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 .
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 abstract idea without significantly more.
The claim(s) recite(s) “A method for predicting whether a user executed a golf shot, the method comprising: receiving a selection of a machine learning model from a plurality of machine learning models, each of the plurality of machine learning models being trained to predict whether the golf shot occurred; receiving inputs relevant to the machine learning model that was selected; and predicting, using the machine learning model that was selected, whether the user executed the golf shot using the inputs relevant to the machine learning model that was selected.” (Claim 1); “A system comprising: a memory comprising computer readable instructions; and at least one processor for executing the computer readable instructions, the computer readable instructions controlling the at least one processor to perform operations for predicting whether a user executed a golf shot, the operations comprising: receiving a selection of a machine learning model from a plurality of machine learning models, each of the plurality of machine learning models being trained to predict whether the golf shot occurred; receiving inputs relevant to the machine learning model that was selected; and predicting, using the machine learning model that was selected, whether the user executed the golf shot using the inputs relevant to the machine learning model that was selected” (Claim 19); “A non-transitory computer-readable medium comprising instructions, wherein execution of the instructions by at least one processor causes the at least one processor to perform operations for predicting whether a user executed a golf shot, the operations comprising: receiving a selection of a machine learning model from a plurality of machine learning models, each of the plurality of machine learning models being trained to predict whether the golf shot occurred; receiving inputs relevant to the machine learning model that was selected; and predicting, using the machine learning model that was selected, whether the user executed the golf shot using the inputs relevant to the machine learning model that was selected.” (Claim 20). Each of the above underlined portions are related to an abstract idea Mental Processes particularly concepts performed in the human mind (including an observation, evaluation, judgment, opinion). In this case, steps of “receiving inputs; and predicting, whether the user executed the golf shot using the inputs (Claim 1); “receiving inputs; and predicting, whether the user executed the golf shot using the inputs” (Claim 19); “receiving inputs; and predicting, whether the user executed the golf shot using the inputs” (Claim 20) pertain to concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
This judicial exception is not integrated into a practical application because the claimed invention merely applies the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform the abstract idea (MPEP 2106.05 (f)) and/or generally links the use of the judicial exception to a particular technology or field of use (particularly the technological environment of a gaming device and/or gaming system) (MPEP 2106.05 (h)). The claimed computer components (“machine learning model”, “system”, “memory”, “processor”, and/or “non-transitory computer-readable medium”) are recited at a level of generality and are merely invoked as a tool to perform the abstract idea. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because no element or combination of elements is sufficient to ensure any claim of the present application as a whole amounts to significantly more than one or more judicial exceptions, as described above. The recitations of utilization of “machine learning model”, “system”, “memory”, “processor”, and/or “non-transitory computer-readable medium” are recited at a level of generality and are merely invoked as tool to perform the used to apply the abstract idea merely implements the abstract idea at a low level of generality and fail to impose meaningful limitations to impart patent-eligibility (the use of a computing device and/or generic components is merely illustrating the environment in which the abstract idea is practiced). These elements and the mere processing of data using these elements do not set forth significantly more than the abstract idea itself applied on general purpose computing devices. Taking the physical elements individually and in combination, the computer-based components perform purely generic computer-based functions that are silent in regards to clearly indicating how a computer aids method, system, and/or medium or to which a computer performs/implements the method, system, and/or medium. The recited generic elements are a mere means to implement the abstract idea. Thus, they cannot provide the “inventive concept” necessary for patent-eligibility. “[I]f a patent’s recitation of a computer amounts to a mere instruction to ‘implement]’ an abstract idea ‘on ... a computer, ’... that addition cannot impart patent eligibility.” Alice, 134 S. Ct. at 2358 (quoting Mayo, 132 S. Ct. at 1301). As such, the significantly more required to overcome the 35 U.S.C. 101 hurdle and transform the claimed subject matter into a patent-eligible abstract idea is lacking. Accordingly, the claims are not patent-eligible.
