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 .
Response to Amendment
The examiner acknowledges applicant’s arguments in the Response dated November 18, 2025 directed to the Non-Final Office Action dated August 18, 2025. Claims 1-5, 7-10, 12-18, and 20-23 are pending in the application and subject to examination as part of this office action.
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 1-5, 7-10, 12-18, and 20-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to non-statutory subject matter because the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. Each of claims 1-20 has been analyzed to determine whether it is directed to any judicial exceptions.
The determination of subject matter eligibility under 35 USC 101, relies on the Mayo/Alice two-step analysis.
In step 1 of the analysis, the claims are evaluated to determine whether they fall within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter). In the present case, claims 1-12 are directed to a method (i.e., a process) and claims 1-5, 7-10, 12-18, and 20-23 are directed to a system (i.e., a machine). The claims are, therefore directed to one of the four statutory categories.
Under prong 1 of step 2A, the examiner is directed to determine whether the claim recites a judicial exception. The claims are compared to groupings of subject matter that have been found by courts as abstract ideas. These groupings include
(a) Mathematical concepts—mathematical relationships, mathematical formulas or equations, mathematical calculations;
(b) Certain methods of organizing human activity—fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
(c) Mental processes—concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 1 recites (the abstract idea is underlined) a method comprising:
presenting, via an output device at a gaming table during an evaluation period, messages related to a game feature available at one or more participant stations at the gaming table;
detecting, for the evaluation period by an electronic processor based on analysis of images of the gaming table by one or more machine learning models, gaming activity associated with the game feature, wherein detecting the gaming activity comprises transforming image features of playing cards via the one or more machine learning models to determine game outcome data;
determining, in response to a comparison of message data to the determined game outcome data by the electronic processor, a statistical correlation between the presenting of the messages and the detected gaming activity; and
computing, by the electronic processor based on the statistical correlation, a message effectiveness score for one or more of the messages in relation to the game feature.
Claim 13 recites (the abstract idea is underlined) a gaming system comprising:
one or more image sensors, wherein the one or more image sensors are configured to capture images at a gaming table; and
an electronic processor configured to execute instructions, which when executed cause the gaming system to perform operations to:
present, via an output device at the gaming table, messages related to a game feature available at the gaming table;
detect, based on analysis of the images by one or more machine learning models, gaming activity associated with the game feature, wherein detecting the gaming activity comprises transforming image features of playing cards via the one or more machine learning models to determine game outcome data;
determine a correlation between a timing of the presenting of the messages and a timing of the detected gaming activity, wherein the correlation is based on a comparison of message data to the determined game outcome data; and
determine, based on the correlation, a message effectiveness score for one or more of the messages in relation to the game feature.
Claim 21 recites (the abstract idea is underlined) a non-transitory computer-readable storage medium storing instructions that, when executed by an electronic processor, cause the electronic processor to perform operations comprising:
presenting, via an output device at a gaming table during an evaluation period, messages related to a game feature available at one or more participant stations at the gaming table;
detecting, for the evaluation period based on analysis of images of the gaming table by one or more machine learning models, gaming activity associated with the game feature, wherein the detecting comprises:
transforming, by the one or more machine learning models, symbol features of images of playing cards dealt to the one or more participant stations;
detecting, based on the transforming, symbols on the playing cards;
comparing the detected symbols to symbols for a known rank and suit of the playing cards; and
determining, based on the comparing of the known rank and suit to outcome criteria, one or more game outcomes associated with the one or more participant stations;
determining, in response to a comparison of message data to the determined one or more game outcomes, a statistical correlation between the presenting of the messages and the detected gaming activity; and
computing, based on the statistical correlation, a message effectiveness score for one or more of the messages in relation to the game feature.
The present claims are directed to a method of computing a message effectiveness score for a message effectiveness score for one or more of the messages in relation to a game feature. These steps fall under the category of mental processes because they can be performed in the human mind. Additionally, the steps fall into the category of certain methods of organizing human activity. Specifically, the steps fall into the sub-category of commercial or legal interactions because the limitations are directed to computing a message effectiveness score of one or more messages, which is advertising, marketing or sales activities or behaviors. Accordingly, the claim recites an abstract idea.
Under prong 2 of Step 2A, the examiner considers whether additional elements integrate the abstract idea into a practical application. To do so, the examiner looks to the following exemplary considerations, looking at the elements individually and in combination:
• an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
• an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (not considered relevant to the present claims);
• an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
• an additional element effects a transformation or reduction of a particular article to a different state or thing; and
• an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
The additional elements in the present claims are an output device, a gaming table, one or more machine learning models, one or more participant stations, an electronic processor, playing cards, one or more betting tokens, one or more bet zones, one or more image sensors. The additional elements do no integrate the judicial exception into a practical application. In particular, the additional elements do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field. The additional elements do not implement a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim. The additional elements do not effect a transformation or reduction of a particular article to a different state or thing. The additional elements do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they does not impose any meaningful limits on practicing the abstract idea.
