High-end display for displaying dynamically evolving generative art

Abstract

This disclosure provides a square display for displaying generative art and a display for displaying generative art. The square QLED display device is specifically designed to display generative and dynamically evolving art. The device combines a custom-designed high-density micro-LED backlight and a quantum dot layer to achieve excellent color gamut and contrast with a 1:1 shape factor. Integrated millimeter-wave (mmWave) and other sensors enable viewer and environmental detection. The display also includes an integrated high-performance GPU for real-time generative art rendering. The display utilizes various inputs from sensors embedded in the display device, as well as randomization features embedded in generative algorithms. These inputs and randomization features together enable the creation of “living” artworks that continuously evolve and dynamically respond to their environment and background.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Patent Application No. 19 / 009,586, filed January 3, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to a digital art display, and more particularly to a high-resolution digital display for displaying dynamic and evolving generative artworks. Background Technology

[0004] The mediums used to display art have undergone a significant transformation from static canvases to digital displays capable of showcasing diverse works of art. While traditional displays allowed for manual alteration of art, they lacked the ability to represent evolving art—art that changes gradually and responds to its environment. Furthermore, traditional display devices were designed for general applications and were not configured to display high-quality generative dynamic art. The limitations of their visual quality, color gamut, and contrast hindered their use for artistic purposes. Moreover, while generative art has become widespread, the hardware required to display these works (especially at high resolutions and frame rates) needs to be connected to external computing devices, thus limiting usability and integration. Summary of the Invention

[0005] At least one embodiment of this disclosure provides a square display for rendering generative art, comprising: a backlight layer customized for a square display area; one or more processors integrated within the square display; a graphics processing unit (GPU) integrated within the square display, the GPU being configured to render the generative art; and a light sensor configured to match illumination at a location of the square display with optimized lighting for rendering the generative art.

[0006] For example, a square display provided in one embodiment of this disclosure further includes a millimeter-wave sensor within the square display, the millimeter-wave sensor being used to sense the number of people present at a certain location on the square display, and the activity of one of the one or more people.

[0007] For example, a square display provided in one embodiment of this disclosure also includes a software engine configured to change the generative art presented on the square display when sensor readings from at least one of the light sensor and the millimeter-wave sensor change.

[0008] For example, a square display provided in one embodiment of this disclosure further includes an LCD layer, which is customized for use with a square display.

[0009] For example, a square display provided in one embodiment of this disclosure further includes a backlight controller, wherein the backlight controller is customized to be suitable for the square backlight layer.

[0010] For example, a square display provided in one embodiment of this disclosure further includes a thermally conductive frame, the thermally conductive frame including a raised surface surrounded by a recessed portion for conducting heat away from the square display.

[0011] At least one embodiment of this disclosure also provides a display for presenting generative art, comprising: one or more environmental sensors and one or more processors; the one or more processors being configured to execute code to: run a generative art algorithm to generate a generative artwork; render the generative artwork; modify the generative artwork in response to input from the one or more environmental sensors; and modify the generative artwork in response to a randomization function included in the generative art algorithm.

[0012] For example, in a display provided in one embodiment of this disclosure, the generative artwork is changed in response to input from one or more environmental sensors and in response to the randomization function, such that the artwork changes during the usage period of the display and does not repeatedly display previously shown images or videos.

[0013] For example, in a display provided in one embodiment of this disclosure, the generative art algorithm generates artworks categorized into a certain type.

[0014] For example, in a display provided in one embodiment of this disclosure, the generative art algorithm is selected because the classification of the generative art algorithm matches the environmental atmosphere of a certain location on the display.

[0015] For example, in a display provided in one embodiment of this disclosure, the generative art algorithm discovers the input from one or more environmental sensors in the display via an application programming interface.

[0016] For example, in a display provided in one embodiment of this disclosure, the one or more environmental sensors include a light sensor.

[0017] For example, in a display provided in one embodiment of this disclosure, the one or more environmental sensors include millimeter-wave sensors.

[0018] For example, in a display provided in one embodiment of this disclosure, the one or more environmental sensors include a microphone.

[0019] For example, in a display provided in one embodiment of this disclosure, the display is a quantum light-emitting diode (QLED) type display.

[0020] At least one embodiment of this disclosure also provides a display for presenting generative art, the display including: one or more environmental sensors and one or more artificial intelligence (AI) processors; the one or more AI processors being configured to execute code to: generate a generative art algorithm; run the generative art algorithm to generate a generative artwork; render the generative artwork; modify the generative artwork using artificial intelligence in response to input from the one or more environmental sensors; and modify the generative artwork in response to a randomization function included in the generative art algorithm; wherein modifying the generative artwork in response to input from the one or more environmental sensors and modifying the generative artwork in response to the randomization function such that the artwork modified during the usage period of the display does not repeatedly display previously shown images or videos.

[0021] For example, in a display provided in one embodiment of this disclosure, the generative art algorithm uses artificial intelligence to generate artworks categorized into a category.

[0022] For example, in a display provided in one embodiment of this disclosure, the generative art algorithm is selected because the classification of the generative art algorithm matches the environmental atmosphere of a certain location on the display.

