CTNF 18/231,064 CTNF 92068 DETAILED ACTION This office action is responsive to the above identified application filed 8/7/2023. The application contains claims 1-20, all examined and rejected. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Information Disclosure Statement The Information Disclosure Statement with references submitted 8/7/2023, 11/11/2024, and 4/8/2026, have been considered and entered into the file. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-16, 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claim 1 is rejected under 35 USC 101 because the claimed inventions are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. While independent claims 1, 10 and 17 are each directed to a statutory category, Claims 1, and 10 appears to be directed to an abstract idea (mental process). Claims 1-16, 18-20 are rejected under 35 U.S.C. § 101 because the instant application is directed to non-patentable subject matter. Specifically, the claims are directed toward at least one judicial exception without reciting additional elements that amount to significantly more than the judicial exception. The rationale for this determination is in accordance with the guidelines of USPTO, applies to all statutory categories, and is explained in detail below. When considering subject matter eligibility under 35 U.S.C. 101, (1) it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, (2a) it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so (2b), it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include certain methods of organizing human activities; a mental processes; and mathematical concepts, (2019 PEG) STEP 1. Per Step 1, the claims are determined to include process, and machine as in independent Claim 1, 10, and 17, and in the therefrom dependent claims. Therefore, the claims are directed to a statutory eligibility category. At step 2A, prong 1, The invention is directed to identifying features within received data that could be an indication of the probability of occurrence of a machine failure based on analyzed historic data which is akin to Mental Process (see Alice), As such, the claims include an abstract idea. When considering the limitations individually and as a whole the limitations directed to the abstract idea are: Claim 1 “generate an artificial intelligence (AI) prompt, based at least in part on the one or more dynamic context signals”; (Mental process, observation, evaluation and judgment) Claim 10 “generating a first artificial intelligence (AI) prompt including the dynamic context signal” (Mental process, observation, evaluation and judgment); “generating a second AI prompt based at least in part on the augmented context signal” (Mental process, observation, evaluation and judgment). Claim 18 “generating a first query based on the dynamic context signal; executing the first query against a database of images” , “generating a second query based on the updated dynamic context signal“, “executing the second query against the database” (Mental process, observation, evaluation and judgment). Claim 19 “generating a first artificial intelligence (AI) prompt including the dynamic context signal”, “generating a second artificial intelligence (AI) prompt including the updated dynamic context signal” (Mental process, observation, evaluation and judgment). Claim 20 “comparing the updated context signal with the initially extracted context signal to determine that the updated context signal changed from the initially extracted context signal” (Mental process, observation, evaluation and judgment). The claims recites additional elements as Claim 1 “A computing device for generating context-aware, dynamic visualizations, the device comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the device to perform operations comprising:” (“Using a computer as a tool to perform a mental process”, MPEP 2106.04(a)(2)(III)(C), merely indicates a field of use or technological environment in which the judicial exception is performed and fails to add an inventive concept to the claims. See MPEP 2106.05(h)); “extract one or more dynamic context signals”, “provide the generated AI prompt as input to a generative AI model; in response to providing the AI prompt as input, receive an output payload from the generative AI model including the visualization”, “cause a display of the visualization as part of a user interface of an application or an operating system operating on the computing device” (insignificant extra-solution activity, MPEP 2106.05(g)). Claim 10 “A computer-implemented method for generating context-aware, dynamic visualizations, the method comprising” (“Using a computer as a tool to perform a mental process”, MPEP 2106.04(a)(2)(III)(C), merely indicates a field of use or technological environment in which the judicial exception is performed and fails to add an inventive concept to the claims. See MPEP 2106.05(h)); “extracting a dynamic context signal”, “ providing the first AI prompt as input to a first generative AI model; in response to providing the first AI prompt as input, receiving an output payload from the first generative Al model including an augmented context signal”, “providing the second AI prompt as input to a second generative AI model; in response to providing the second AI prompt as input, receiving an output payload from the second generative AI model including a visualization; and causing a display of the visualization in at least one of a user interface of an application or an operating system operating on a computing device” (insignificant extra-solution activity, MPEP 2106.05(g)). Claim 18 “retrieving the first visualization comprises: receiving, in response to the first query, a first image as the first visualization”, “retrieving the second visualization comprises”, “receiving, in response to the second query, a second image as the second visualization” (insignificant extra-solution activity, MPEP 2106.05(g)). Claim 19 “retrieving the first visualization comprises” “providing the first AI prompt as input to a generative AI model” “in response to providing the AI prompt as input, receiving an output payload from the generative AI model including the first visualization”; “retrieving the second visualization comprises”, “providing the second AI prompt as input to the generative AI model”; “in response to providing the AI prompt as input, receiving an output payload from the generative AI model including a second visualization” (insignificant extra-solution activity, MPEP 2106.05(g)). This judicial exception is not integrated into a practical application. The elements are recited at a high level of generality, i.e. a generic computing system performing generic functions including generic processing of data. Accordingly the additional elements do not integrate the abstract into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Therefore the claims are directed to an abstract idea. (2019 Revised Patent Subject Matter Eligibility Guidance ("2019 PEG"). Thus, under Step 2A of the Mayo framework, the Examiner holds that the claims are directed to concepts identified as abstract. STEP 2B. Because the claims include one or more abstract