Additionally, as it pertains to “receiving a selection of a machine learning model from a plurality of machine learning models, each of the plurality of machine learning models being trained… using the machine learning model that was selected” found in Claim 1 and similarly in Claims 19-20, features are well-known in the art. Stivoric (US 2007/0100666) teaches it conventional in the art to use machine learning models trained from collected data that could be used to predict the activity of a user (¶ 113).
It is settled law that adding physical elements to an abstract idea will not amount to an “inventive concept" if the physical elements are well-known, routine and conventional elements and they perform their well-known, routine and conventional functions. TLI Communications LLC v. AV Automotive, L.L.C. (Fed Cir 2016):
Turning to the second step in our analysis, we find that the claims fail to recite any elements that individually or as an ordered combination transform the abstract idea of classifying and storing digital images in an organized manner into a patent-eligible application of that idea. It is well-settled that mere recitation of concrete, tangible components is insufficient to confer patent eligibility to an otherwise abstract idea. Rather, the components must involve more than performance of “‘well understood, routine, conventional activit[ies]’ previously known to the industry.” Alice, 134 S. Ct. at 2359 (quoting Mayo, 132 S.Ct. at 1294). We agree with the district court that the claims’ recitation of a “telephone unit,” a “server”, an “image analysis unit,” and a “control unit” fail to add an inventive concept sufficient to bring the abstract idea into the realm of patentability. (Emphasis added by Examiner.)
On the question of preemption, the Federal Circuit has stated in Ariosa Diagnostics, Inc., V. Sequenom, Inc., (Fed Cir. June 12, 2015):
The Supreme Court has made clear that the principle of preemption is the basis for the judicial exceptions to patentability. Alice, 134 S. Ct at 2354 (“We have described the concern that drives this exclusionary principal as one of pre-emption”). For this reason, questions on preemption are inherent in and resolved by the § 101 analysis. The concern is that “patent law not inhibit further discovery by improperly tying up the future use of these building blocks of human ingenuity.” Id. (internal quotations omitted). In other words, patent claims should not prevent the use of the basic building blocks of technology—abstract ideas, naturally occurring phenomena, and natural laws. While preemption may signal patent ineligible subject matter, the absence of complete preemption does not demonstrate patent eligibility. In this case, Sequenom’s attempt to limit the breadth of the claims by showing alternative uses of DNA outside of the scope of the claims does not change the conclusion that the claims are directed to patent ineligible subject matter. Where a patent’s claims are deemed only to disclose patent ineligible subject matter under the Mayo framework, as they are in this case, preemption concerns are fully addressed and made moot. (Emphasis added.)
Nor do the dependent claims 2-18 add “significantly more” since they merely add to the claimed concepts relating to concepts performed in the human mind (including an observation, evaluation, judgment, opinion). The dependent claims failing to place the claimed invention into a practical applicant or additional generic components of the dependent claims failing to amount to “significantly more” for the same reasons noted above.
Consideration of each and every element of each and every claim, both individually and as an ordered combination, leads to the conclusion that the claim are not patent-eligible under 35 USC §101.
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.
Claim(s) 1, 7, 14, and 16-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nuesmeyer (2016/0354671).
Claims 1 and 19-20: Nuesmeyer discloses a system comprising: a memory (non-transitory computer-readable medium) comprising computer readable instructions; and at least one processor for executing the computer readable instructions, the computer readable instructions controlling the at least one processor (¶ 20-23, 45-52, 111-117) to perform operations (perform a method) for predicting whether a user executed a gold shot, the operations comprising (the method comprising): receiving a selection of a machine learning model from a plurality of machine learning models (swing detection classifier and/or contact detection classifiers), each of the plurality of machine learning models being trained to predict whether the golf shot occurred (¶ 52-56, 80-91); receiving inputs relevant to the machine learning model that was selected; and predicting, using the machine learning model that was selected, whether the user executed the golf shot using the inputs relevant to the machine learning model that was selected (¶ 52-56, 80-91, 124).
