Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Methods and systems for automated user group triggers for collaboration platforms are described. The method may include, in response to monitoring a set of event data, receiving a user identity event message associated with a first collaboration platform of a collaboration system. The user identity event message may include a group identifier and an identity event type identifier. A first indicator (e.g., a first fingerprint) of the user identity event message may be compared against a second indicator (e.g., a second fingerprint) to determine whether an automation rule is triggered by the user group event. If the automation rule is triggered, then an action may be performed in a second collaboration platform of the collaboration system, the action corresponding to an action component.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: A system and method for generating recommendations of a vehicle corresponding to a driver's driving behavior includes receiving driving behavior data of the vehicle, receiving data related to ownership of the vehicle, receiving vehicle sales market data, generating an asset valuation, generating a recommendation to a user, and providing the recommendation to the user through a user device. The driving behavior data is generated from vehicle sensors and is received with one or more processors communicatively coupled to a vehicle. A trained machine-learning model is implemented by the one or more processors and generates an asset valuation. The trained machine-learning model generates a recommendation to a user based on the asset valuation and the driving behavior data. The recommendation includes a new or used vehicle for purchase or leasing. The recommendation is provided to a user though a user device.

Abstract: A building management system (BMS) includes a sensor array structured to provide sensor data indicative of temperature, pressure, and humidity in an interior space, and one or more processing circuits configured to execute stored instructions to receive the sensor data from the sensor array, generate, based on the sensor data, trend data indicative of the temperature, pressure, and humidity of the interior space over a period of time, generate, based on the trend data, a prediction of future trend data for the interior space, compare the sensor data and the prediction to a compliance standard, and initiate an automated response process in response to a determining that at least one of the sensor data or the prediction does not meet the compliance standard.

Abstract: Embodiments described herein relate to systems and methods for automated content assessment for collaboration platforms. An automation rule may be established that uses a condition component that utilizes a generative output engine. A trigger component may trigger the automation rule to run, for example when an object is created or modified. A content portion from the object may be used to generate a condition prompt for the generative output engine that also includes a classifier string for the content portion and a set of example input-output content to classifier pairs. Based on a returned generative response, the condition component of the automation rule may be satisfied, and one or more next components of the automation rule performed in response. In some examples, the next component may include actions or additional conditions that utilize the generative output engine.

Abstract: Embodiments described herein relate to systems and methods for automated content labeling for collaboration platforms. A method includes receiving, at a graphical user interface (GUI), user input to create an automation rule, including a first input designating, for a label action, a label text for a label, and a second input designating, for the label action, a representative content for the label. The method generates the automation rule, including the label action, then, in response to a trigger criteria being satisfied for a page, extracting content from the page. The method includes generating, for a generative output engine, a first prompt comprising the extracted content and the representative content. A generative response may be received from the generative output engine, the response indicating the label, and associating the label with the page. A graphical indicator of the label and associated text may be displayed on the page.

Abstract: Embodiments described herein relate to systems and methods for automated content assessment for collaboration platforms. An automation rule may be established that uses a condition component that utilizes a generative output engine. A trigger component may trigger the automation rule to run, for example when an object is created or modified. A content portion from the object may be used to generate a condition prompt for the generative output engine that also includes a classifier string for the content portion and a set of example input-output content to classifier pairs. Based on a returned generative response, the condition component of the automation rule may be satisfied, and one or more next components of the automation rule performed in response. In some examples, the next component may include actions or additional conditions that utilize the generative output engine.

Abstract: Various aspects of the present disclosure relate to Type-II port-selection codebook generation. The method and apparatuses described herein may include a means for receiving a set of CSI reference signals and identifying a set of ports based on the set of reference signals. The method and apparatuses described herein may include a means for selecting a subset of ports from the identified set of ports and for generating a set of amplitude coefficient indicators and a set of phase coefficient indicators corresponding to the subset of ports. The method and apparatuses described herein may include a means for generating a CSI report comprising an indication of the subset of ports, the set of amplitude coefficient indicators, and the set of phase coefficient indicators, where the indication of the subset of ports comprises a combinatoric value.

Abstract: Embodiments described herein relate to systems and methods for automation rule creation for collaboration platforms. A natural language user input may be input to a centralized automation rule service that creates prompts for a generative output service to automatically create an automation rule understandable to one or more collaboration platforms of a system. A trigger-selection prompt, component-selection prompt, and rule-selection prompt are generated by the system and provided to the generative output engine. An automation rule can then be identified from the generative response, verified, and used in the system for the one or more collaboration platforms. In some cases, the automation rule creation from natural language input may reduce the burden on a user to craft and manage automation rules in a collaboration platform.