ideas, the examiner now proceeds to Step 2B of the analysis, in which the examiner considers if the claims include individually or as an ordered combination limitations that are "significantly more" than the abstract idea itself. This includes analysis as to whether there is an improvement to either the "computer itself," "another technology," the "technical field," or significantly more than what is "well-understood, routine, or conventional" (WURC) in the related arts. The instant application includes in Claims additional steps to those deemed to be abstract idea(s). When taken the steps individually, these steps are: Claim 1 “A computing device for generating context-aware, dynamic visualizations, the device comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the device to perform operations comprising:” (“Using a computer as a tool to perform a mental process”, MPEP 2106.04(a)(2)(III)(C), merely indicates a field of use or technological environment in which the judicial exception is performed and fails to add an inventive concept to the claims. See MPEP 2106.05(h)); “extract one or more dynamic context signals”, “provide the generated AI prompt as input to a generative AI model; in response to providing the AI prompt as input, receive an output payload from the generative AI model including the visualization”, “cause a display of the visualization as part of a user interface of an application or an operating system operating on the computing device” (Well-Understood, Routine, Conventional Activity, sending, receiving, displaying and processing data are common and basic functions in computer technology, MPEP 2106.05(d)(II)(i)) Claim 10 “A computer-implemented method for generating context-aware, dynamic visualizations, the method comprising” (“Using a computer as a tool to perform a mental process”, MPEP 2106.04(a)(2)(III)(C), merely indicates a field of use or technological environment in which the judicial exception is performed and fails to add an inventive concept to the claims. See MPEP 2106.05(h)); “extracting a dynamic context signal”, “ providing the first AI prompt as input to a first generative AI model; in response to providing the first AI prompt as input, receiving an output payload from the first generative Al model including an augmented context signal”, “providing the second AI prompt as input to a second generative AI model; in response to providing the second AI prompt as input, receiving an output payload from the second generative AI model including a visualization; and causing a display of the visualization in at least one of a user interface of an application or an operating system operating on a computing device” (Well-Understood, Routine, Conventional Activity, sending, receiving, displaying and processing data are common and basic functions in computer technology, MPEP 2106.05(d)(II)(i)). Claim 18 “retrieving the first visualization comprises: receiving, in response to the first query, a first image as the first visualization” (receiving data), “retrieving the second visualization comprises” (receiving data) “receiving, in response to the second query, a second image as the second visualization” (receiving data) (Well-Understood, Routine, Conventional Activity, sending, receiving, displaying and processing data are common and basic functions in computer technology, MPEP 2106.05(d)(II)(i)). Claim 19 “retrieving the first visualization comprises” “providing the first AI prompt as input to a generative AI model” (sending data) “in response to providing the AI prompt as input, receiving an output payload from the generative AI model including the first visualization” (receiving data); “retrieving the second visualization comprises” (receiving data), “providing the second AI prompt as input to the generative AI model” (sending data); “in response to providing the AI prompt as input, receiving an output payload from the generative AI model including a second visualization” (receiving data) (Well-Understood, Routine, Conventional Activity, sending, receiving, displaying and processing data are common and basic functions in computer technology, MPEP 2106.05(d)(II)(i)) In the instant case, Claims 1 and 10, and 18-20 are directed to above mentioned abstract idea. Technical functions such as receiving, and extracting are common and basic functions in computer technology. The individual limitations are recited at a high level and do not provide any specific technology or techniques to perform the functions claimed. In addition, when the claims are taken as a whole, as an ordered combination, the combination of steps does not add "significantly more" by virtue of considering the steps as a whole, as an ordered combination. The instant application, therefore, still appears only to implement the abstract idea to the particular technological environments using what is well-understood, routine, and conventional in the related arts. The steps are still a combination made to the abstract idea. The additional steps only add to those abstract ideas using well understood and conventional functions, and the claims do not show improved ways of, for example, an unconventional non-routine functions for analyzing model operations or updating the model that could then be pointed to as being "significantly more" than the abstract ideas themselves. Moreover, Examiner was not able to identify any "unconventional" steps, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. The instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is well-understood, routine, and conventional (WURC) in the related arts. Further, note that the limitations, in the instant claims, are done by the generically recited computing devices. The limitations are merely instructions to implement the abstract idea on a computing device that is recited in an abstract level and require no more than a generic computing devices to perform generic functions. CONCLUSION It is therefore determined that the instant application not only represents an abstract idea identified as such based on criteria defined by the Courts and on USPTO examination guidelines, but also lacks the capability to bring about "Improvements to another technology or technical field" (Alice), bring about "Improvements to the functioning of the computer itself" (Alice), "Apply the judicial exception with, or by use of, a particular machine" (Bilski), "Effect a transformation or reduction of a particular article to a different state or thing" (Diehr), "Add a specific limitation other than what is well- understood, routine and conventional in the field" (Mayo), "Add unconventional steps that confine the claim to a particular useful application" (Mayo), or contain "Other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment" (Alice), transformed a traditionally subjective process performed by humans into a mathematically automated process executed on computers (McRO), or limitations directed to improvements in computer related technology, including claims directed to software (Enfish). The dependent claims, when considered individually and as a whole, likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. claims 2 disclose “wherein the operations further comprise, at an expiration of a refresh period, extract one or more updated dynamic context signals” (Mental process, observation, evaluation and judgment), t does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 3 disclose “computing device of claim 2, wherein the refresh period is based on a type of the one or more dynamic context signals” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 4 disclose “compare the updated context signals with the extracted context signals to determine that the updated context signals have changed (Mental process); and based on determining that the updated context signals have changed, generate another AI prompt requesting another visualization based on the updated context signals.” (Mental process); claims 5 disclose “the operations further comprise receiving a selection of the dynamic context signals to be used for generating the visualization” (receiving data) (insignificant extra-solution activity, MPEP 2106.05(g), Well-Understood, Routine, Conventional Activity, sending, receiving, displaying and processing data are common and basic functions in computer technology, MPEP 2106.05(d)(II)(i)); claim 5 does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 6 disclose “generating the AI prompt comprises: based on the selected dynamic context signals, selecting a particular AI prompt template from a plurality of AI prompt templates (Mental process), each of the AI prompt templates including static portions and dynamic portions (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use); and populating the dynamic portions of the particular AI prompt template with the dynamic context signals to generate the AI prompt.” (Mental process)). claim 6 does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 7 disclose “the context signals are extracted from at least one of the application, the operating system, the computing device, or an external source” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 8 disclose “the context signals include at least one of a location context signal or a weather context signal” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 9 disclose “wherein the context signals include a mailbox context signal” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 11 disclose “method of claim 10, wherein generating the first AI prompt comprises: based on the dynamic context signal, selecting a particular AI prompt template from a plurality of AI prompt templates (Mental process),, each of the AI prompt templates including a static portion and a dynamic portion (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use); and populating the dynamic portion of the particular AI prompt template with the dynamic context signal to generate the first AI prompt” (Mental process)). claim 11 does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 12 disclose “method of claim 10, wherein generating the first AI prompt comprises: based on the dynamic context signal, selecting a particular AI prompt template from a plurality of AI prompt templates (Mental process), each of the AI prompt templates including a static portion and a dynamic portion (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use); and populating the dynamic portion of the particular AI prompt template with the dynamic context signal to generate the first AI prompt” (Mental process)). claim 12 does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claim 13 disclose “wherein the context signal includes at least one of a location context signal, a weather context signal, or a mailbox context signal” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 14 disclose “wherein the second AI prompt also includes the extracted context signal” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 15 disclose “wherein the augmented context signal includes additional information related to the extracted context signal” (data description , which is directed to generally linking the use of a judicial exception to a particular technological environment or field of use). It does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea; claims 16 disclose “at an expiration of a refresh period, re-extracting the dynamic context signal and generating an updated visualization based on the re-extracted dynamic context signal” (Mental process, observation, evaluation and judgment). Claim 16 does not integrate the abstract idea into a practical application and did not add significantly more to the abstract idea. The dependent claims which impose additional limitations also fail to claim patent eligible subject matter because the limitations cannot be considered statutory. The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 1 ; where all claims are directed to the same abstract idea, "addressing each claim of the asserted patents [is] unnecessary." Content Extraction &. Transmission LLC v, Wells Fargo Bank, Natl Ass'n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter. Claims for the other statutory classes are similarly analyzed. For at least these reasons, the claimed inventions of each of dependent claims are directed or indirect to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more and are rejected under 35 USC 101. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15 AIA Claim s 17-18, and 20 are rejected under 35 U.S.C. 102( a)(1) and 35 U.S.C. 102(a)(2 ) as being anticipated by Karmanenko et al. [US 2014/0310643 A1, hereinafter Karmanenko] . With regard to Claim 17, Karmanenko teach a computer-implemented method for generating context-aware, dynamic visualizations, the method comprising: extracting a dynamic context signal (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”) ; based on the dynamic context signal, retrieving a first visualization (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”) ; causing a display of the first visualization as part of an application user interface (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, ¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶420, “with some user input and various sensors, can Switch between some predetermined “profiles'.”, ¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess”) ; at an expiration of a refresh period, extracting an updated dynamic context signal (¶179, “wallpaper is changed at a low rate”, ¶180, “wallpaper is changed very slowly”, “19. Living/Live Wallpaper ¶565. The wallpaper of the EPD screen could in one mode change itself depending on the Surrounding fac tors and other activating events”, ¶571, “The refresh rate should below (eg. once per day)”, ¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess”) ; based on the updated dynamic context signal, retrieving a second visualization (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶566, “Activating events could be” ¶567, “Location”, ¶568, “Time”, ¶569, “Upcoming events in calendar”, ¶570, “Weather (+location)”, ¶571, “The refresh rate should be low (eg. once per day)”, ¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess”) ; and replacing the first visualization with the second visualization as part of an application user interface (¶176, “the second screen is operable to display a wallpaper, and wherein an application which provides the wallpaper for display”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”) . With regard to Claim 18, Karmanenko teach the method of claim 17, wherein: retrieving the first visualization comprises: generating a first query based on the dynamic context signal (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶420, “with some user input and various sensors, can Switch between some predetermined “profiles'.