The present application relates generally to In-Game Asset tracking using NFTs that track impressions across multiple platforms.
Non-fungible tokens (NFT) are the digital world's version of physical collectables, such as but not limited to artwork. An NFT is a digital file in a block chain that proves who owns the underlying digital asset, much as a sales receipt proves ownership of a physical painting, although forging NFT proof-of-ownership is nearly impossible owing to the use of block chain technology. Like a print or painting, ownership of an NFT does not necessarily include copyright in the original work, which copyright may be retained by the creator. While anyone can view the digital asset, only the person identified in the NFT can sell the ownership of the asset, which then is recorded in the block chain. Thus, digital assets can be bought and sold like physical collectables through NFT transactions.
As understood herein, in some applications, for example, computer simulations such as computer games, a player or spectator might find it interesting who has possessed an NFT related to the game in the past, in a clean, intuitive presentation. Such an NFT may facilitate tracking gamer/spectator impressions.
Accordingly, a system includes at least one computer medium that is not a transitory signal and that in turn instructions executable by at least one processor to input to at least a first machine learning (ML) model at least one non-fungible token (NFT) representing at least one digital asset related to at least one computer simulation. The instructions are executable to receive from the ML model information from the NFT indicating aspects of a lifetime of the NFT, and to present on at least one computer display the information.
In example embodiments the instructions can be executable to receive from the ML model information from the NFT indicating aspects of a lifetime of the NFT. The information from the NFT may be derived from some but not all metadata associated with the NFT.
In some implementations the instructions can be executable to present on at least one computer display the information from the NFT. The information may include at least one user interface (UI) that presents a list of at least some owners of the NFT. In some examples, the UI presents a respective period for which each respective owner owned the NFT. In non-limiting embodiments the UI presents a respective game and/or game scene associated with acquisition of the NFT by the respective owner. If desired, the UI can present a respective event in a game associated with acquisition of the NFT.
In some embodiments, the instructions can be executable to, responsive to selection from the UI, present a secondary UI surfacing elements of the information related to the selection.
In examples, the instructions may be executable to present on at least one computer display the information from the NFT in a UI that presents a timeline which includes spikes each of which represents an important event in the NFT. In such examples, the instructions may be executable to receive selection of a first spike in the timeline, and responsive to the selection, present a secondary UI presenting information associated with the first spike.
In another aspect, a method includes inputting to at least one machine learning (ML) model at least one training set of data including metadata of non-fungible tokens (NFT) associated with computer simulation assets and ground truth interesting elements therein. The method includes training the ML model using the training set. Subsequent to training, the method includes inputting to the ML model at least one NFT comprising metadata and presenting metadata output by the ML model for a user to hear or visualize or feel important events in a life of the NFT.
If desired, user feedback can be added into the ML model to continuously improve the model over time. User feedback could be: viewable impressions, focus events, click events etc.
In another aspect, an assembly includes at least one display and at least one processor programmed with instructions to present on the display information associated with at least one non-fungible token (NFT) derived to represent at least one digital asset in a computer game.
The details of the present application, both as to its structure and operation, can be best understood in reference to the accompanying drawings, in which like reference numerals refer to like parts, and in which:
This disclosure relates generally to computer ecosystems including aspects of consumer electronics (CE) device networks such as but not limited to computer game networks. A system herein may include server and client components which may be connected over a network such that data may be exchanged between the client and server components. The client components may include one or more computing devices including game consoles such as Sony PlayStation® or a game console made by Microsoft or Nintendo or other manufacturer, virtual reality (VR) headsets, augmented reality (AR) headsets, portable televisions (e.g., smart TVs, Internet-enabled TVs), portable computers such as laptops and tablet computers, and other mobile devices including smart phones and additional examples discussed below. These client devices may operate with a variety of operating environments. For example, some of the client computers may employ, as examples, Linux operating systems, operating systems from Microsoft, or a Unix operating system, or operating systems produced by Apple, Inc., or Google. These operating environments may be used to execute one or more browsing programs, such as a browser made by Microsoft or Google or Mozilla or other browser program that can access websites hosted by the Internet servers discussed below. Also, an operating environment according to present principles may be used to execute one or more computer game programs.
Servers and/or gateways may include one or more processors executing instructions that configure the servers to receive and transmit data over a network such as the Internet. Or a client and server can be connected over a local intranet or a virtual private network. A server or controller may be instantiated by a game console such as a Sony PlayStation®, a personal computer, etc.