[0023] For example, in a display provided in one embodiment of this disclosure, the display is a quantum light-emitting diode (QLED) type display. Attached Figure Description

[0024] Figure 1 This is a schematic block diagram of a generative display according to embodiments of the present disclosure;

[0025] Figure 2 This is a schematic representation of a generative display according to embodiments of the present disclosure;

[0026] Figure 3 This is a flowchart illustrating the steps of an artist content provider creating a generative art algorithm according to embodiments of the present disclosure;

[0027] Figure 4 This is a flowchart illustrating the steps of performing a generative art algorithm within a display according to an embodiment of the present disclosure;

[0028] Figure 5 This is an illustration of a display showing generative art according to embodiments of the present disclosure;

[0029] Figure 6 This is an illustration of the back of a generative display according to an embodiment of the present disclosure; and

[0030] Figure 7 This is a schematic block diagram of a computing environment according to embodiments of the present disclosure. Detailed Implementation

[0031] The technology of this disclosure will now be described with reference to the accompanying drawings, which generally relate to a square quantum light-emitting diode (QLED) display device specifically designed for displaying generative, dynamically evolving art. This display combines a custom-designed high-density micro-LED backlight with a quantum dot layer to achieve excellent color gamut and contrast with a 1:1 form factor. Integrated millimeter-wave (mmWave) and other sensors enable viewer and environmental detection. The display also includes an integrated high-performance graphics processing unit (GPU) for real-time generative art rendering.

[0032] The display is configured to showcase dynamically changing and constantly evolving generative artworks. The system utilizes various inputs from sensors embedded in the display device, as well as randomization features embedded in the generative art algorithm. These inputs and randomization features together enable the creation of “vivid” artworks that continuously evolve and dynamically respond to their environment and context.

[0033] It should be understood that the present invention can be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided to make this disclosure clear and complete and to fully communicate the invention to those skilled in the art. In fact, the invention is intended to cover alternatives, modifications, and equivalents to these embodiments, which are included within the scope and spirit of the invention as defined by the appended claims. Furthermore, numerous specific details are set forth in the following detailed description of the invention to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without these specific details.

[0034] Figure 1 This is a schematic block diagram of a sample-generating display 100 according to the present disclosure. Reference is made below. Figure 7The composition of display 100 will be described in more detail, but generally, display 100 can be a quantum light-emitting diode (QLED) type display. In another embodiment, display 100 may operate according to organic light-emitting diode (OLED) or other technologies. Display 100 may include processor 102, which is configured to control the operation of display 100 and facilitate communication between various components within display 100. Processor 102 may include a standardized processor, a dedicated processor, a microprocessor, an artificial intelligence (AI) processor, etc., capable of executing instructions for controlling display 100.

[0035] According to other aspects of this disclosure, the display 100 may include an integrated graphics processing unit (or GPU) 104 dedicated to rendering high-quality images and graphics, including real-time generative art. The GPU 104 of this disclosure is designed to provide high-performance rendering capabilities tailored to real-time generative dynamic art. The GPU 104 may include advanced parallel processing cores optimized for handling complex visual computations, ensuring smooth rendering of high-resolution interactive art at frame rates exceeding, for example, 60 FPS, even if the frame rate is higher or lower than that in other embodiments.

[0036] To match the enhanced color gamut and contrast of the display, the GPU can incorporate a dedicated tone mapping algorithm and support HDR (High Dynamic Range) processing, ensuring accurate and vivid color reproduction. Furthermore, GPU 104 can include hardware acceleration for machine learning inference, allowing it to process sensor data from mmWave as described below. Hardware acceleration can also assist in real-time machine learning related to ambient light and microphone input, enabling seamless interaction between the displayed art and its environment. GPU 104 can also integrate a custom memory tier with high-bandwidth GDDR6 or GDDR6X RAM for fast data access, ensuring minimal latency during complex art transformations. Display 100 may also include a thermal management system for managing processor 102 and GPU 104, optimized for silent operation, making it suitable for art displays. Figure 1 In the illustrated embodiment, the processor 102 and GPU 104 are separate components; in another embodiment, the processor 102 and GPU 104 may also be integrated together.

[0037] The display 100 may also include a memory 106, which may store algorithms that can be executed by the processor 102 and the GPU 104. According to an example embodiment, the memory 106 may include RAM, ROM, cache, flash memory, hard disk, and / or any other suitable storage component. Figure 1As shown, in one embodiment, memory 106 may be a separate component that is communicatively connected to processor 102 and GPU 104, while in another embodiment, memory 106 may also be integrated into processor 102 and / or GPU 104.

[0038] Memory 106 may store various software applications executed by processor 102 and / or GPU 104 for controlling the operation of display 100. These applications may include, for example, an operating system 108, a dynamic generative art engine 110, a graphics rendering engine 112, a sensor integration controller 114, and a power management system 115. Each of these software components is explained in more detail below. Display 100 may also include data storage 116 for storing selections of generative art algorithms. Display 100 also includes sensors 120 (including, for example, mmWave sensors), input / output (I / O) interfaces 122, and network interfaces 124. Each of these components is explained in more detail below. In some other embodiments, memory 106 may also store additional algorithms.

[0039] Operating system 108 manages the hardware and software components of display 100 to ensure that software components are scheduled and executed without conflicts, and provides a user interface for users to interact with display 100. Operating system 108 includes a kernel that integrates and coordinates hardware and software components, including GPU 104, sensor 120, and display rendering components as described below. Operating system 108 may also prioritize low-latency graphics rendering to ensure seamless display of dynamically generative art. Operating system 108 also includes a content management framework that allows users to upload and organize generative art files or algorithms locally or via a cloud-connected interface. In some other embodiments, operating system 108 may also perform additional functions.