Claim 7: Nuemeyer discloses wherein the selection of the machine learning model is based at least in part on a position of the user relative to a hole on a golf course (¶ 55).
Claim 14: Nuemeyer discloses wherein the inputs relevant to the machine learning model that was selected comprise at least a swing detection from a watch swing model, the machine learning model that was selected being trained to take as input the swing detection from the watch swing model whether the user executed the golf shot (¶ 20, 45-52, 80-91).
Claim 16: Nuemeyer discloses wherein the predicting comprises generating a prediction value and comparing the prediction value to a threshold (¶ 81-82).
Claim 17: Nuemeyer discloses wherein it is determined that the user executed the golf shot responsive to the prediction value satisfying the threshold (¶ 81-82).
Claim 18: Nuemeyer discloses wherein it is determined that the user did not execute the golf shot responsive to the prediction value failing to satisfy the threshold (¶ 81-82).
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 (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 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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 2-3 and 5-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nuesmeyer (2016/0354671) in view of Bentley (US 2012/0088544).
Claim 2: Nuesmeyer teaches the above, but lacks explicitly suggesting determining whether the user was stationary long enough to potentially hit the golf shot. Nuesmeyer at least teaches that variations of the invention are possible (¶ 127-128) and teaches manual input of scoring (¶ 2, 34, 61, 63). Furthermore, an analogous art of Bentley teaches determining whether the user was stationary long enough to potentially hit the golf shot (Figs. 44-45, ¶ 151-153, - “If the mobile computer is stationary for a threshold T amount of time at 4404, then the mobile computer may either optionally determine if the mobile computer has rotated or moved in a manner that is indicative of a golf swing or putt at 4405, or simply wait until the mobile computer has moved from the current position at 4406 for example, which occurs once a golfer has finished a shot or putt”) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Nuesmeyer with the determining means of Bentley because such a modification would have yielded predictable results, namely, a means of allowing a user to manually input a scoring event in which at least Nuesmeyer is intended (see above). Such a modification allows the mobile device to intelligently determine whether to query a golfer to count a shot and to records shots that are so designated.
Nuesmeyer in view of Bentley fails to teach the determining step occurring prior to receiving the selection of the machine learning model. However, applicant fails to disclose determining whether the user was stationary long enough to potentially hit the golf shot prior to receiving the selection of the machine learning model solve any stated problem, provides an advantage, or is for any particular purpose. Furthermore, Applicant discloses that “One of ordinary skill in the art will recognize that exemplary methods may include more or fewer steps than those illustrated in the exemplary flowcharts, and that the steps in the exemplary flowcharts may be performed in a different order than the order shown in the illustrative flowcharts”. Moreover, it appears that the determining means of Nuesmeyer in view of Bentley, or applicant’s invention, would perform the same function of determining whether the user was stationary long enough to potentially hit the golf shot, regardless of the order of which it occurs. Therefore, it would have been prima facie obvious to modify Nuesmeyer in view of Bentley to obtain the invention as specified in claim 2 because such a modification would have been considered a mere design consideration which fails to patentably distinguish over the prior art of Nuesmeyer in view of Bentley.
Claim 3: Nuesmery in view of Bentley teaches wherein the determining is performed by comparing a time the user was stationary to a threshold, the threshold being based on information about the user (Step 4403) and information about a golf course (Step 4402) (Bentley - ¶ 151-153).
Claim 5: Nuesmery in view of Bentley teaches responsive to determining that the user was stationary long enough to potentially hit the golf shot, determining that no golf shot occurred (Bentley - ¶ 151-153, Step 4408).
Claim 6: Nuesmery in view of Bentley teaches prior to determining whether the user was stationary long enough to potentially hit the golf shot, receiving at least one of course information and user positional data (Steps 4402-4403)(Bentley - ¶ 151-153).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nuesmeyer (2016/0354671) in view of Wiegers (US 2009/0298605).