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”) ; executing the first query against a database of images (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶420, “with some user input and various sensors, can Switch between some predetermined “profiles'.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”, ¶¶519-522, “When the “EPD wallpaper” icon has been selected the user is taken to a screen where he is presented with three options; New photo, EPD Wallpapers and Gallery”, ¶523 “Selecting EPD Wallpapers takes the user to the EPD Wallpaper gallery to select a wallpaper. Selecting Gallery takes the user to the native gallery application where the user can select“) ; and receiving, in response to the first query, a first image as the first visualization (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”, ¶512, “The widgets shown on the EPD screen have different layouts. These layouts can be related to the privacy level that the user decides to use for the information shown on the back Screen”, ¶522, “When the “EPD wallpaper” icon has been selected the user is taken to a screen where he is presented with three options; New photo, EPD Wallpapers and Gallery”, ¶523 “Selecting EPD Wallpapers takes the user to the EPD Wallpaper gallery to select a wallpaper. Selecting Gallery takes the user to the native gallery application where the user can select, crop and adjust an image“) ; and retrieving the second visualization comprises: generating a second query based on the updated dynamic context signal (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶420, “with some user input and various sensors, can Switch between some predetermined “profiles'.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”) ; executing the second query against the database (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶420, “with some user input and various sensors, can Switch between some predetermined “profiles'.”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”, ¶¶519-522, “When the “EPD wallpaper” icon has been selected the user is taken to a screen where he is presented with three options; New photo, EPD Wallpapers and Gallery”, ¶523 “Selecting EPD Wallpapers takes the user to the EPD Wallpaper gallery to select a wallpaper. Selecting Gallery takes the user to the native gallery application where the user can select“) ; and receiving, in response to the second query, a second image as the second visualization (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”, ¶512, “The widgets shown on the EPD screen have different layouts. These layouts can be related to the privacy level that the user decides to use for the information shown on the back Screen”, ¶522, “When the “EPD wallpaper” icon has been selected the user is taken to a screen where he is presented with three options; New photo, EPD Wallpapers and Gallery”, ¶523 “Selecting EPD Wallpapers takes the user to the EPD Wallpaper gallery to select a wallpaper. Selecting Gallery takes the user to the native gallery application where the user can select, crop and adjust an image“) . With regard to Claim 20, Karmanenko teach the method of claim 17, further comprising comparing the updated context signal with the initially extracted context signal to determine that the updated context signal changed from the initially extracted context signal (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶566, “Activating events could be” ¶567, “Location” , ¶568, “Time”, ¶569, “Upcoming events in calendar”, ¶570, “Weather (+location)”, ¶571, “The refresh rate should below (eg. once per day), So as not to annoy the user with new information too often or unnecessarily drain the battery”, ¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess” system compare current with previous location to identify that the current location is a new location to trigger activating event ) . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Karmanenko et al. [US 2014/0310643 A1, hereinafter Karmanenko] in view of “Opal: Multimodal Image Generation for News Illustration” disclosed in IDS submitted 11/11/2024 [hereinafter D1] . With regard to Claim 19, Karmanenko teach the method of claim 17, wherein: retrieving the first visualization (¶418, “various phone settings changing and events happening automatically with change in context, for example, hidden widgets appearing at certain times or themes changing with the weather”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”); dynamic context signal, and updated dynamic context signal ( ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”). Karmanenko does not disclose generating a first artificial intelligence (AI) prompt including the dynamic context signal ; providing the first AI prompt as input to a generative AI model; in response to providing the AI prompt as input, receiving an output payload from the generative AI model including the first visualization; and retrieving the second visualization comprises: generating a second artificial intelligence (AI) prompt including the updated dynamic context signal; providing the second AI prompt as input to the generative AI model; and in response to providing the AI prompt as input, receiving an output payload from the generative AI model including a second visualization. D1 teach retrieving the first visualization comprises: generating a first artificial intelligence (AI) prompt including dynamic context signals (P. 2, Col. 2, ¶3, “prompts structured in the template "{SUBJECT} in the style of {STYLE}". By parameterizing the prompts in this way, we systematically searched for qualities of the successful prompts that represented the articles well”, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety. These variations spanned different default styles: "{SELECTED WORD} in the style of a {photo / collage / painting }".”); providing the first AI prompt as input to a generative AI model (P. 6, 3.3.5, “For text-to-image generation, we used the checkpoint and configuration of VQGAN+CLIP”, “Each prompted image was generated to be 256x256 pixels”) ; in response to providing the AI prompt as input, receiving an output payload from the generative AI model including the first visualization (P. 1, “Figure 1: A screenshot of the Opal system”, Abstract, “Opal, a system that produces text-to-image generations”, “Opal guides users through a structured search for visual concepts and provides a pipeline allowing users to generate illustrations”, P. 6, 3.3.5, “Each prompted image was generated to be 256x256 pixels”) ; and retrieving the second visualization comprises: generating a second artificial intelligence (AI) prompt including the updated dynamic