[0040] The dynamic generative art engine 110 can perform multiple functions, but is generally used to create display-ready generative art to be presented on the display 100. In some embodiments, the dynamic generative art engine 110 receives generative art algorithms from an artist via one or more remote sources described below. The generative art algorithms are created to display digital art that changes and evolves over time. One way the algorithm is configured to change the displayed art over time is by accepting contextual input, such as from environmental and situational sensors embedded in the display 100. The algorithm may also include a randomization function that changes the characteristics of the displayed digital art in an unpredictable and non-repeatable manner. This combination of context awareness and random variability produces “living” artwork that evolves and continuously changes the displayed generative art to consistently engage and entertain the viewer.

[0041] The following is for reference. Figure 3 and Figure 4 The flowchart details the creation of the generative art algorithm and its use by the motion art engine 110. However, generally, artist content creators generate generative art algorithms, which are processed by the motion art engine 110 for rendering on the display 100. The generative art algorithm from the content creator can be loaded into the memory 106 of the display 100 in various ways. For example... Figure 1 As shown, in one example, display 100 is connected to network 130, such as the Internet or a local area network, via network interface 124. Generative art server 132 may be dedicated to serving display 100 at multiple locations and may be a central repository for generative art algorithms. Server 132 may receive generative art algorithms from artists and may download generative art algorithms to display 100 in response to requests received from curators of display 100. Generative art algorithms may originate from other remote locations, such as including one or more third-party content providers 134 that provide content to server 132 or directly to display 100. Generative art algorithms may additionally or alternatively be loaded from flash drives or other portable storage devices into data storage 116 of memory 106 via I / O interface 122.

[0042] User control of the display 100 can be achieved by a dedicated controller or by a portable computing device such as a smartphone, tablet, or laptop. Such control can include various tasks, such as turning the display on and off, manually selecting channels or specific artwork, and / or manually adjusting the display 100. The dedicated controller or portable computing device can interact with the display 100 via I / O interface 122 or a network interface.

[0043] As mentioned above, digital art displayed by generative art algorithms can be customized for its display environment. This can be done in at least two ways. First, the subject matter of the generative artwork can be broadly categorized into one of several categories that match the atmosphere of the space or location of the display 100 (referred to as the display location in this document). These categories may include, for example:

[0044] Peaceful and serene;

[0045] Full of energy;

[0046] Introspection and reflection;

[0047] Socially active;

[0048] Romantic and intimate;

[0049] Mysterious and magical;

[0050] The profession is formal;

[0051] Fun and play;

[0052] Minimalist and modern;

[0053] Inspired by nature;

[0054] Festival season; and

[0055] Cultural traditions.

[0056] Other atmospheres and classification types are also acceptable. Different channels corresponding to these different categories can be provided for the display. Generative artworks can be categorized into one or more of these categories by content providers or by a dynamic generative art engine 110 (e.g., implementing an AI platform as described below). Based on the selected channel, the engine 110 can select a generative art algorithm from that channel category.

[0057] A second way in which generative art algorithms customize digital art for their display environment is by configuring the algorithm to receive real-time contextual input from or related to the display environment. For example, display 100 may include multiple sensors 120 for sensing parameters and characteristics of the display's position. For instance, display 100 may include a millimeter-wave sensor 120 that can sense several characteristics about people in the room. It can determine whether someone is in the room. It can also determine the number of people in the room, as well as their movements and behaviors. It can also provide biometric data about the people in the room.

[0058] In some other embodiments, the millimeter-wave sensor 120 may be omitted. In these embodiments, machine learning can also be used to infer room context based on the signal strength and device ID of nearby Bluetooth devices. This Bluetooth-based approach will enhance mmWave data, or replace mmWave data in embodiments where the mmWave sensor is omitted.

[0059] The display may also include other types of sensors 120, such as sensors that measure the amount of light in the display's position, temperature sensors, noise level sensors, and microphones. In some other embodiments, the display 100 may also include other or alternative types of sensors 120. Artist content providers may be provided with an application programming interface (API) that allows them to program generative art algorithms to accept some or all of the input from these sensor outputs. Generative art algorithms may be programmed to accept other non-contextual inputs. For example, a dynamic generative art engine 110 may be configured to receive current events or other news via its connection to the Internet. Input received from any of the sensors 120 or the Internet is referred to herein as contextual input.

[0060] The generative art algorithm generated by the content provider can be customized in response to an API (e.g., provided by server 132 or display 100) to receive real-time contextual input from either of the aforementioned sources. Therefore, when the algorithm is executed on display 100 by dynamic generative art engine 110, the same generative art algorithm will produce different digital artworks based on the contextual input received by the algorithm. As a simple example, unlike traditional computer monitors, the display brightness is expected to be maintained at the room light level. Therefore, the brightness of display 100 can be adjusted to match the light in the display's location. When the light in the display's location changes, where the light is the input to the generative art algorithm, the display brightness also changes accordingly. The generative art algorithm can be configured to receive a large amount of contextual input or a relatively small amount of contextual input as input.

[0061] The dynamic generative art engine 110 can customize and change the displayed art in a variety of ways in response to different contextual inputs. The dynamic generative art engine 110 processes data from mmWave sensors, microphones, ambient light detectors, and any other sensors 120 to adjust the content of the artwork in real time. For example, the generative art algorithm running by engine 110 can slow down animations in a silent environment or create interactive art that reacts to viewer actions. The artwork presented on display 100 can change or evolve in many other ways in response to contextual inputs.