Under step 2B, the examiner evaluates whether the additional elements amount to significantly more than the judicial exception itself. The examiner considers if the additional elements:
• add a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
• simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The present claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are well-understood, routine, or conventional, as shown:
an output device (Tedesco et al., US 2008/0248865 A1, for gaming devices, common output devices include a cathode ray tube (CRT) monitor on a video poker machine, a bell on a gaming device (e.g., rings when a player wins), an LED display of a player's credit balance on a gaming device, an LCD display of a personal digital assistant (PDA) for displaying keno numbers [0120]);
one or more machine learning models (Cohen et al., US 9,498,704 B1, a wide variety of well-known analytic and machine-learning techniques can be applied to create predictive models [C15:14-55]); (Aman et al., US 2019/0143204 A1, the present inventor anticipates that the object tracking systems described both herein and in the prior related applications are capable of detecting these theme related products such as clothing and toys using well-known imaging analysis including now popular machine learning algorithms implementing for example deep-neural nets, where the detected type of clothing or toy is used at least in part to determine how the interactive gaming system responds to an individual gamer [0019]);
a gaming table, one or more participant stations, one or more bet zones (Santoro, US 2017/0209776 A1, the table 12, as is well known in the art, includes a top that is essentially semi-circular having a straight side 14 where a dealer is normally positioned; the curved side 16 includes six player positions such as shown [0014]); (Czyzewski et al., US 2008/0113783 A1, FIG. 1 shows a portion of a conventional casino table 10 suitable for playing baccarat; the table 10 includes a card shoe 12, player hand positions 14, 16, banker hand positions 18, 20 and three player wagering positions 22, 24, 26; each player wagering position 22, 24, 26 includes a position P for wagering on the player hand (comprising cards dealt to the player hand positions 14, 16), a position B for wagering on the banker hand (comprising cards dealt to the player hand positions 14, 16) and a position T for wagering that there will be a tie (also known as a standoff) between the player and banker hands [0007]);
an electronic processor (Walker et al., US 2003/0218303 A1,. well-known examples of gaming devices include, without limitation, video poker machines, video blackjack machines, mechanical slot machines, video slot machines, video keno machines, video bingo machines, pachinko machines, and video lottery terminals. Other well-known examples of gaming devices include, without limitation: table controllers, such as the table controller 92 (FIG. 5); game tables, such as virtual Blackjack table 150 (FIG. 9); and player terminals, such as those described in implementing virtual Blackjack table 150 (FIG. 9) [0176]);
one or more betting tokens (Panambur et al., US 2016/0093165 A1, gaming tokens are well known [0003]);
one or more image sensors, playing cards (Isso et al., US 11,127,263 B1, the camera 670 may be trained to capture images of the card faces, chips, and chip stacks on the surface of the gaming table and perform card recognition routines to identify the card, rank, and suit, which is well known in the art [C15:3-18]).
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
As a result, the claims are not directed to patent eligible subject matter.
Prior Art
There are currently no prior art rejections against claims 1-5, 7-10, 12-18, and 20-23.
Response to Arguments
Applicant's arguments filed November 18, 2025 have been fully considered but they are not persuasive.
With respect to the rejections under 35 USC 101, applicant argues that claim 1 is eligible under Thales Visonix (Response [p. 11]). In particular, applicant argues that using sensors to capture raw image data of a gaming table and use machine learning to transform the raw data into a specific determination of the physical game outcome is a specific sensor-processing pipeline that transforms pixel data into a meaningful physical state that is then used to validate a digital message (Response [p. 11]).
The examiner disagrees with applicant’s conclusion.
The examiner considers “transforming image features of playing cards via the one or more machine learning models to determine game outcome data” part of the abstract idea rather than an additional element.
However, if “transforming image features of playing cards via the one or more machine learning models to determine game outcome data” is considered an additional element, the examiner refers to MPEP 2106.05(c). According to MPEP 2106.05(c), where a transformation is recited in a claim the following factors are relevant to the analysis:
The particularity or generality of the transformation
The degree to which the recited article is particular
The nature of the transformation in terms of the type or extent of change in state or thing
The nature of the article transformed
Whether the transformation is extra-solution activity or a field-of-use (i.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps).
In the present instance, the “transforming image features of playing cards via the one or more machine learning models to determine game outcome data” limitation is broadly stated lacking particularity. “Image features” are transformed using undisclosed steps performed via a generic “one or more machine learning models”.