context signal (P. 2, Col. 2, ¶3, “prompts structured in the template "{SUBJECT} in the style of {STYLE}". By parameterizing the prompts in this way, we systematically searched for qualities of the successful prompts that represented the articles well”, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety. These variations spanned different default styles: "{SELECTED WORD} in the style of a {photo / collage / painting }".”) ; providing the second AI prompt as input to the generative AI model (P. 6, 3.3.5, “For text-to-image generation, we used the checkpoint and configuration of VQGAN+CLIP”, “Each prompted image was generated to be 256x256 pixels”) ; and in response to providing the AI prompt as input, receiving an output payload from the generative AI model including a second visualization (P. 1, “Figure 1: A screenshot of the Opal system”, Abstract, “Opal, a system that produces text-to-image generations”, “Opal guides users through a structured search for visual concepts and provides a pipeline allowing users to generate illustrations”, P. 6, 3.3.5, “Each prompted image was generated to be 256x256 pixels”) . Karmanenko and D1 are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information based on input context. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Karmanenko resulting in resolutions as disclosed by D1 with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify Karmanenko as described above to incorporate text-to-image generation technique into system that generate visual outputs based on user provided or dynamically updated context, in order to improve the flexibility and expressiveness of context aware illustrations, this will increase user satisfaction and save user time and effort that would be needed to manually create images (D1, Fig. 1, “Opal system, which helps users create news illustrations using a text-to-image generative AI”) . 07-21-aia AIA Claim s 1, 5-8, and 10-15 are rejected under 35 U.S.C. 103 as being unpatentable over “Opal: Multimodal Image Generation for News Illustration” disclosed in IDS submitted 11/11/2024 [hereinafter D1] in view of Antol et al. [US 2018/0204059 A1, hereinafter Antol] . With regard to Claim 1, D1 teach a computing device for generating context-aware, dynamic visualizations, the device comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor (Fig. 1, P. 1, “Figure 1: A screenshot of the Opal system”, screenshot show computer icons and windows ) cause the device to perform operations comprising: generate an artificial intelligence (AI) prompt, based at least in part on the one or more dynamic context signals, requesting a visualization (P. 2, Col. 2, ¶3, “prompts structured in the template "{SUBJECT} in the style of {STYLE}". By parameterizing the prompts in this way, we systematically searched for qualities of the successful prompts that represented the articles well”, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety”) ; provide the generated AI prompt as input to a generative AI model (P. 6, 3.3.5, “For text-to-image generation, we used the checkpoint and configuration of VQGAN+CLIP”) ; in response to providing the AI prompt as input, receive an output payload from the generative AI model including the visualization (P.6, 3.3.6, “The oeuvre provides users with a birds-eye view of all the generations they have created, and the generations stream in in real time as they are generated”, Abstract, “generate illustrations based on an article’s tone”) ; and cause a display of the visualization as part of a user interface of an application or an operating system operating on the computing device (P. 1, Fig. 1, “Figure 1: A screenshot of the Opal system”, P.6, 3.3.6, “The oeuvre provides users with a birds- eye view of all the generations they have created, and the generations stream in in real time as they are generated”) . D1 does not explicitly teach extract one or more dynamic context signals. Antol teach a computing device for generating context-aware, dynamic visualizations, the device comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor (Fig. 12, ¶67) , cause the device to perform operations comprising: extract one or more dynamic context signals (Fig. 2, 223, ¶70, “ information is received from sensors (e.g., sensors 230), speech/voice input (e.g., speech/voice input 231), Internet (e.g., Internet 232) and electronic device applications (e.g., installed applications 233)“, “ information received in block 1340 is classified (e.g., by context generation processing 220) into static context (e.g., static context 222), dynamic context (e.g., dynamic context 223), learned context (e.g., learned context 224) and inferred context (e.g., inferred context 225) “¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) . D1 and Antol are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information based on input context. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify D1 resulting in resolutions as disclosed by Antol with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify D1 as described above to provide intelligent services utilizing such physical sensors, software mechanisms and services hosted by electronic devices, thereby enabling context aware processing and adaptive generation of outputs based on real time and dynamically updated information (Antol, ¶¶3-5) . With regard to Claim 5, D1-Antol teach the computing device of claim 1, wherein the operations further comprise receiving a selection of the dynamic context signals to be used for generating the visualization (D1, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety”) . The same motivation to combine for claim 1 equally applies for current claim. With regard to Claim 6, D1-Antol teach the computing device of claim 5, wherein generating the AI prompt comprises: based on the selected dynamic context signals, selecting a particular AI prompt template from a plurality of AI prompt templates, each of the AI prompt templates including static portions and dynamic portions; and populating the dynamic portions of the particular AI prompt template with the dynamic context signals to generate the AI prompt (D1, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users vari-ety. These variations spanned different default styles: "{SELECTED WORD} (dynamic) in the style of a {photo / collage / painting }" ( static) ”) . The same motivation to combine for claim 1 equally applies for current claim. With regard to Claim 7, D1-Antol teach the computing device of claim 1, wherein the context signals are extracted from at least one of the application, the operating system, the computing device, or an external source (Antol, ¶70, “ information is received from sensors (e.g., sensors 230), speech/voice input (e.g., speech/voice input 231), Internet (e.g., Internet 232) and electronic device applications (e.g., installed applications 233) “) . The same motivation to combine for claim 1 equally applies for current claim. With regard to Claim 8, D1-Antol teach the computing device of claim 1, wherein the context signals include at least one of a location context signal or a weather context signal (Antol, Fig. 2, ¶61, “contextual information may