidalX AI and an advisor to TidalX AI. “This Alphabet Spin-off Brings ‘Fishal Recognition’ to Aquaculture” IEEE Spectrum April 7, 2025 (May 2025 print edition), Rajesh Jadhav, Kira K. Smiley, Grace C. Young, retrieved from https://spectrum.ieee.org/aquaculture.
For example:
The article states (p. 4): To get started, we partnered with Mowi ASA, the largest salmon-aquaculture company in the world, to develop underwater camera and software systems for fish farms. For two weeks in 2018, our small team of Silicon Valley engineers lived and breathed salmon aquaculture, camping out in an Airbnb on a small Norwegian island and commuting to and from the fish farm in a small motorboat.
On pp. 11-12, the article says, in relevant part, “Developing models for Mowi’s desired accuracy required a drastically larger dataset. … But the need for better data sent us to Norway in 2018 to collect footage. … A second breakthrough came when we got access to data from the fish farms’ harvests, when every fish is individually weighed. … Soon we had a model capable of making highly precise and accurate estimates of fish weight distributions for the entire population within a given enclosure.”
It appears that model capable of estimating fish weight distributions was developed “soon” after an unspecified date in 2018. Inferring from the combination of the two passages suggests that the breakthrough occurred during the two weeks that the team was in Norway (i.e., in 2018). The inference that this occurred in 2018 aligns with (pp. 3-4) the article’s description of team members weighing hundreds of fish as part of a visit to a fish farm in 2018.
Reference C:
Mowi’s website has a news article titled “Mowi collaborates with X, Alphabet’s innovation engine, to make salmon farming more sustainable,” March 3, 2020, retrieved from https://mowi.com/news/mowi-collaborates-with-x-alphabets-innovation-engine-to-make-salmon-farming-more-sustainable/ that begins with the statement “Over the last three years, Mowi has been researching and testing a new sensing system developed by Tidal at Alphabet’s X.”
Reference D:
Tidal’s website states (https://www.tidalx.ai/en/company):
The earliest tests of the Tidal system were in a kiddie pool at the X lab. As our system became more sophisticated, we brought prototypes to Norway for extensive testing—from protected fjords in the Arctic Circle, to the open ocean in the North Sea.
We observed 46 million fish, collected 28 billion data points to train our ML models, and worked with industry-leading fish farmers such as Mowi to improve our hardware and software.
The examiner’s search of the prior art has not found evidence that Tidal worked in Norway outside of their partnership with Mowi.
Commercial Exploitation (including Ready for Patenting)
The earliest asserted priority date for this application is April 13, 2022. Because this prior art is applied under 35 U.S.C. 102(a)(1), there are no exceptions applicable for prior art that became public more than one year before.
The above cited March 3, 2020 article from Mowi (Reference C) states:
After an extensive research and development period involving field testing and data collection, the project is now ready for commercial validation and Mowi will roll out the technology to multiple sites across Norway.
Commercial validation is a type of commercial exploitation. What is being validated is not the technology, but rather the commercial opportunity.
Reference E:
On March 2, 2020 Neil Davé (then general manager of Tidal within Alphabet) wrote “Introducing Tidal,” a Medium blog post (retrieved from https://blog.x.company/introducing-tidal-1914257962c3).
After spending lots of time out on the water, we’ve developed an underwater camera system and a set of machine perception tools that can detect and interpret fish behaviors not visible to the human eye. Our software can track and monitor thousands of individual fish over time, observe and log fish behaviors like eating, and collect environmental information like temperature and oxygen levels. This kind of information gives farmers the ability to track the health of their fish and make smarter decisions about how to manage the pens — like how much food to put in the pens, which we hope can help reduce both costs and pollution.
The examiner notes that the word “developed” is in the past tense, i.e., the development has been completed. The examiner also notes that immediately below this paragraph, the original blog post includes a video clip of machine learning tracking fish swimming with squares of various colors tracking heads (and fish pellets) and chains of line segments tracking body movements. The examiner also notes that the blog post closes with “If Tidal’s mission sounds like something you’d like to be part of, please get in touch.” (The phrase please get in touch is hyperlinked to https://www.x.company/contact/?utm_source=tid). While this is suggestive of commercial exploitation, it is not definitive. Additionally, while it suggests that the technology was public, it does not state so explicitly.
Reference F:
On March 17, 2021, Fish Farming Expert reported “Mowi unveils its digital farming future” (retrieved from https://www.fishfarmingexpert.com/mowi-mowi-40-smart-farming/mowi-unveils-its-digital-farming-future/1283289). The article states that “Mowi today introduced its new aquaculture technological solutions, called Mowi 4.0 Smart Farming, at its online Capital Markets Day.” That this is geared to investors (i.e., is from the Capital Markets Day) shows that this is commercially exploited. The article does not discuss areas for research, but instead talks about the commercial advantages (e.g., “clearer economies of scale”). More to the point, that this technology is being presented at a Capital Markets Day means that Mowi is actively displaying the technology to present and potential investors because this technology will increase the value of the company, i.e., it is being commercially exploited.
Reference F:
Mowi’s website for “Capital Markets Day 2021” (dated March 8, 2021, retrieved from https://mowi.com/news/capital-markets-day-2021/) also discusses the roll out of this technology (referred to as “Mowi 4.0 Smart Farming, same as with the Fish Farming Expert article). The article states:
The ongoing implementation of Smart Farming technologies in Mowi Farming is expected to have a positive impact not only on productivity and costs, but also on fish welfare and sustainability. Farming Norway leads the way within “Mowi 4.0 Smart Farming” and by 2025 expects to have completed the roll-out of Smart Farming technologies in its largest farming unit.