[0062] Contextual input can be updated in real time. However, user-defined sensitivity metrics can also be applied when determining whether to change the displayed art. For example, a curator can set the sensitivity level to high, meaning that even subtle changes in the contextual input will cause the artwork to change. Alternatively, the sensitivity level can be set to low, so that small changes in the contextual input will not cause the artwork to change. Sensitivity metrics can also be set by default by the dynamically generated art engine 110.

[0063] Alternatively, the displayed digital artwork can be allowed to change periodically in response to changing contextual input (only after a set period of time). This allows users to avoid overly frequent changes to the artwork. The timeframe and speed at which the digital artwork changes in response to new contextual input can be defined by the curator of the display or by the default settings of the dynamic generative art engine 110.

[0064] The system described above provides two layers of control over the content displayed on monitor 100. First, the artist content provider has the right to define how their generative artwork responds to specific contextual inputs. For example, the artwork can change its visual elements or behavior based on room brightness, the number of people and their activity level, or other detected conditions. This allows for artistic interpretation and customization in different environments. Second, the dynamic generative art engine 110 can control the content by responding to contextual inputs to select content to be displayed in a predefined and known manner.

[0065] Another feature of this disclosure is that the artwork presented on display 100 according to a given generative art algorithm can continuously and dynamically change (within the display's usage cycle), never repeating previously displayed images or videos. This can be attributed in part to the variation in contextual input as described above. As another feature, the generative art algorithm can be programmed using a randomization function. In particular, the algorithm can use a random seed generator to generate a random seed. Changing the random seed will result in different sequences of random numbers, which can be used to change various aspects of the artwork, such as shape, color, position, size, or pattern. The seed can be a static seed or an evolving seed. Therefore, the artwork generated by the given generative art algorithm can continuously change, regardless of any changes caused by contextual input.

[0066] Using the features described above, the dynamic generative art engine 110 can select a generative art algorithm based on a defined classification (see below). Figure 4 (The flowchart is explained below). Then, engine 110 can run the algorithm using contextual input from sensor 120 or other sources required by the algorithm. The result is a "living" work of art. Like a living organism, the work of art is affected by and responds to changes in its environment, constantly evolving to continuously attract and entertain the audience.

[0067] The dynamic generative art engine 110 can also be used as a content management service. Engine 110 can manage generative art algorithms downloaded from server 132 or third-party content providers 134, as well as algorithm storage within data storage 116 of memory 106. The content management functions of the dynamic generative art engine 110 can also include scheduling content for display on display 100.

[0068] By executing generative art algorithms, the dynamic generative art engine 110 generates display-ready image or video files. The graphics rendering engine 112 is responsible for acquiring display-ready files from the dynamic generative art engine 110 and rendering them as visual content and images on the screen of the display 100. The graphics rendering engine 112 processes input data, such as code for generative art, and uses the GPU 104 to render high-resolution image frames at a smooth (high) frame rate. The engine 112 operates through a rendering pipeline that includes stages such as vertex processing (defining object shape and position), rasterization (converting shapes into pixels), and fragment processing (adding textures, colors, and lighting). In embodiments where the display 100 is QLED, the graphics rendering engine 112 may further include advanced shader procedures to ensure accurate color reproduction and vivid contrast, thereby leveraging the quantum dot enhancement capabilities of the QLED display to achieve a high-quality visual experience.

[0069] Figure 1 The illustrated display 100 may also include a sensor integration controller 114 for receiving sensor feedback from the sensor 120 and formatting the sensor feedback for use by the dynamic generative art engine 110. For example, the controller 114 may format sensor data to match algorithm input. The sensor integration controller 114 may further filter noise and / or normalize data from the sensor data for use by the engine 110. The controller 114 may also monitor the operation of the various sensors 120.

[0070] The display 100 may also include a power management system 115. The power management system in the display is designed to optimize energy consumption while maintaining display quality. The system 115 can also implement a power-saving mode, wherein when the mmWave sensor 120 senses that the display position is empty for a predetermined period of time, the system 115 can turn off the power to the display or dim the display.

[0071] As described above, processor 102 can be an artificial intelligence processor, such as implementing a large language model or other convolutional neural network. Artificial intelligence can be used to improve several aspects of this disclosure. For example, artificial intelligence can help the dynamic generative art engine 110 categorize generative artworks into different categories corresponding to room atmospheres. The dynamic generative art engine 110 can use artificial intelligence to analyze sensor feedback and select optimized generative artworks for room atmospheres. Artificial intelligence can also help engine 110 determine how artworks evolve as contextual input changes. It is conceivable that artificial intelligence can be used to create entirely new generative art algorithms based on contextual input.

[0072] Artificial intelligence can also be used to assist sensors such as mmWave sensor 120 in analyzing the position of the display, people in the vicinity of display 100, and their activities. Artificial intelligence can help the dynamic generative art engine 110 and / or graphics rendering engine 112 improve image quality in real time, adjusting parameters such as contrast and color balance for optimal viewing. Artificial intelligence can be used to improve randomization functions, which can be embedded within generative art algorithms processed by the dynamic generative art engine 110. It should be understood that in some other embodiments, artificial intelligence can also be used to assist and improve the operation of other aspects of this disclosure.

[0073] It should be understood that the display 100 may also include, in addition to Figure 1 Other software components besides those shown in the diagram and those described in the other embodiments above.