Information may be exchanged over a network between the clients and servers. To this end and for security, servers and/or clients can include firewalls, load balancers, temporary storages, and proxies, and other network infrastructure for reliability and security. One or more servers may form an apparatus that implement methods of providing a secure community such as an online social website to network members.
A processor may be a single- or multi-chip processor that can execute logic by means of various lines such as address lines, data lines, and control lines and registers and shift registers.
Components included in one embodiment can be used in other embodiments in any appropriate combination. For example, any of the various components described herein and/or depicted in the Figures may be combined, interchanged, or excluded from other embodiments.
“A system having at least one of A, B, and C” (likewise “a system having at least one of A, B, or C” and “a system having at least one of A, B, C”) includes systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.
Now specifically referring to
Accordingly, to undertake such principles the AVD 12 can be established by some, or all of the components shown in
In addition to the foregoing, the AVD 12 may also include one or more input and/or output ports 26 such as a high-definition multimedia interface (HDMI) port or a USB port to physically connect to another CE device and/or a headphone port to connect headphones to the AVD 12 for presentation of audio from the AVD 12 to a user through the headphones. For example, the input port 26 may be connected via wire or wirelessly to a cable or satellite source 26a of audio video content. Thus, the source 26a may be a separate or integrated set top box, or a satellite receiver. Or the source 26a may be a game console or disk player containing content. The source 26a when implemented as a game console may include some or all of the components described below in relation to the CE device 48.
The AVD 12 may further include one or more computer memories 28 such as disk-based or solid-state storage that are not transitory signals, in some cases embodied in the chassis of the AVD as standalone devices or as a personal video recording device (PVR) or video disk player either internal or external to the chassis of the AVD for playing back AV programs or as removable memory media or the below-described server. Also, in some embodiments, the AVD 12 can include a position or location receiver such as but not limited to a cellphone receiver, GPS receiver and/or altimeter 30 that is configured to receive geographic position information from a satellite or cellphone base station and provide the information to the processor 24 and/or determine an altitude at which the AVD 12 is disposed in conjunction with the processor 24. The component 30 may also be implemented by an inertial measurement unit (IMU) that typically includes a combination of accelerometers, gyroscopes, and magnetometers to determine the location and orientation of the AVD 12 in three dimension or by an event-based sensors.
Continuing the description of the AVD 12, in some embodiments the AVD 12 may include one or more cameras 32 that may be a thermal imaging camera, a digital camera such as a webcam, an event-based sensor, and/or a camera integrated into the AVD 12 and controllable by the processor 24 to gather pictures/images and/or video in accordance with present principles. Also included on the AVD 12 may be a Bluetooth transceiver 34 and other Near Field Communication (NFC) element 36 for communication with other devices using Bluetooth and/or NFC technology, respectively. An example NFC element can be a radio frequency identification (RFID) element.
Further still, the AVD 12 may include one or more auxiliary sensors 38 (e.g., a motion sensor such as an accelerometer, gyroscope, cyclometer, or a magnetic sensor, an infrared (IR) sensor, an optical sensor, a speed and/or cadence sensor, an event-based sensor, a gesture sensor (e.g., for sensing gesture command), providing input to the processor 24. The AVD 12 may include an over-the-air TV broadcast port 40 for receiving OTA TV broadcasts providing input to the processor 24. In addition to the foregoing, it is noted that the AVD 12 may also include an infrared (IR) transmitter and/or IR receiver and/or IR transceiver 42 such as an IR data association (IRDA) device. A battery (not shown) may be provided for powering the AVD 12, as may be a kinetic energy harvester that may turn kinetic energy into power to charge the battery and/or power the AVD 12. A graphics processing unit (GPU) 44 and field programmable gated array 46 also may be included. One or more haptics generators 47 may be provided for generating tactile signals that can be sensed by a person holding or in contact with the device.
