Abstract: This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can utilize artificial intelligence to generate user-specific content based on content collections associated with a user account. Indeed, in one or more implementations, the disclosed systems utilize machine learning to intelligently generate new, custom content items that emulate user-specific content attributes based on content collections associated with a user account. In some instances, the disclosed systems utilize a content generation model that is trained to generate new content items in response to user requests (e.g., requests that describe one or more features).

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for providing a creativity web browser for content creation that integrates features of a content management system with internet browsing capabilities. Specifically, the disclosed systems provide a creativity web browser that includes specialized interface elements for restructuring web browsing to focus on content-related context, including a digital canvas, a content collection pane, an x-ray pane, and other elements. The disclosed systems can provide access to browsing across multiple systems or platforms, such as internet locations and/or locations within a content management system, within an integrated web browsing environment.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for consolidating freelancer information of a plurality of freelancer data categories in a centralized environment for performing various tasks in relation to freelancer development. For example, the disclosed systems can determine interaction parameters based on user interactions associated with a freelancer account and determine freelancer information associated with a plurality of freelancer data categories. In certain cases, the disclosed systems can analyze the interaction parameters and freelancer information to generate a suggested action associated with a first freelancer data category from the plurality of freelancer data categories. The disclosed systems can also provide for display a freelancer account summary interface comprising a notification of the suggested action with a predicted result associated with the first freelancer data category.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for providing a creativity web browser for content creation that integrates features of a content management system with internet browsing capabilities. Specifically, the disclosed systems provide a creativity web browser that includes specialized interface elements for restructuring web browsing to focus on content-related context, including a digital canvas, a content collection pane, an x-ray pane, and other elements. The disclosed systems can provide access to browsing across multiple systems or platforms, such as internet locations and/or locations within a content management system, within an integrated web browsing environment.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for providing a creativity web browser for content creation that integrates features of a content management system with internet browsing capabilities. Specifically, the disclosed systems provide a creativity web browser that includes specialized interface elements for restructuring web browsing to focus on content-related context, including a digital canvas, a content collection pane, an x-ray pane, and other elements. The disclosed systems can provide access to browsing across multiple systems or platforms, such as internet locations and/or locations within a content management system, within an integrated web browsing environment.

Abstract: A system for allowing product managers and software engineers to search for existing software modules that meet desired parameters and to identify opportunities to develop new software modules is provided. When product developer creates a software component they assign combinations of tags to the software component in a predetermined format and structure that describes features of the component such as the entity that would use the component, actions that are performed by the component, objects used by the component, and desired outcomes of the component. These tags are associated with the software component in the system. Later, when a developer has a need or idea for a particular component, the developer uses the system to construct a sentence that describes the features of the component as described above. The system then identifies any existing components that match or are close matches to the described component.

Abstract: The grounding clamp system is for use with an electrically insulated pole and for attachment to an electrical conductor in angled configurations. The grounding clamp system includes a clamping mechanism having an actuatable clamp and an associated ground conductor connector. An attachment coupler is configured to attach to the electrically insulated pole, and an angular adjustment mechanism is coupled between the clamping mechanism and the attachment coupler. The adjustment mechanism is configured to provide angular adjustment between the clamping mechanism and the attachment coupler in at least one axis while also transferring force to actuate the actuatable clamp when attaching the clamping mechanism to the electrical conductor at a selected angular position. The clamping mechanism is configured to create a path to pass ground fault current from the electrical conductor to a ground conductor coupled to the ground conductor connector without including the angular adjustment mechanism in the path.

Abstract: The grounding damp system is for use with an electrically insulated pole and for attachment to an electrical conductor in angled configurations. The grounding clamp system includes a damping mechanism having an actuatable damp and an associated ground conductor connector. An attachment coupler is configured to attach to the electrically insulated pole, and an angular adjustment mechanism is coupled between the clamping mechanism and the attachment coupler. The adjustment mechanism is configured to provide angular adjustment between the clamping mechanism and the attachment coupler in at least one axis while also transferring force to actuate the actuatable damp when attaching the clamping mechanism to the electrical conductor at a selected angular position. The damping mechanism is configured to create a path to pass ground fault current from the electrical conductor to a ground conductor coupled to the ground conductor connector without including the angular adjustment mechanism in the path.

