Abstract: Aspects of the preset document relate to social or group-based presentation of cryptographic objects. Cryptographic objects linked to members of a group are visually represented to each group member, such as in a “binder”-like presentation. Further, group activity related to the cryptographic objects is also presented to each group member. Specific object events of the group activity are detected based on searching an immutable cryptographic ledger. The object events are categorized according to value and volume of the cryptographic objects involved in the object events. With this event data (and event data for other related object events), event signifiers are assigned to object events and presented to group members. Example event signifiers include audio, persistent visuals, and/or dynamic visuals that are connected to visual representations of the cryptographic objects involved in the object events.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique extended reality environments based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique digital objects based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: Embodiments disclosed herein relate to user-centric security classifications of cryptographic token sets that represent a prediction of whether a token set is malicious. A user-centric security classification of a token set is generated according to user behaviors that characterize users involved with the token set, including users holding tokens of the token set and users creating tokens of the token set. A model is trained to recognize user behaviors of certain users whose involvement with the token set increase the likelihood that the token set is non-malicious and secure. Such user behaviors that the model is trained to recognize include high time-rank behaviors, or holding onto cryptographic tokens for extended lengths of time. Upon generation of a user-centric security classification for a token set, graphical displays of tokens or of the token set are updated to reflect the user-centric security classification.

Abstract: Disclosed herein is a social media platform profile identification and social discovery feature. Disclosed social media networks enable introduction of users that may not otherwise know one another based on commonality between those users. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Social discovery on a social network is performed via matching to similar behavior profiles in activity monitored by a block explorer. Machine learning models categorize behavior patterns observed by the block explorer into a machine recognized glossary. Social networks further recommend actions by users based on the monitored online behaviors of social connections.

Abstract: Implementations generally relate to an emoji visualizer. In some implementations, a method includes generating at least one emoji identifier (ID), wherein the at least one emoji ID is digitally signed with a private encryption key, and wherein the emoji ID is associated with a user. The method further includes displaying an emoji visualizer on a client device, wherein the emoji visualizer is a user interface for customizing background patterns for emoji IDs, and wherein the emoji visualizer comprises a window and a plurality of controls. The method further includes displaying the at least one emoji ID in the window of the emoji visualizer. The method further includes receiving one or more commands based on the plurality of controls of the emoji visualizer. The method further includes generating a background pattern for the at least one emoji ID, wherein the background pattern is based on the one or more commands.

Abstract: Disclosed herein is a social media platform profile identification feature. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Associating a digital object as a Social Media avatar, or as a profile detail enables the social media platform to index the digital object and enable users to search for the subject user with the digital object or descriptions thereof. A digital object generator builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users.

Abstract: Aspects of the preset document relate to social or group-based presentation of cryptographic objects. Cryptographic objects linked to members of a group are visually represented to each group member, such as in a “binder”-like presentation. Further, group activity related to the cryptographic objects is also presented to each group member. Specific object events of the group activity are detected based on searching an immutable cryptographic ledger. The object events are categorized according to value and volume of the cryptographic objects involved in the object events. With this event data (and event data for other related object events), event signifiers are assigned to object events and presented to group members. Example event signifiers include audio, persistent visuals, and/or dynamic visuals that are connected to visual representations of the cryptographic objects involved in the object events.

Abstract: Disclosed herein is a time-based leaderboard that ranks users based on a length of time each user has controlled or possessed a given digital object. The leaderboard includes customization options for purposes of user identification and identity connected to social network objects. The leaderboard further uses a staking feature where users provide their digital objects to universal wallets to hold for a predetermined period based on smart contract limitations. Staking improves leaderboard position. The leaderboard further enables expression and displayed of staked digital objects despite the user no longer having actual possession of the digital object. A digital object generator builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users.

Abstract: Accordingly, systems and methods for purchasing, securing, and maintaining emoji sequences is presented herein. In one or more examples, an enterprise or user can generate or purchase an emoji sequence, which can include a sequence of emojis that can be used to uniquely identify an enterprise. Once the emoji sequence has been acquired, in one or more examples, the emoji sequence can have a digital token associated with it, wherein the digital token can be derived from the emoji sequence string, in a manner that is unique and deterministic.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique digital objects based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: Disclosed concepts relate to presenting interconnected animations in an object display interface that indicate dynamic events for related objects. A platform presents an interface that includes tiles for objects that belong to object sets (e.g., a non-fungible token (NFT) collection, a set of numbered items, a limited sneaker line). Each tile includes information individually specific to a corresponding object. A platform monitors for event data that results in a change to an aggregate parameter (e.g., a floor price, an event rate) for a given object set or that specifies one or more individual events for objects belonging to the given object set. Based on detecting the event data, the platform dynamically presents animations on certain tiles corresponding to objects of the given object set, and the animations indicate the change to the aggregate parameter or indicate the individual events. Contextual and multi-level information is thus conveyed without significant visual clutter.

Abstract: Disclosed herein is a social media platform profile identification and social discovery feature. Disclosed social media networks enable introduction of users that may not otherwise know one another based on commonality between those users. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Social discovery on a social network is performed via matching to similar behavior profiles in activity monitored by a block explorer. Machine learning models categorize behavior patterns observed by the block explorer into a machine recognized glossary. Social networks further recommend actions by users based on the monitored online behaviors of social connections.

Abstract: A digital object generation platform processes a request to generate a digital object associated with an event according to criteria associated with the event for generating the digital object. If the criteria are satisfied, the platform generates the digital object based on digital media associated with the event. A user decipherable representation of the digital object is encoded to a smart contract.

Abstract: Disclosed herein is digital object generator that makes uses biometric data to generate unique digital objects based on the user specific input. In some embodiments, the biometric data is captures in real-time such as gestures or heart rate captures by wearable devices or mobile device cameras. Also, disclosed herein is a system and a method establishing a set of input types including any combination of cryptographic protocols, biometric data, image data, or multimedia data, and parameters handled by a digital object generator. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: A digital object generation platform generates a digital object associated with an event. Ownership of the digital object is assigned to a first cryptographic wallet based on attendance of a first user associated with the first cryptographic wallet at the event. When the platform detects a transfer of ownership of the digital object associated with the event to a second cryptographic wallet, the platform performs an analysis to determine attendance of a second user associated with the second cryptographic wallet at the event. The digital object is deactivated in response to the analysis returning a result indicating the second user did not attend the event.

Abstract: Disclosed herein is a social media platform profile identification feature. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Associating a digital object as a Social Media avatar, or as a profile detail enables the social media platform to index the digital object and enable users to search for the subject user with the digital object or descriptions thereof. A digital object generator builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users.

Abstract: Disclosed herein is a social media platform profile identification and social discovery feature. Disclosed social media networks enable introduction of users that may not otherwise know one another based on commonality between those users. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Social discovery on a social network is performed via matching to similar behavior profiles in activity monitored by a block explorer. Machine learning models categorize behavior patterns observed by the block explorer into a machine recognized glossary. Social networks further recommend actions by users based on the monitored online behaviors of social connections.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique digital objects based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique digital objects based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.