[0074] Figure 2 This is an exploded perspective view showing the hardware layer of display 100. As described above, in this embodiment, the display may be a QLED display, although some of its components are customized to operate in a square 1:1 aspect ratio as described below. Starting with the rearmost components, display 100 may include a thermally conductive chassis 140 with an integrated cooling structure. References below... Figure 6 To describe the cooling structure in more detail, however, the thermally conductive chassis 140 may typically include multiple protruding surfaces to maximize surface area and passively conduct heat away from the active layer of the display 100 to the maximum extent possible. The chassis may include vents disposed along one, two, three, or all four sides to allow cooling airflow through the display 100.

[0075] The internal panel 142 can support various printed circuit boards, including circuitry for controlling the operation of the display 100 (as described below). These control units 160, 162, 164a, and 164b are shown in the figures in a disassembled state from the display 100, but can actually be mounted on the inner or outer surface of the panel 142.

[0076] The QLED display 100 may also include a backlight unit 144, which may include an array of LEDs providing illumination to the display. As described below, these LEDs may emit blue light to the quantum dot layer. In one embodiment, a square array of 9216 mini-LEDs is used; however, in other embodiments, more or fewer LEDs may be present.

[0077] The light guide plate (or light diffusion layer) 146 is located between the backlight unit 144 and the quantum dot layer 148. Its main function is to distribute the light from the backlight evenly across the entire surface of the display, thereby ensuring uniform brightness and minimizing any hot spots or uneven lighting.

[0078] The quantum dot layer 148 receives blue light emitted from the backlight unit 144 via the light diffusion layer 146. The quantum dot layer 148 contains nanoparticles that convert the blue light into high-purity red and green light, which, when mixed, generate the RGB spectrum required by the display 100. The quantum dot layer 148 has been customized to be square and has a 1:1 aspect ratio for this disclosure.

[0079] The next layer is polarizer 150. Polarizers are used to reduce halo effects from backlight. They reduce stray light and enhance contrast and sharpness in the displayed image by selectively filtering and adjusting the light incident on the LCD layer (described below). By improving light control, it ensures deeper blacks, more accurate colors, and clearer transitions between bright and dark areas.

[0080] The open-cell LCD layer 152 in the QLED display 100 is a multi-layered, thin structure that modulates light to generate an image. It consists of two glass substrates (one shown at 154) sandwiching the liquid crystal layer, with electrodes for controlling crystal alignment and polarizers for managing light transmission. An array of color filters assigns red, green, or blue to sub-pixels, combining to form a full-color image. By dynamically adjusting the alignment of the liquid crystals using an electric field, this layer controls the brightness and color of each pixel, providing a clear and vivid visual effect. As mentioned above, like other layers, layer 152 can also be customized as a square with a 1:1 aspect ratio.

[0081] As described above, layer 154 can be a glass layer forming part of LCD layer 152 and can form the front surface of QLED display 100. It can be coated with one or more layers of film to achieve anti-glare, anti-reflection, and anti-fingerprint functions, thereby optimizing the viewing experience of the visual image formed by LCD layer 152. Layer 154 can also be polarized to filter out unwanted light transmission. The front bezel 156 provides an aesthetically pleasing appearance and can seal the layers of display 100 within the chassis 140.

[0082] As described above, the QLED display 100 may also include various control units and sensors. Controllers 160, 162, 164a, and 164b can be mounted to the internal panel 142 and electrically connected to the internal layers of the display 100. Controllers 160, 162a, and 162b collectively control the operation of the backlight layer 144. The separation of the controllers indicates that they are located on different printed circuit boards (PCBs). Controller 160, based on a field-programmable gate array (FPGA), can be mounted on the first PCB and can act as the main controller controlling the overall operation of the backlight layer 144. Sub-controller 162a can be mounted on the second PCB and can drive the operation of the first half of the display (e.g., the left side). Furthermore, sub-controller 162b can be mounted on the third PCB and can drive the operation of the second half of the display (e.g., the right side). It should be understood that in some other embodiments, the backlight controllers may be integrated together on a single PCB or otherwise partitioned onto different PCBs.

[0083] Controllers 160, 162a, and 162b jointly control the operation of the backlight layer 144. One of their main control functions is to minimize the delay between the video signal sent to the LCD layer 152 and the electrical signal sent to the micro-LED array of the backlight layer 144. Backlight controllers are typically configured to control 16:9 aspect ratio displays. Controllers 160, 162a, and 162b have been customized for use with the square display 100 of this disclosure.

[0084] Controller 164 may be a main controller for display 100, comprising a system-on-a-chip (SoC) including a processor 102, a GPU 104, and memory 106 mounted on a PCB. The PCB may also accommodate other supporting components, some of which will be integrated with… Figure 7 As described below.

[0085] A key feature of this disclosure is that the GPU 104 is mounted on a PCB inside the display 100. Specifically, the GPU 104 is a powerful GPU capable of supporting generative art, requiring far more real-time computing and rendering capabilities than those needed for still images or pre-rendered video. Televisions (TVs) and displays have historically featured basic integrated GPUs, but none have possessed the high-end GPUs used in the display 100, capable of rendering dynamic art with extensive use of vertex and pixel shaders. Devices primarily used as displays (such as televisions, computer monitors, or billboards) do not feature high-performance GPUs with a large number of shader units. Entry-level GPUs commonly found in traditional displays cannot render the generative art of this disclosure at satisfactory frame rates. Displays attempting to render generative art always require connection to an external computer equipped with a GPU via input modes such as HDMI or USB.