Abstract: A training system is described herein for generating a prediction model that relies on a feature space with reduced dimensionality. The training system performs this task by producing partitions, each of which corresponds to a subset of aspect values (where each aspect value, in turn, may correspond to one or more attribute values). The training system then produces instances of statistical information associated with the partitions. Each instance of statistical information therefore corresponds to feature information that applies to a plurality of aspect values, rather than a single aspect value. The training system then trains the prediction model based on the feature information. Also described herein is a prediction module that uses the prediction model to make predictions in various online contexts.

Abstract: Technologies are described herein for active machine learning. An active machine learning method can include initiating active machine learning through an active machine learning system configured to train an auxiliary machine learning model to produce at least one new labeled observation, refining a capacity of a target machine learning model based on the active machine learning, and retraining the auxiliary machine learning model with the at least one new labeled observation subsequent to refining the capacity of the target machine learning model. Additionally, the target machine learning model is a limited-capacity machine learning model according to the description provided herein.

Abstract: Technologies for an application reputation service to assist users with minimizing their computerized machines' exposure to and infection from malware, including an application reputation service that contains the reputations for elements (e.g., applications) that are known to be non-malicious as well as those known to be malicious. In one example, when a user attempts to install or execute a new application, the service is queried by the user's machine with a set of identities for the element. The service determines the reputation of the application by referencing a knowledge base of known reputations and returns an indication (e.g., an overall rating, or a flag) of how safe that application would be to install and run on the user's computer.

Abstract: The present application concerns a coated film comprising a substantially biodegradable substrate having a biodegradable coating thereon at a coat weight of not more than 12 gsm, as well as useful articles sealed inside a package at least partly comprising such a film, and also a process for producing a coated film comprising providing a substantially biodegradable film substrate and applying a biodegradable coating to the substrate at a coat weight of less than 12 gsm by means of a hot melt coating step.

Abstract: Systems and methods of pre-launching applications in a computer system, said applications being likely to be activated by a user from a terminated and/or suspended process state, are disclosed. The pre-launching of an application may be based on the assessed probability of the application being activated—as well as the level of availability of system resources to affect such pre-launching. Applications may be pre-launched based on these and other conditions/considerations, designed to improve the user's experience of a quick launch of applications in the background. Several prediction models are presented to provide a good estimate of the likelihood of an application being activated by a user. Such prediction models may comprise an adaptive predictor (based on past application usage situations) and/or a switch rate predictor (based on historic data of an application being switched and, possibly, having a decay rate applied to such switch rate measure).

Abstract: Architecture that monitors interaction data (e.g., search queries, query results and click-through rates), and provides users with links to other users that fall into similar categories with respect to the foregoing monitored activities (e.g., providing links to individuals and groups that share common interests and/or profiles). A search engine can be interactively coupled with one or more social networks, and that maps individuals and/or groups within respective social networks to subsets of categories associated with searches. A database stores mapped information which can be continuously updated and reorganized as links within the system mapping become stronger or weaker. The architecture can comprise a social network system that includes a database for mapping search-related information to an entity of a social network, and a search component for processing a search query for search results and returning a link to an entity of a social network based on the search query.

Abstract: Technologies are described herein for active machine learning. An active machine learning method can include initiating active machine learning through an active machine learning system configured to train an auxiliary machine learning model to produce at least one new labeled observation, refining a capacity of a target machine learning model based on the active machine learning, and retraining the auxiliary machine learning model with the at least one new labeled observation subsequent to refining the capacity of the target machine learning model. Additionally, the target machine learning model is a limited-capacity machine learning model according to the description provided herein.

Abstract: Systems and methods allow an on-line game to extract information relevant to a specific need of a game platform or service platform. The specific need relates to management and use of digital content, and is addressed by designing and playing an on-line collaborative game. The rules of the game intend to solve a specific task dictated by the specific need. Players' responses to the game generate a wealth of information related to a specific task objective, such as ranking, sorting, and evaluating a set of digital content items. To compel participation in a game, players can be rewarded with monetary value rewards. As a game illustration, an image selection game (ISG) that exploits human contextual inference is described in detail. The information extracted from ISG is a list of key-image associations, relevant for the task of image sorting and ranking.

Abstract: A system is described for allowing a user, operating a trusted device, to remotely log into a server via a potentially untrustworthy client. A first secure connection is established between the client and the server. A second secure connection is established between the device and the server through the client. The user then remotely logs into the server over the second secure connection using the device. The second secure connection is tunneled within the first secure connection, preventing the untrustworthy client from discovering personal information associated with the user. According to one feature, prior to forming the second secure connection, the user establishes a pairing relationship with the client by reading an address of the client using a reading mechanism. According to another feature, the device can receive marketing information in the course of a transaction.