Abstract: The present disclosure pertains to techniques for reducing inaccuracies in context aware policies (CAP) with real-time feedforward validation in extended reality environments. In a particular aspect, a extended reality system is configured to author, by a user using the head-mounted device, a rule or policy or context aware policy (CAP) including one or more target actions and triggering context instances, capture, using one or more sensors, context history records for the user, render, by the head-mounted device, one or more validation scenes based on the rule or policy or CAP and the context history records, validate, by the user using the head-mounted device, the one or more validation scenes within an extended reality environment, and update, by the user using the head-mounted device, the rule or policy or CAP based on the validation.

Abstract: Features described herein generally relate to learning and recognizing object-centered routines. Particularly, object-centered routines can be learned and recognized by collecting data corresponding to a user. The data can include information representing interactions by the user with respect to objects in an environment. The routine can be learned by presenting a visual graph to the user. The user can define nodes associating an interaction with an object, specify a relationship between nodes, and arrange the nodes into segments. The visual graph can be stored, and a routine can be recognized based on the visual graph.

Abstract: The present disclosure relates to refining context aware policies in extended reality systems. In one aspect, an extended reality system is provided that performs operations including: accessing data collected from user interactions while using a context aware policy in an extended reality environment, determining a support set and confidence score for the context aware policy based on the data, generating replacement policies for the context aware policy, determining a support set and confidence score for each of the replacement policies based on the data, identifying a replacement policy from the replacement policies as a replacement for the context aware policy based on the support sets and confidence scores, and updating one or more conditions or an action defined by the context aware policy with a modified version of the one or more conditions or the action defined by the replacement policy to generate an updated context aware policy.

Abstract: Features described herein generally relate to predicting policies with an artificial intelligence (AI) platform based on shared or similar interactions. Particularly, data that includes information about users and a corpus of policies is collected, embeddings are generated for the collected data, and policies are predicted based on the embeddings. The policies can be predicted based on content-based filtering, collaborative filtering, and/or game theory approaches.

Abstract: The present disclosure relates to defining and modifying behavior in an extended reality environment. The systems and methods include capturing, using the one or more audio sensors, a natural language explanation of a rule or policy from the user, extracting features from the natural language explanation of the rule or policy, wherein the features include one or more conditions, one or more actions, and connections between the one or more events, conditions, and actions, predicting a control structure comprised of one or more conditional statements based on the extracted features and model parameters learned from historical rules or policies, and generating the rule or policy based on the control structure, wherein the rule or policy comprises the one or more conditional statements for executing the one or more actions based on evaluation of the one or more conditions.

Abstract: The present disclosure relates to systems and methods for defining and modifying behavior in an extended reality environment. The systems and methods include receiving a request to build or modify a rule or policy for a given user or activity, obtaining a template based on the user or the activity, displaying the template and tools for editing the template, receiving a modification to the template via the user interacting with the tools of the user interface, and modifying the template based on the modification to generate the rule or policy. The modification includes changing the initial value for the actions or the conditions of the template and saving the template as a separate instance representative of the rule or policy, and the rule or policy includes one or more conditional statements for executing one or more of the actions based on evaluation of one or more of the conditions.

Abstract: Features described herein generally relate to generating and modifying policies with an artificial intelligence (AI) platform based on user activities. Particularly, data comprising characteristics of activities performed by a user in real-world and virtual environments is collected, a control structure is predicted based on the data and model parameters learned from historical policies, and a new policy is generated or a pre-existing policy is modified based on the control structure.

Abstract: Techniques are provided for using a virtual assistant to optimize multi-step processes to enhance a user's ability and efficiency in performing tasks. In one particular aspect, a computer-implemented method is provided that includes obtaining input data from one or more cameras of a head-mounted device, detecting, from the input data, objects and relationships between the objects for performing a task, generating a symbolic task state based on the objects and the relationships between the objects, feeding, using a domain specific planning language, the symbolic task state and a corresponding desired task goal state into a planner, generating, using the planner, a plan that includes a sequence of actions to perform the task and achieve the corresponding desired task goal, and in response to executing the sequence of actions in the plan, rendering, on a display of the head-mounted device, virtual content in an extended reality environment.

Abstract: The disclosed computer-implemented method may include identifying, via an artificial reality system, a current state of a physical object in a real-world environment of a user and determining a desired end state for the physical object. The method may also include determining a sequence of action steps for manipulating the object to place the object in the desired end state, and presenting, via the artificial reality system, a notification to the user indicative of the sequence of action steps. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include identifying, via an artificial reality system, a plurality of physical objects in a real-world environment of a user and defining, based on identifying the plurality of objects, an object-manipulation objective for manipulating at least one of the plurality of objects. The method may also include determining an action sequence that defines a sequence of action steps for manipulating the at least one of the plurality of objects to complete the object-manipulation objective, and presenting, via the artificial reality system, a notification to the user indicative of the action sequence. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include identifying, via an artificial reality system, a plurality of physical objects in a real-world environment of a user and defining, based on identifying the plurality of objects, an object-manipulation objective for manipulating at least one of the plurality of objects. The method may also include determining an action sequence that defines a sequence of action steps for manipulating the at least one of the plurality of objects to complete the object-manipulation objective, and presenting, via the artificial reality system, a notification to the user indicative of the action sequence. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A process for the preparation of optically pure R (?) salbutamol of formula (6) and its pharmaceutically acceptable salts by using a (+) 4-nitro tartranilic acid as the resolving agent and a binary solvent system comprising alkyl acetate and C1 to C4 branched or normal chain alcohol for dissolution of the racemic mixture and resolving agent and purification of the 4-nitro tartranilic acid salt of R (?) salbutamol. 4-nitro tartranilic acid salt of R (?) salbutamol is converted into formic acid salt of R(?) 4-benzyl salbutamol followed by basification and debenzylation to form optically pure R(?) salbutamol. Optically pure (R)-salbutamol is obtained in good yield and high purity. The optically pure R(?)salbutamol is optionally converted into pharmaceutically acceptable salts.