[0086] As described above, the display 100 may include multiple sensors 120. These sensors include an mmWave sensor 120a, an ambient light sensor 120b, and a microphone 120c. In some other embodiments, more than one type of sensor may be present. For example, a light sensor may be positioned diagonally opposite each other on the display 100. These sensors in Figure 2 The images are illustrated schematically by way of example, and it should be understood that these sensors can be positioned in various locations (without obstructing the viewing angle of the artistic images / videos presented on display 100). In some other embodiments, display 100 may also include other sensors.

[0087] As described above, all hardware layers and control devices in this disclosure are customized to provide a rectangular display with a 1:1 aspect ratio. Natively outputting a rectangular resolution is not easy, as most display hardware has been standardized to a 16:9 resolution. Past GPUs and display controllers have been optimized for standard rectangular resolutions. Creating a rectangular display requires custom firmware and hardware modifications to achieve native rectangular resolution output. Only through such modifications can the GPU 104 and other rendering components run at a native rectangular resolution, thus enabling the design of a rectangular display area.

[0088] Furthermore, traditional devices that included resized LCDs simply stretched 16:9 images to the new aspect ratio, resulting in degraded visual quality and a loss of pixel density. Providing a square display area necessitates a redesign of the backlight layer 144, quantum dot layer 148, and LCD layer 152. Through this redesign, the artwork in this disclosure can be presented at the exact same resolution as the physical output.

[0089] Figure 3 This is a flowchart describing the steps an artist takes in generating a generative art algorithm. In step 200, the artist conceives the artwork using a concept and defines the artistic vision. In step 202, the artist selects a programming environment, such as p5.js or Three.js. In step 204, the artist designs the algorithm components. The artist can define layers and attributes and formulate rules defining the generation of the artwork. Here, the artist can also set a randomization function. In step 208, the artist can integrate sensor data from the API onto display 100. As described above, the API can be generated, for example, at generative art server 132 or display 100, for use by artists designing generative art to be presented on display 100. This API allows the artist to access display 100 or server 132, enabling the artist to identify sensors and define the sensor inputs the artist will include in the generative art algorithm.

[0090] In step 210, the artist can develop the core algorithm, including generative functions for visual elements of the artwork, and an integration of input and randomization functions for contextual data. In step 212, the artist can implement interactivity in response to sensor feedback. Here, the artist can define how the artwork will vary in response to specific contextual inputs. In step 214, the artist can test the generative artwork, for example, by testing to ensure real-time rendering capabilities and to test its response to different contextual data. In step 218, the artist can finalize and deploy the generative art algorithm. As described above, the generative art algorithm can be stored on a third-party art content provider site 134, stored on a generative art server 132, or directly downloaded to the data storage 116 of the display 100. It is conceivable that samples of the artwork will be uploaded to a directory (e.g., stored on the generative art server 132).

[0091] As described above, in some other embodiments, Figure 3 Some or all of the steps in the process can be executed by an artificial intelligence processor.

[0092] Figure 4 This is a flowchart illustrating how the generative art engine 110 within display 100 selects and processes generative art algorithms, including providing sensor input for adjusting the generative artwork within the generative art algorithm. In step 230, the system can be initialized, for example, by turning on display 100, launching a software engine such as generative art engine 110, and activating sensor 120. In step 232, the sensor can analyze the display position and receive feedback on parameters such as the number of people and their activities, light levels, temperature, and noise levels in the room. The received contextual data can be processed by sensor integration controller 114 into unified data usable by the generative art algorithm.

[0093] In step 234, the dynamic generative art engine 110 can analyze sensor input to categorize the ambient atmosphere of the display location. The engine 110 can then select artworks from categories corresponding to that atmosphere. If multiple artworks exist within a defined category, the engine 110 can prioritize selections based on artist-provided meta-tags, system parameters (curator preferences, rotation schedules, or content usage history), and randomization or weighting algorithms, ensuring a diverse and engaging rotation of artworks while adhering to the categorized atmosphere. Other factors can also be considered when prioritizing artworks for selection from a given category. As mentioned above, artificial intelligence can also be used in this process. Once a generative art algorithm is selected, it can be retrieved from data storage 116 in memory 106 in step 236, or downloaded from a remote site (server 132 or third-party content provider 134).

[0094] In step 238, engine 110 can execute the selected generative art algorithm and perform randomization according to its randomization function to ensure that the display does not simply repeat past presentations. In step 240, the dynamic generative art engine 110 (in real time) analyzes the contextual input to determine if the contextual input has changed. If so, the presentation of the artwork can change or evolve in response to the change in contextual input in step 244. As mentioned above, the change in the artwork may be affected by sensitivity measures or time periods. If the contextual input has not changed in step 240, adjustment step 244 can be skipped.

[0095] In step 246, the artwork can be rendered by graphics rendering engine 112. Engine 110 can check in step 248 whether the curator or other user wishes to change the artwork. If not, the process can return to step 238 to continue executing the selected generative art algorithm.

[0096] On the other hand, if a change is requested in step 248, engine 110 can check in step 250 whether the curator or user wishes to manually select an artwork. If not, the process returns to step 234 and a new generative art algorithm is selected (while recording the content selection history to avoid repeatedly selecting the same artwork). If a manual selection is received in step 250, the identifier of the selected artwork is received in step 252, and the process returns to step 236 to load the newly selected generative art algorithm.

[0097] As described above, in some other embodiments, Figure 4Some or all of the steps in the process can be executed independently by the artificial intelligence processor, or in collaboration with the dynamic generative art engine 110.

[0098] Figure 5 This is a front view of a display 100 showing an artwork 170 created according to the generative art algorithm described above. It should be understood that any type of art can be presented on the display 100 according to this disclosure. The display 100 can be suspended from a wall by a hook or similar device, or suspended in the air by a line or rope fixed to a wall or ceiling.