Reference H:
Mowi’s Capital Markets Day 2021 Presentation also shows commercial exploitation (March 17, 2021, retrieved from https://mowi.com/wp-content/uploads/2021/03/MOWI-CMD-2021-final.pdf. The examiner notes that Mowi’s Investor Presentations page currently links to a version of this document from June of 2021, but the discussion herein is limited to the version from March 2021.)
Slide 51 states “Several farms in commercial validation phase.”
Slide 51 also includes a map of Norway with the title “Intelligent sensor systems deployed.” The legend for the map states that there are 13 “Sea sites with sensor technology” and 97 “Pens with sensor technology.” There is also a photo from one of the pens that is annotated with boxes illustrating what the machine learning has recognized.
Comparison with Current Application
The current application is titled “Distribution-Based Machine Learning.” Reference B discloses “Soon we had a model capable of making highly precise and accurate estimates of fish weight distributions for the entire population within a given enclosure.”
Specification, [0005] “A solution described in this specification includes techniques to enable the use of images from actual environments in training data by using fish population data as ground truth data instead of individual fish measurements. The solution described herein can generate a trained model that is configured to predict weight of individual fish without being trained using training data that uses weight of individual fish.”
Reference B: “The moment of truth arrived two months later, when our demo software successfully estimated fish weights from images alone. It was a breakthrough, a validation of our vision, and yet only the first step on a multiyear journey of technology development.” The examiner notes that “two months later” refers to the trip in 2018.
Specification, [0006] “Fish population data can include one or more values that represent a distribution of a fish population, such as a population that has been sorted, harvested, or otherwise processed. Because population based metrics are already obtained for other purposes, their use can improve training data generation efficiency.”
Reference B: “A second breakthrough came when we got access to data from the fish farms’ harvests, when every fish is individually weighed.”
Specification, [0008] “In some implementations, a model being trained generates a predicted weight for multiple fish. For example, a model can generate a predicted weight using input data such as an image of a fish or extracted data, such as key points on a detected fish or truss lengths between key points.”
Reference H, slide 51 (enlarged):
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The examiner notes that the boxes and line segments connecting dots are in color in the original. The examiner further notes the similarity between this image and that from Reference B. The examiner also notes that Reference E includes a matching image.
Specification, [0010] “One innovative aspect of the subject matter described in this specification is embodied in a method that includes obtaining fish images from a camera device; generating predicted values using a machine learning model and one or more of the fish images; comparing the predicted values to distribution data representing features of multiple fish; and updating one or more parameters of the machine learning model based on the comparison.”
Reference B: Still, that early trip armed us with our first 1,000 fish data points and a growing library of underwater images (since then, our datasets have grown by a factor of several million). That first data collection allowed us to meticulously train our first AI models to discern patterns invisible to the human eye. The moment of truth arrived two months later, when our demo software successfully estimated fish weights from images alone.
Reference B’s discussion of training models corresponds to the specification’s updating parameters based on the comparison.
Conclusions
MPEP 2133.03(a)(I) explains that commercial exploitation is a type of public use. Here, Mowi was commercially exploiting the invention, such as by using it in its sea sites and its pens to raise fish that it sold. Further, it advertised this technology at its Capital Markets Day, which also furthers Mowi’s commercial ambitions. Additionally, Mowi described the activity as “commercial validation” on more than one occasion.
MPEP 2133.03(a)(II)(A) states that where commercial exploitation occurs (as here), secret uses are also available as prior art. For example, if the software being used performed a certain calculation that is now claimed, but the calculation was not disclosed, that the software was commercially exploited renders the calculation prior art.
MPEP 2133.03(a)(II)(A)(2) is titled “Even If the Invention Is Hidden, Inventor Who Puts Machine or Article Embodying the Invention in Public View Is Barred from Obtaining a Patent as the Invention Is in Public Use.” Mowi’s “sea sites” are understood to be public because they are in public waters (whereas the “pen” sites appear to be private). Therefore, to the extent that this invention was hidden, it is still prior art as it was embodied in public view (see, e.g., the photos in Reference B).
MPEP 2133.03(b)(II) discusses that offers for sale also count as on sale prior art, it is not just products that were actually sold. That said, Mowi actually sold the fish from the pens and sea sites. See, e.g., MPEP 2133.03(c)(III) “However, sale of a product made by the claimed process by the patentee or a licensee would constitute a sale of the process within the meaning of pre-AIA 35 U.S.C. 102(b).” (Helsinn found that pre-AIA law is applicable here.)
Mowi was commercially exploiting the presently disclosed technology not later than March 18, 2021, i.e., more than one year prior to the earliest asserted priority date. To the extent that there are differences between Mowi’s public disclosures and the claims, any differences are inherent (e.g., are disclosed by secret prior art).
The above “Comparison with the Current Invention” shows that the commercially exploited technology is at least substantially identical to the currently claimed invention. Therefore, the burden of production shifts to Applicant. MPEP 2112(V).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kandimalla V, Richard M, Smith F, Quirion J, Torgo L, Whidden C. Automated detection, classification and counting of fish in fish passages with deep learning. Frontiers in Marine Science. 2022 Jan 13;8:823173.
Shelby Brown, “Alphabet's moonshot to save the oceans starts with a fish cam,” CNET, March 2, 2020, retrieved from https://www.cnet.com/science/alphabets-moonshot-to-save-the-oceans-starts-with-a-fish-cam/.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/DAVID ORANGE/Primary Examiner, Art Unit 2663