Still referring to
Now in reference to the afore-mentioned at least one server 52, it includes at least one server processor 54, at least one tangible computer readable storage medium 56 such as disk-based or solid-state storage, and at least one network interface 58 that, under control of the server processor 54, allows for communication with the other devices of
Accordingly, in some embodiments the server 52 may be an Internet server or an entire server “farm” and may include and perform “cloud” functions such that the devices of the system 10 may access a “cloud” environment via the server 52 in example embodiments for, e.g., network gaming applications. Or the server 52 may be implemented by one or more game consoles or other computers in the same room as the other devices shown in
The components shown in the following figures may include some or all components shown in
Present principles may employ various machine learning models, including deep learning models. Machine learning models consistent with present principles may use various algorithms trained in ways that include supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, feature learning, self-learning, and other forms of learning. Examples of such algorithms, which can be implemented by computer circuitry, include one or more neural networks, such as a convolutional neural network (CNN), a recurrent neural network (RNN), and a type of RNN known as a long short-term memory (LSTM) network. Support vector machines (SVM) and Bayesian networks also may be considered to be examples of machine learning models.
As understood herein, performing machine learning may therefore involve accessing and then training a model on training data to enable the model to process further data to make inferences. An artificial neural network/artificial intelligence model trained through machine learning may thus include an input layer, an output layer, and multiple hidden layers in between that that are configured and weighted to make inferences about an appropriate output.
In some cases, the digital asset 204 may be encoded as part of the data structure 200 (hereinafter for brevity, “NFT 200”) for inclusion into the block chain 200 or may be stored separately from the NFT 200 per se, in which case the NFT 200 may include a pointer 206 to a network address 208 of the digital asset 204.
The NFT 200 typically includes metadata 210 indicating ownership of the NFT 200 and hence of the digital asset 204. The metadata may include indication of the current and if desired past owners of the NFT 200, the price(s) paid for the ownership or other means by which ownership was acquired, the terms of the ownership (e.g., whether copyright does or does not accompany ownership), length of ownership, whether ownership can be transferred during the temporary period of ownership, etc.
The digital asset is associated with an NFT. The NFT may include metadata concerning the digital asset as described in reference to
Not all metadata in an NFT associated with a digital asset may be presented, to avoid over-complicating presentation to users. Present principles thus understand the need to create a clear, uncluttered story people care about, accounting for the complexity of knowledge they need to understand the presentation. To this end, machine learning (ML) may be employed to extract metadata from NFTs associated with computer game assets.
At 804
Presentation of NFT metadata may be audibly and/or visibly and/or tactilely using at least one appropriately configured computer display.
The NFT data structure can be linked to a gameplay data transport and processing system with which games report metadata about gameplay, such as activity start and end, which mechanics are being used by the player, where on the game map the user is located, etc. This data is sent from the game to our backend servers, which then use that data to power different features in the computer simulation ecosystem. In this way, the NFT logged information can access and record who was present in an event related to or spawning the NFT, corresponding activity metadata, etc. This information may be accessed from the NFT and sold to people who were present during game play or when the NFT was minted.
In addition to or alternative to buying an NFT, an NFT may be earned by a player executing an in-game task such as winning a tournament, slaying, or defeating an opponent, etc. The significance of the win can thus be frozen in time to record, e.g., a winner's first pro battle defeating reigning champion. The information included in or pointed to by the NFT may include a snapshot of the metaverse, which includes game statistics, indicating important aspects of the game such as an underdog defeating a champion, a come from behind win, etc. This information related to the recorded event can be dynamic and thus emerge as the game evolves for purposes of minting the NFT. The importance of events can be determined by how many people have accomplished a task, what sort of social value has been attributed to the task, etc.
The total record of the metaverse attending minting of an NFT may be maintained in an internal database with only memorable events being written to a block chain, with the block chain including a pointer to where the total record is stored.
Cross-platform use of the NFT and the benefits it affords may be facilitated. For example, an NFT minted on one game platform may be used with a different game platform by use of generic or common file formats such as .jpg or image files.
For special information pertaining to an asset underlying an NFT, such as a game car or game sword, attributes of the asset (car dented, sword notched) that may affect performance of the asset in-game may be transferred to a cloud server for reformatting from one game format (e.g., PlayStation) to another (e.g., Xbox). Or, the attributes may be encoded in the NFT by means of a pointer to the network location the attributes may be accessed,
Using NFTs according to present principles, “impressions” may be tracked. User generated assets used to track “impressions” in our community to be transported—how is asset being used/circulated, tied to events. Impressions may include user interactions and as mentioned above an NFT may be minted from an in-game asset or an evet attached to an object, such as a major victory using a particular weapon.
While the particular embodiments are herein shown and described in detail, it is to be understood that the subject matter which is encompassed by the present invention is limited only by the claims.
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