MPEP 2106.05(c) states:
1. The particularity or generality of the transformation. According to the Supreme Court, inventions comprising processes of "‘tanning, dyeing, making waterproof cloth, vulcanizing India rubber [or] smelting ores’ . . . are instances . . . where the use of chemical substances or physical acts, such as temperature control, changes articles or materials [in such a manner that is] sufficiently definite to confine the patent monopoly within rather definite bounds." Gottschalk v. Benson, 409 U.S. 63, 70, 175 USPQ 673, 676 (1972) (discussing Corning v. Burden, 15 How. (56 U.S.) 252, 267-68 (1854)). Therefore, a more particular transformation would likely provide significantly more.
The “transforming” described in the present claims is not particular enough to provide significantly more.
Additionally, MPEP 2106.05(c) states:
5. Whether the transformation is extra-solution activity or a field-of-use (i.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps). A transformation that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more (or integrate a judicial exception into a practical application). For example, in Mayo the Supreme Court found claims regarding calibrating the proper dosage of thiopurine drugs to be patent ineligible subject matter. The Federal Circuit had held that the step of administering the thiopurine drug demonstrated a transformation of the human body and blood. Mayo, 566 U.S. at 76, 101 USPQ2d at 1967. The Supreme Court disagreed, finding that this step was only a field-of-use limitation and did not provide significantly more than the judicial exception. Id. See MPEP § 2106.05(g) & (h) for more information on insignificant extra-solution activity and field of use, respectively.
The examiner does not consider the “transforming” to impose meaningful limits on the execution because it contributes only nominally or significantly to the execution of the claimed method, more along the lines of data gathering.
With respect to the “one or more image sensors”, the “one or more image sensors” appear to be generic computer components that capture images. The one or more image sensors do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field. The one or more image sensors do not implement a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim. The one or more image sensors do not effect a transformation or reduction of a particular article to a different state or thing. The one or more image sensors do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
As such, the examiner does not agree that the “transforming” transforms the abstract idea into a particular application or recites significantly more.
Applicant also argues:
Under Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016), claims directed to an improvement in the functioning of the computer itself are eligible. A generic computer cannot "see" a winning blackjack hand; it can only store pixels. By implementing the claimed machine learning model to "transform image features," claim 1 enables a computing system to autonomously verify physical events (outcomes) to validate digital data (message effectiveness). This turns the computing system into a special-purpose device capable of semantic understanding of visual gaming data, improving the computing system's ability to function as an automated tracking system. (Response [pp. 11-12])
The additional elements in the present claims are an output device, a gaming table, one or more machine learning models, one or more participant stations, an electronic processor, playing cards, one or more betting tokens, one or more bet zones, one or more image sensors. The only alleged improvement is that the generic computer components carry out the abstract idea. The generic computer components are not improved.
In Enfish, the Court asked whether the claims are directed to an improvement to computer functionality versus being directed to an abstract idea. The plain focus of the claims was on an improvement to computer functionality itself, not on economic or other tasks for which a computer is used in its ordinary capacity. The Court found that the claims are directed to a specific improvement to the way computers operate. The Court’s conclusion that the claims were directed to an improvement of an existing technology was bolstered by the specification’s teachings that the claimed invention achieves other benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements.
In the present claims, applicant’s specification states “According to one aspect of the present disclosure, a gaming system is provided for determining an effectiveness of one of more messages based on machine-learning analysis of images of a gaming environment.” (Specification [0008]). The examiner interprets this as an economic task for which the computer is used in its ordinary capacity.
Finally, applicant argues
Claim 21 is directly analogous to the claims found eligible in McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299 (Fed. Cir. 2016). In McRO, the claims recited a specific set of rules (morph weights) to automate 3D lip-synchronization-a task previously performed by humans using subjective judgment. The court held the claims eligible because they did not claim the result (animation), but the specific genus of rules (processing phonemes/vectors) to achieve it. Similarly, Claim 21 claims the specific rules (machine learning transformation of symbol features) to automate the detection of gaming outcomes. A human identifying a card uses visual cognition; a human does not "transform symbol features" of a digital image file. The claim recites a specific technological process that automates a task (verifying outcomes for effectiveness scores) in a way a human cannot perform.
In McRO, the additional elements were sufficient to overcome the abstract idea (mathematical function) by reflecting an improvement in the functioning of a computer, or an improvement to other technology or technical field.
In the present claims, the combination of the additional elements is no more than using generic computing components to apply the judicial exception, adding insignificant extra-solution activity to the judicial exception and generally linking the judicial exception to a particular technological environment or field of use. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
As a result, the claims are not directed to patent eligible subject matter.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WERNER G GARNER whose telephone number is (571)270-7147. The examiner can normally be reached M-F 7:30-15:30 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, DAVID LEWIS can be reached at (571) 272-7673. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WERNER G GARNER/ Primary Examiner, Art Unit 3715