include: current time, velocity of the device, sensor information, user speech information, textual information, device application information, and location information”, ¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) . The same motivation to combine for claim 1 equally applies for current claim. With regard to Claim 10, D1 teach a computer-implemented method for generating context-aware, dynamic visualizations, the method comprising: generating a first artificial intelligence (AI) prompt including the dynamic context signal (P. 5, 3.3.2, “To generate keyword suggestions for some {ARTICLE TEXT}, we prompted GPT-3 with the following instruction prompt, “Here are ten keywords for: {ARTI CLE TEXT}", and parsed the output. Likewise, we extracted tones from the text using the following prompt for GPT-3: "Here are ten emotions for: {ARTICLE TEXT}”” ; providing the first AI prompt as input to a first generative AI model (P. 5, 3.3.2, “To generate keyword suggestions for some {ARTICLE TEXT}, we prompted GPT-3 with the following instruction prompt, “Here are ten keywords for: {ARTI CLE TEXT}", and parsed the output. Likewise, we extracted tones from the text using the following prompt for GPT-3 : "Here are ten emotions for: {ARTICLE TEXT}””, 3.3.3, “We prompted GPT 3 using a prompt template: “Here are 10 icons related to: {KEY WORD / TONE }” We chose to look for “icons”, as they exist as abstractions in between the word and image space. This prompt allowed us to utilize GPT-3 as a knowledge base”) ; in response to providing the first AI prompt as input, receiving an output payload from the first generative Al model including an augmented context signal (Abstract, “generate illustrations based on an article’s tone, keywords, and related artistic styles”, P. 5, Fig. 3, “Opal generates key words and tones, as well as icons that can visualize those keywords and tones”) ; generating a second AI prompt based at least in part on the augmented context signal (P. 2, Col. 2, ¶3, “prompts structured in the template "{SUBJECT} in the style of {STYLE}". By parameterizing the prompts in this way, we systematically searched for qualities of the successful prompts that represented the articles well”, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety”) ; providing the second AI prompt as input to a second generative AI model (P. 6, 3.3.5, “For text-to-image generation, we used the checkpoint and configuration of VQGAN+CLIP”) ; in response to providing the second AI prompt as input, receiving an output payload from the second generative AI model including a visualization (D1, P.6, 3.3.6, “The oeuvre provides users with a birds-eye view of all the generations they have created, and the generations stream in in real time as they are generated”, Abstract, “generate illustrations based on an article’s tone”) ; and causing a display of the visualization in at least one of a user interface of an application or an operating system operating on a computing device (D1, P. 1, Fig. 1, “Figure 1: A screenshot of the Opal system”, P.6, 3.3.6, “The oeuvre provides users with a birds-eye view of all the generations they have created, and the generations stream in in real time as they are generated”) . D1 does not explicitly teach extracting a dynamic context signal. Antol teach a computer-implemented method for generating context-aware, dynamic visualizations, the method comprising: extracting a dynamic context signal (Fig. 2, 223, ¶70, “information is received from sensors (e.g., sensors 230), speech/voice input (e.g., speech/voice input 231), Internet (e.g., Internet 232) and electronic device applications (e.g., installed applications 233)“, “information received in block 1340 is classified (e.g., by context generation processing 220) into static context (e.g., static context 222), dynamic context (e.g., dynamic context 223), learned context (e.g., learned context 224) and inferred context (e.g., inferred context 225)“, ¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) ; in response to providing input, receiving an output including an augmented context signal (¶34, “camera imagery may be used to classify the location of the user (“home,” “office,” “beach,” etc.), to detect common objects, and to recognize specific faces and emotions. The intelligent camera 205 derives from advances in computer vision and artificial intelligence that make use of deep learning technology”, ¶70, “ information is received from sensors (e.g., sensors 230), speech/voice input (e.g., speech/voice input 231), Internet (e.g., Internet 232) and electronic device applications (e.g., installed applications 233) “, “ information received in block 1340 is classified (e.g., by context generation processing 220) into static context (e.g., static context 222), dynamic context (e.g., dynamic context 223), learned context (e.g., learned context 224) and inferred context (e.g., inferred context 225) “¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) . D1 and Antol are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information based on input context. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify D1 resulting in resolutions as disclosed by Antol with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify D1 as described above to provide intelligent services utilizing such physical sensors, software mechanisms and services hosted by electronic devices, thereby enabling context aware processing and adaptive generation of outputs based on real time and dynamically updated information (Antol, ¶¶3-5) . With regard to Claim 11, D1-Antol teach the method of claim 10, wherein generating the first AI prompt comprises: based on the dynamic context signal, selecting a particular AI prompt template from a plurality of AI prompt templates, each of the AI prompt templates including a static portion and a dynamic portion, and populating the dynamic portion of the particular AI prompt template with the dynamic context signal to generate the first AI prompt (D1, P. 5, 3.3.2, “To generate keyword suggestions for some {ARTICLE TEXT}, we prompted GPT-3 with the following instruction prompt, “Here are ten keywords for: {ARTI CLE TEXT}", and parsed the output. Likewise, we extracted tones from the text using the following prompt for GPT-3 : "Here are ten emotions for: {ARTICLE TEXT}””, 3.3.3, “We prompted GPT 3 using a prompt template: “Here are 10 icons related to: {KEY WORD / TONE }” We chose to look for “icons”, as they exist as abstractions in between the word and image space. This prompt allowed us to utilize GPT-3 as a knowledge base”), Antol, Fig. 2, 223, ¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) . The same motivation to combine for claim 10 equally applies for current claim. With regard to Claim 12, D1-Antol teach the method of claim 10, wherein generating the second AI prompt comprises: based on the augmented context signal, selecting a particular AI prompt template from a plurality of AI prompt templates, each of the AI prompt templates including a static portion and a dynamic portion; and populating the dynamic portion of the particular AI prompt template with the augmented context signal to