Abstract: Provided herein are compositions comprising a first compound having the structure of first Formula Ia, wherein the first compound comprises a first therapeutic agent having the configuration of [diacid]-[linker]-[an amylin analog], in which the amylin analog has the amino acid sequence of SEQ ID NO: 20, with a proviso that the amino acid sequence comprises one or more of the following amino acid substitutions: N14E, V17R, Y37P, F15E, L16E, V17E, or any combination thereof, and the first compound has an anion: cation molar ratio of from about 1:1 to about 1:3, and a second compound having the structure of second Formula Ia, wherein the second compound comprises a second therapeutic agent having the sequence of SEQ ID NO: 35, and the second compound has an anion: cation molar ratio of from about 1:1 to about 1:7, and methods of using thereof for the treatment of metabolic diseases or disorders, including type 1 diabetes, type 2 diabetes, obesity, overweight, and nonalcoholic steatohepatitis, and for reducing we

Abstract: Embodiments described herein relate to systems and methods for automation rule creation for collaboration platforms. A natural language user input may be input to a centralized automation rule service that creates prompts for a generative output service to automatically create an automation rule understandable to one or more collaboration platforms of a system. A trigger-selection prompt, component-selection prompt, and rule-selection prompt are generated by the system and provided to the generative output engine. An automation rule can then be identified from the generative response, verified, and used in the system for the one or more collaboration platforms. In some cases, the automation rule creation from natural language input may reduce the burden on a user to craft and manage automation rules in a collaboration platform.

Abstract: Provided herein are compounds having the structure of Formula I, wherein the compounds comprise a therapeutic agent having the configuration of [diacid]-[linker]-[an amylin analog], in which the amylin analog has the amino acid sequence of SEQ ID NO: 20, with a proviso that the amino acid sequence comprises one or more of the following amino acid substitutions: N14E, V17R, Y37P, F15E, L16E, V17E, or any combination thereof, and the compounds have an anion: cation molar ratio of from about 1:1 to about 1:3, and methods of using thereof for the treatment of metabolic diseases or disorders, including type 1 diabetes, type 2 diabetes, obesity, overweight, and nonalcoholic steatohepatitis, and for reducing weight in a subject in need thereof.

Abstract: Apparatuses, methods, and systems are disclosed for channel state information report coefficients. One method (700) includes receiving (702), at a user equipment, a set of reference signals. The method (700) includes identifying (704) a set of ports based on the set of reference signals. The method (700) includes selecting (706) a subset of ports from the set of ports. The method (700) includes computing (708) a subset of coefficients corresponding to a set of indices for each reference signal in the set of reference signals. The method (700) includes generating (710) a channel state information report comprising the subset of coefficients corresponding to the set of indices for each port in the subset of ports.

Abstract: Apparatuses, methods, and systems are disclosed for Type-II port-selection codebook generation. One apparatus includes a processor and a transceiver that receives a set of CSI-RS. The processor identifies a set of CSI-RS ports based on the set of CSI-RS. The processor selects a subset of CSI-RS ports from the identified set of CSI-RS ports based on a free selection of the respective CSI-RS ports from the identified CSI-RS ports. The processor generates, based on the set of CSI-RSs, at least one amplitude coefficient indicator and at least one phase coefficient indicator for each selected CSI-RS port generates a CSI report comprising a Type-II port-selection codebook corresponding to the generated coefficients and the subset of CSI-RS ports.

Abstract: Apparatuses, methods, and systems are disclosed for preparing channel state information (CSI). One apparatus includes a processor and a memory with instructions executable by the processor to cause the apparatus to cause a base station to receive, from a user equipment (UE), CSI based on a CSI codebook which includes a plurality of precoding matrices; decode a codeword based on the CSI; determine a total number of non-zero coefficients based on the codeword, where the codeword identifies the total number of non-zero coefficients, and where the total number of non-zero coefficients is associated with the CSI codebook over a set of transmission layers.

Abstract: Provided herein are methods of treating metabolic diseases or disorders in a subject in need thereof and methods of reducing weight in a subject in need thereof by using compounds having the structure of Formula Ia, wherein the compounds comprise a therapeutic agent having the configuration of [diacid]-[linker]-[an amylin analog], in which the amylin analog has the amino acid sequence of SEQ ID NO: 20, with a proviso that the amino acid sequence comprises one or more of the following amino acid substitutions: N14E, V17R, Y37P, F15E, L16E, V17E, or any combination thereof, and the compounds have an anion:cation molar ratio of from about 1:1 to about 1:3.

Abstract: Provided herein are compositions or compounds comprising therapeutic proteins or peptides for treating metabolic diseases or disorders and/or for reducing weight in a subject in need thereof, and methods of using thereof.