[0099] Figure 6 This is a rear view of the display 100 showing a thermally conductive chassis 140. The chassis 140 includes a plurality of raised surfaces 172 defined by a low-elevation recessed portion 174. The raised surfaces 172 and the recessed portion 174 together provide a larger surface area for dissipating heat from the display 100. In one embodiment, the height of the raised surface 172 relative to the recessed portion 174 can be between 0.5 inches and 2 inches, although in some other embodiments, this height difference can be larger or smaller. In an embodiment, the raised surface 172 can be square, and its length and width can be between 1 inch and 5 inches, although in some other embodiments, these dimensions can be larger or smaller. The thermally conductive chassis can be made of a thermally conductive material, such as aluminum, copper, graphite, or stainless steel. Other materials can also be used. Although the raised surfaces shown in the figure are square, in some other embodiments, the raised surfaces can also be other geometries, including rectangular and circular shapes.

[0100] While the passive cooling system described above may be preferred due to its lack of noise, fan units may also be included in some other embodiments. Fan units with low noise emissions can be used. Another cooling solution employs an ionization-based airflow system with no moving parts. Such units are available from Ventiva Corporation in Fremont, California.

[0101] Figure 7 An exemplary computing system 300 is shown, which may be a display 100 or other server for implementing embodiments of this disclosure. Figure 7 The computing system 300 includes one or more processors 310 and main memory 320. Main memory 320 partially stores instructions and data executed by the processor units 310. When the computing system 300 is running, main memory 320 may store executable code. Figure 7 The computing system 300 may also include a mass storage device 330, a portable storage medium drive 340, an output device 350, a user input device 360, a display system 370, and other peripheral devices 380.

[0102] Figure 7 The components shown are depicted as being connected via a single bus 390. Components may be connected via one or more data transfer devices. Processor unit 310 and main memory 320 may be connected via a local microprocessor bus, and mass storage device 330, peripheral device 380, portable storage media drive 340 and display system 370 may be connected via one or more input / output (I / O) buses.

[0103] Mass storage device 330, which can be implemented using a solid-state drive, disk drive, or optical disk drive, is a non-volatile storage device used to store data and instructions for use by processor unit 310. Mass storage device 330 can store system software used to implement embodiments of the present invention, so that the software can be loaded into main memory 320.

[0104] The portable storage media drive 340 works in conjunction with portable non-volatile storage media (such as external hard drives, external SSDs, or USB flash drives) to deliver... Figure 7 The computing system 300 inputs data and code, and from Figure 7 The computing system 300 outputs data and code. System software used to implement embodiments of the present invention can be stored on such a portable medium and input to the computing system 300 via a portable storage medium drive 340.

[0105] Input devices 360 form part of the user interface. Input devices 360 may include alphanumeric keypads (such as a keyboard for entering alphanumeric and other information) or pointing devices (such as a mouse, trackball, stylus, or cursor arrow keys). Additionally, as... Figure 7 The system 300 shown includes an output device 350. Suitable output devices include speakers, printers, network interfaces, and displays. When the computing system 300 is part of a mechanical client device, the output device 350 may also include servo controls for motors within that mechanical device.

[0106] The display system 370 may include a liquid crystal display (LCD) or other suitable display device. The display system 370 receives text and graphic information and processes the information to output it to the display device.

[0107] One or more peripheral devices 380 may include any type of computer support device to add additional functionality to the computing system. Peripheral device 380 may include a modem or a router.

[0108] Figure 7The components included in the computing system 300 are common components in computing systems and can be applied to embodiments of the present invention, intended to represent a broad category of such computer components well known in the art. Therefore, Figure 7 The computing system 300 can be a personal computer, handheld computing device, telephone, mobile computing device, workstation, server, minicomputer, mainframe computer, or any other computing device. The computer can also include different bus configurations, networking platforms, multiprocessor platforms, etc. Various operating systems can be used, including UNIX, Linux, Windows, MacOS, FreeBSD, and other suitable operating systems.

[0109] Some of the functions described above may consist of instructions stored on a storage medium (e.g., a computer-readable medium). These instructions can be retrieved and executed by a processor. Some examples of storage media are memory devices, magnetic tapes, disks, etc. The instructions are operable when executed by a processor to instruct the processor to operate according to the present invention. Those skilled in the art are familiar with instructions, processors, and storage media.

[0110] It should be noted that any hardware platform suitable for performing the processes described herein is applicable to this invention. The term "computer-readable storage medium" as used herein refers to any one or more media that participate in providing instructions to a CPU for execution. These media can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks, such as fixed disks. Volatile media include dynamic memory, such as system RAM. Transmission media include coaxial cables, copper wires, and optical fibers, including conductors in one embodiment that comprise a bus. Transmission media can also take the form of sound waves or light waves, such as sound waves or light waves generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, SSDs, floppy disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, digital video disks (DVDs), any other optical media, any other physical media with markings or perforation patterns, RAM, PROMs, EPROMs, EEPROMs, FLASHEPROMs, any other memory chips or cassette tapes, carrier waves, or any other media that a computer can read.

[0111] Various forms of computer-readable media may involve delivering one or more sequences of one or more instructions to a CPU for execution. A bus transfers data to system RAM, from which the CPU retrieves and executes instructions. Instructions received in system RAM may be selectively stored on a fixed disk before or after execution by the CPU.