generate the second AI prompt (D1, P. 2, Col. 2, ¶3, “prompts structured in the template "{SUBJECT} in the style of {STYLE}". By parameterizing the prompts in this way, we systematically searched for qualities of the successful prompts that represented the articles well”, P. 6, ¶5, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety”, Antol, Fig. 2, 223, ¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶36, “context from static context 222, dynamic context 223, learned context 224, and inferred context 225”) . The same motivation to combine for claim 10 equally applies for current claim. With regard to Claim 13, D1-Antol teach the method of claim 10, wherein the context signal includes at least one of a location context signal, a weather context signal, or a mailbox context signal (Antol, Fig. 2, 223, ¶24, “retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof”, ¶61, “contextual information may include: current time, velocity of the device, sensor information, user speech information, textual information, device application information, and location information”) . The same motivation to combine for claim 10 equally applies for current claim. With regard to Claim 14, D1-Antol teach the method of claim 10, wherein the second AI prompt also includes the extracted context signal (D1, Abstract, “generate illustrations based on an article’s tone keywords, and related artistic styles”, P. 6, “Users could generate by selecting keywords, tones, and icons they wanted to try and hitting ’Generate’. These selections were automatically generated with three variations of the prompts, to show users variety”) . The same motivation to combine for claim 10 equally applies for current claim. With regard to Claim 15, D1-Antol teach the method of claim 10, wherein the augmented context signal includes additional information related to the extracted context signal (D1, Abstract, “generate illustrations based on an article’s tone, keywords, and related artistic styles”, P. 5, Fig. 3, “Opal generates key words and tones, as well as icons that can visualize those keywords and tones”) . The same motivation to combine for claim 10 equally applies for current claim . 07-21-aia AIA Claim s 2-4, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over “Opal: Multimodal Image Generation for News Illustration” disclosed in IDS submitted 11/11/2024 [hereinafter D1] in view of Antol et al. [US 2018/0204059 A1, hereinafter Antol] in view of Karmanenko et al. [US 2014/0310643 A1, hereinafter Karmanenko] . With regard to Claim 2, D1-Antol teach the computing device of claim 1. D1-Antol does not explicitly teach an expiration of a refresh period, extract one or more updated dynamic context signals. Karmanenko teach at an expiration of a refresh period, extract one or more updated dynamic context signals (¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess”, ¶419, “Context (location, time and other sensors or user input) may affect the style and layout of the UI, including for example widgets (and information) on front and back screen”, ¶467-474, ¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶178, “ activating event is one or more of: device location, time, calendar events, weather, weather in combination with location”, ¶564, “19. Living/Live Wallpaper” ¶565 “The wallpaper of the EPD screen could in one mode change itself depending on the Surrounding fac tors and other activating events” ¶566, “Activating events could be” ¶567, “Location”, ¶568, “Time”, ¶569, “Upcoming events in calendar”, ¶570, “Weather (+location)”, ¶571, “The refresh rate should below (eg. once per day), So as not to annoy the user with new information too often or unnecessarily drain the battery”)) . D1-Antol and Karmanenko are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information based on input context. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify D1-Antol resulting in resolutions as disclosed by Karmanenko with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify D1-Antol as described above to provide a dynamic data that ensures that the system operated on current data, improve accuracy, and relevance of the generated output to the user which increase the user satisfaction by providing correct customized data to the user. This is simply combining prior art elements according to known methods to yield predictable results, use of known technique to improve similar devices (methods, or products) in the same way, and applying a known technique to a known device (method, or product) ready for improvement to yield predictable results. With regard to Claim 3, D1-Antol-Karmanenko teach the computing device of claim 2, wherein the refresh period is based on a type of the one or more dynamic context signals (Karmanenko ¶467, “Widgets displayed on the EPD screen could have different update frequencies to reflect the type of widget.”, ¶468, “for example”, ¶¶469-474, “Weather widget updates every 30 minutes, Weather widget updates every 30 minutes Clock widget updates every 1 minute, Twitter widget updates on demand, Twitter widget updates on demand Friends nearby widget updates every 5 minutes“). The same motivation to combine for claim 2 equally applies for current claim. With regard to Claim 4, D1-Antol-Karmanenko teach the computing device of claim 2, wherein the operations further comprise: compare the updated context signals with the extracted context signals to determine that the updated context signals have changed; and based on determining that the updated context signals have changed, generate another AI prompt requesting another visualization based on the updated context signals (¶177, “the application which provides the wallpaper for display changes the displayed wallpaper in response to activating event”, ¶566, “Activating events could be” ¶567, “Location” , ¶568, “Time”, ¶569, “Upcoming events in calendar”, ¶570, “Weather (+location)”, ¶571, “The refresh rate should below (eg. once per day), So as not to annoy the user with new information too often or unnecessarily drain the battery”, ¶421, “sensor may well be used to poll the status, e.g. once every day check the temperature at a specific time to guess the season or the GPS every hour to see if the user changes location or even in combination for best guess” , P. 6, 3.3.5, “For text-to-image generation, we used the checkpoint and configuration of VQGAN+CLIP”) . The same motivation to combine for claim 2 equally applies for current claim. With regard to Claim 16, D1-Antol teach the method of claim 10. D1-Antol does not explicitly teach update based upon an expiration of a refresh period, re-extracting the dynamic context signal and generating an updated visualization based on the re-extracted dynamic context signal. Karmanenko teach update based upon an expiration of a refresh period, re-extracting the dynamic context signal and generating an updated visualization based on the re-extracted dynamic context signal (“19. Living/Live Wallpaper 0565. The wallpaper of the EPD screen could in one mode change itself depending on the Surrounding fac tors and other activating events” ¶566, “Activating events could be” ¶567, “Location”, ¶568, “Time”, ¶569, “Upcoming events in calendar”, ¶570, “Weather (+location)”, ¶571, “The refresh rate should below (eg. once per day)”). D1-Antol and Karmanenko are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information based on input context. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify D1-Antol resulting in resolutions as disclosed by Karmanenko with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify D1-Antol as described above to provide a dynamic data that ensures that the system operated on current data, improve accuracy, and relevance of the generated output to the user which increase the user satisfaction by providing correct customized data to the user. This is simply combining prior art elements according to known methods to yield predictable results, use of known technique to improve similar devices (methods, or products) in the same way, and applying a known technique to a known device (method, or product) ready for improvement to yield predictable results . 07-21-aia AIA Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over “Opal: Multimodal Image Generation for News Illustration” disclosed in IDS submitted 11/11/2024 [hereinafter D1] in view of Antol et al. [US 2018/0204059 A1, hereinafter Antol] in view of Tseng et al. [US 2008/0295017 A1, hereinafter Tseng] . With regard to Claim 9, D1-Antol teach the computing device of claim 1. The same motivation to combine for claim 1 equally applies for current claim. Antol teach that the context signals include applications (¶70, “ information is received from sensors (e.g., sensors 230), speech/voice input (e.g., speech/voice input 231), Internet (e.g., Internet 232) and electronic device applications (e.g., installed applications 233)). However, D1-Antol does not explicitly teach context signals include a mailbox context signal. Tseng teach context signals include a mailbox context signal (Fig. 4, 404, ¶76, “messaging bar 404 may provide status information that shows the number of unread messages for a particular messaging application. The messaging application may comprise, for example, e'mail, SMS, and/or MMS along with date and time. The messaging bar 404 displays a message list view of icons associated with a particular messaging application. The messaging bar 404 displays an SMS/MMS message list view icon 404-1 and the number of unread SMS/MMS messages associated therewith (e.g., 555). The messaging bar 404 also displays an e'mail message list view icon 404-2 and the number of unread e'mail messages associated therewith (e.g., 555)”) . D1-Antol and Tseng are analogous art to the claimed invention because they are from a similar field of endeavor of visual representation of information. Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify D1-Antol resulting in resolutions as disclosed by Tseng with a reasonable expectation of success. One of ordinary skill in the art would be motivated to modify D1-Antol as described above to provide a clear visualization for mailbox data in real time which save user time and effort required for manual checking. This is simply combining prior art elements according to known methods to yield predictable results, use of known technique to improve similar devices (methods, or products) in the same way, and applying a known technique to a known device (method, or product) ready for improvement to yield predictable results. Conclusion 07-96 The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure. US Patent Application Publication No. 2008/0201647 A1 filed by Lagerstedt et al. that disclose the ability to collect context data to provide dynamic visualization within application See at least Fig. 1 Examiner has pointed out particular references contained in the prior arts of record in the body of this action for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and Figures may apply as well. It is respectfully requested from the applicant, in preparing the response, to consider fully the entire references as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior arts or disclosed by the examiner. It is noted that any citation to specific pages, columns, figures, or lines in the prior art references any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck , 699 F.2d 1331-33, 216 USPQ 1038-39 (Fed. Cir. 1983) ( quoting In re Lemelson , 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED ABOU EL SEOUD whose telephone number is (303)297-4285. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MOHAMED ABOU EL SEOUD/Primary Examiner, Art Unit 2148 Application/Control Number: 18/231,064 Page 2 Art Unit: 2148 Application/Control Number: 18/231,064 Page 3 Art Unit: 2148 Application/Control Number: 18/231,064 Page 4 Art Unit: 2148 Application/Control Number: 18/231,064 Page 5 Art Unit: 2148 Application/Control Number: 18/231,064 Page 6 Art Unit: 2148 Application/Control Number: 18/231,064 Page 7 Art Unit: 2148 Application/Control Number: 18/231,064 Page 8 Art Unit: 2148 Application/Control Number: 18/231,064 Page 9 Art Unit: 2148 Application/Control Number: 18/231,064 Page 10 Art Unit: 2148 Application/Control Number: 18/231,064 Page 11 Art Unit: 2148 Application/Control Number: 18/231,064 Page 12 Art Unit: 2148 Application/Control Number: 18/231,064 Page 13 Art Unit: 2148 Application/Control Number: 18/231,064 Page 14 Art Unit: 2148 Application/Control Number: 18/231,064 Page 15 Art Unit: 2148 Application/Control Number: 18/231,064 Page 17 Art Unit: 2148 Application/Control Number: 18/231,064 Page 18 Art Unit: 2148 Application/Control Number: 18/231,064 Page 19 Art Unit: 2148 Application/Control Number: 18/231,064 Page 20 Art Unit: 2148 Application/Control Number: 18/231,064 Page 21 Art Unit: 2148 Application/Control Number: 18/231,064 Page 22 Art Unit: 2148 Application/Control Number: 18/231,064 Page 23 Art Unit: 2148 Application/Control Number: 18/231,064 Page 24 Art Unit: 2148 Application/Control Number: 18/231,064 Page 25 Art Unit: 2148 Application/Control Number: 18/231,064 Page 26 Art Unit: 2148 Application/Control Number: 18/231,064 Page 27 Art Unit: 2148 Application/Control Number: 18/231,064 Page 28 Art Unit: 2148 Application/Control Number: 18/231,064 Page 29 Art Unit: 2148 Application/Control Number: 18/231,064 Page 30 Art Unit: 2148 Application/Control Number: 18/231,064 Page 31 Art Unit: 2148 Application/Control Number: 18/231,064 Page 32 Art Unit: 2148 Application/Control Number: 18/231,064 Page 33 Art Unit: 2148 Application/Control Number: 18/231,064 Page 34 Art Unit: 2148 Application/Control Number: 18/231,064 Page 35 Art Unit: 2148 Application/Control Number: 18/231,064 Page 36 Art Unit: 2148 Application/Control Number: 18/231,064 Page 37 Art Unit: 2148 Application/Control Number: 18/231,064 Page 38 Art Unit: 2148 Application/Control Number: 18/231,064 Page 39 Art Unit: 2148 Application/Control Number: 18/231,064 Page 40 Art Unit: 2148 Application/Control Number: 18/231,064 Page 41 Art Unit: 2148 Application/Control Number: 18/231,064 Page 42 Art Unit: 2148 Application/Control Number: 18/231,064 Page 43 Art Unit: 2148 Application/Control Number: 18/231,064 Page 44 Art Unit: 2148
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