Claim 8: Nuesmeyer teaches the above, but lacks explicitly suggesting wherein the inputs relevant to the machine learning model that was selected comprise at least user profile information for the user, the machine learning model that was selected being trained to take as input the user profile information for the user and to predict whether the user executed the golf shot. Nuesmeyer at least teaches that variations of the invention are possible (¶ 127-128) and that predicting whether the user executed the golf shot can employ any suitable machine-learning approach (¶ 91). Furthermore, an analogous art of Weigers teaches using user profile to predict a golf shot (¶ 3, 93-96, Claims 1-4). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the input means of Nuesmeyer to include the user profile means of Weigers because such a modification would have yielded predictable results namely providing inputs (data) such that a golf shot can be predicted in which at least Nuesmeyer is intended. Such a modification allowing the prediction of future golf swing results (Wiegers – Claim 4).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nuesmeyer (2016/0354671) in view of Beno (US 2012/0316843).
Claim 9: Nuesmeyer teaches the above, but lacks explicitly suggesting wherein the inputs relevant to the machine learning model that was selected comprise at least positional and hole history information, the machine learning model that was selected being trained to take as input the positional and hole history information and to predict whether the user executed the golf shot. Nuesmeyer at least teaches that variations of the invention are possible (¶ 127-128) and that predicting whether the user executed the golf shot can employ any suitable machine-learning approach (¶ 91). Furthermore, an analogous art of Beno teaches providing inputs to machine learning models including positional (¶ 30) and hole history (¶ 42) information to predict future information (¶ 30-43). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the input means of Nuesmeyer to include the positional and hole history information means of Beno because such a modification would have yielded predictable results namely providing inputs (data) such that a golf shot can be predicted in which at least Nuesmeyer is intended. Such a modification allowing for the prediction of future information such as golf shot trajectory (Beno - ¶ 43).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nuesmeyer (2016/0354671) in view of Hadden (US 2014/0278207).
Claim 12: Nuesmeyer teaches the above, in addition to wherein the inputs relevant to the machine learning model that was selected comprise at least audio hit information, the machine learning model that was selected being trained to take as input the audio hit information and to predict whether the user executed the golf shot (¶ 48, 54, 81, 88-90), but lacks explicitly suggesting the audio hit information being audio hit probability information. Nuesmeyer at least teaches that variations of the invention are possible (¶ 127-128) and that predicting whether the user executed the golf shot can employ any suitable machine-learning approach (¶ 91). Furthermore, an analogous art of Hadden teaches using audio hit probability information to determine or predict a golf shot (¶ 61, 88, 94-96, emphasis on ¶ 95). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the input means of Nuesmeyer to include the audio hit probability information of Hadden because such a modification would have yielded predictable results namely providing inputs (data) such that a golf shot can be predicted in which at least Nuesmeyer is intended. Such a modification allowing for the prediction/determination of characteristics of a user’s golf swing (Hadden - ¶ 5).
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nuesmeyer (2016/0354671) in view of Manwaring (US 6,506,124).
Claim 13: Nuesmeyer teaches the above, but lacks explicitly suggesting wherein the inputs relevant to the machine learning model that was selected comprise at least head movement data, the machine learning model that was selected being trained to take as input the head movement data and predict whether the user executed the golf shot. Nuesmeyer at least teaches that variations of the invention are possible (¶ 127-128) and that predicting whether the user executed the golf shot can employ any suitable machine-learning approach (¶ 91). Furthermore, an analogous art of Manwaring teaches using inputs including head movement data to predict a golfer’s ball striking performance (Col. 3:25-41, Col. 4:24-35, Col. 5:54-59, Claims 20-21). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the input means of Nuesmeyer to include the head movement data of Manwaring because such a modification would have yielded predictable results namely providing inputs (data) such that a golf shot can be predicted in which at least Nuesmeyer is intended. Such a modification provides a means to predict a golfer’s ball striking performance (Manwaring – Col. 2:25-30).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Please see attached PTO-892.
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/TRAMAR HARPER/Primary Examiner, Art Unit 3715