[0112] In general, one embodiment of this disclosure relates to a square display for rendering generative art, the square display comprising: a backlight layer customized for a square display area; one or more processors integrated within the square display; a graphics processing unit (GPU) integrated within the square display configured to render generative art; and a light sensor configured to match illumination at a location on the square display with optimized lighting for rendering the generative art.

[0113] In another example, the present invention relates to a display for presenting generative art, the display comprising: one or more environmental sensors and one or more processors; the one or more processors being configured to execute code to: run a generative art algorithm to generate a generative artwork; render the generative artwork; modify the generative artwork in response to input from the one or more environmental sensors; and modify the generative artwork in response to a randomization function included in the generative art algorithm.

[0114] In another example, the present invention relates to a display for presenting generative art, the display comprising: one or more environmental sensors and one or more artificial intelligence (AI) processors; the one or more AI processors being configured to execute code to: generate a generative art algorithm; run the generative art algorithm to generate a generative artwork; render the generative artwork; modify the generative artwork using AI in response to input from one or more environmental sensors; and modify the generative artwork in response to a randomization function included in the generative art algorithm; wherein modifying the generative artwork in response to input from one or more environmental sensors and modifying the generative artwork in response to the randomization function ensures that the artwork modified during the display's usage period does not repeatedly display previously shown images or videos.

[0115] The foregoing description is illustrative and not restrictive. Many variations of the invention will become apparent to those skilled in the art upon reading this disclosure. Therefore, the scope of the invention should not be determined by reference to the foregoing description, but rather by reference to the appended claims and their full scope of equivalents. Although the invention has been described in conjunction with a series of embodiments, these descriptions are not intended to limit the scope of the invention to the specific forms set forth herein. It should also be understood that the methods of the invention are not necessarily limited to the discrete steps or the order of steps described. Rather, these descriptions are intended to cover such alternatives, modifications, and equivalents that may be included within the spirit and scope of the invention as defined by the appended claims and as understood by those skilled in the art.

[0116] Those skilled in the art will recognize that an Internet service can be configured to provide Internet access to one or more computing devices connected to the Internet service, and that computing devices may include one or more processors, buses, memory devices, display devices, input / output devices, etc. Furthermore, those skilled in the art will understand that the Internet service can connect to one or more databases, repositories, servers, etc., which can be used to implement any embodiment of the invention described herein.

Claims

1. A square display for presenting generative art, comprising: The backlight layer is customized for use in square display areas; One or more processors integrated within the square display; A graphics processing unit (GPU) integrated within the square display is configured to render the generative art. and A light sensor is configured to match the illumination at a location on the square display with optimized lighting used to present the generative art.

2. The square display according to claim 1, further comprising a millimeter-wave sensor within the square display, the millimeter-wave sensor being used to sense the number of people present at a certain location on the square display, and the activity of one of the one or more people.

3. The square display of claim 2, further comprising a software engine configured to alter the generative art presented on the square display when a sensor reading from at least one of the light sensor and the millimeter-wave sensor changes.

4. The square display according to claim 1, further comprising an LCD layer, the LCD layer being customized for use with the square display.

5. The square display according to claim 1 further includes a backlight controller. in, The backlight controller is customized to fit the square backlight layer.

6. The square display according to claim 1, further comprising a thermally conductive frame, the thermally conductive frame including a raised surface surrounded by a recessed portion for conducting heat away from the square display.

7. A display for presenting generative art, comprising: One or more environmental sensors; and One or more processors are configured to execute code to: Run generative art algorithms to generate generative artworks; Render the generative artwork; The generative artwork is altered in response to input from one or more environmental sensors; as well as The generative artwork is modified in response to the randomization function included in the generative art algorithm.

8. The display according to claim 7, wherein, The generative artwork is modified in response to input from one or more environmental sensors and in response to the randomization function, such that the artwork changes during the usage cycle of the display without repeating previously displayed images or videos.

9. The display according to claim 7, wherein, The generative art algorithm generates artworks that are categorized into one type.

10. The display according to claim 9, wherein, The generative art algorithm was chosen because its classification matches the ambient atmosphere of a particular location on the display.

11. The display according to claim 7, wherein, The generative art algorithm detects the input from one or more environmental sensors in the display via an application programming interface.

12. The display according to claim 7, wherein, The one or more environmental sensors include optical sensors.

13. The display according to claim 7, wherein, The one or more environmental sensors include millimeter-wave sensors.

14. The display according to claim 7, wherein, The one or more environmental sensors include a microphone.

15. The display according to claim 7, wherein, The display is a quantum light-emitting diode (QLED) type display.

16. A display for presenting generative art, the display comprising: One or more environmental sensors; and One or more artificial intelligence (AI) processors are configured to execute code to: Generative art algorithm; run the generative art algorithm to generate generative artwork; Render the generative artwork; in response to input from the one or more environmental sensors, use artificial intelligence to alter the generative artwork; as well as The generative artwork is modified in response to the randomization function included in the generative art algorithm; The generative artwork is modified in response to input from one or more environmental sensors, and in response to the randomization function, such that the artwork changes during the usage cycle of the display without repeating previously displayed images or videos.

17. The display according to claim 16, wherein, The generative art algorithm uses artificial intelligence to generate artworks that can be categorized into a single category.

18. The display according to claim 17, wherein, The generative art algorithm was chosen because its classification matches the ambient atmosphere of a particular location on the display.

19. The display according to claim 16, wherein, The display is a quantum light-emitting diode (QLED) type display.

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