Abstract: Described embodiments provide systems and methods for intelligent load balancing of hosted sessions. A processor can determine a plurality of metrics for each of a plurality of machines configured to connect client devices with hosted sessions. The processor can receive, from a client device, a request to establish a connection with one of the plurality of machines to access a hosted session. The processor can determine a score for each of the plurality of machines based at least on the plurality of metrics for each of the plurality of machines. The processor can select a machine from the plurality of machines as a function of the score and a resource cost of the machine. The processor can cause the client device to connect to the selected machine for the hosted session.

Abstract: Techniques are disclosed for end-to-end assurance of application workloads. For example, a computing system receive time series data comprising performance indicators for elements of layers of a system having host computing devices executing application workloads. The computing system creates, based on mapping, using the time series data, Graphics Processing Units (GPUs) of a compute layer to network devices of a network layer, a dependency graph representing cross-layer relationships between elements of different layers of the layers. The computing system determines an anomaly in the performance of one of the application workloads. The computing system determines, based on a dependency within the dependency graph of the application workload on an element of the network layer, an issue with the element as a root cause of the anomaly in the performance of the workload, and performs a remedial action for the issue with the element of the network layer.

Abstract: Systems and methods of obtaining data from a cellular network are disclosed. In some embodiments, visual query options are presented in a graphical user interface (GUI), wherein the visual query options define a query. Query option selections of the visual query options are received. A query template is generated in accordance with the query option selections. An audit of parameters is performed related with network elements of the cellular network in accordance with the query template. A report of the audit is transmitted to a user device. A visual representation of the report is presented in the GUI.

Abstract: Methods and systems are disclosed herein for preventing hallucinations in machine learning models by enabling query responses based on a predefined ground truth defined by a corpus of information. The system may use multiple machine learning models. In particular, the system may receive a user query and use a machine learning model to split the user query into multiple sub-queries that would ask component questions for the query. The component questions may then be used to get accurate information for responding to the query. Once the information is identified, the hallucination prevention system may input that information into another machine learning model (for example, a large language model) with instructions to deliver the response to the query based on the identified information, but put it into a specific, desired form. In some embodiments, another machine learning model may be used to identify undesired responses based on policy and/or other requirements.

Abstract: The present disclosure relates to systems and methods for improved vehicle transaction platforms. An example method may include receiving, by a vehicle transaction platform, a search request for vehicles from a user device associated with a first user account. The example method may also include receiving identifying information associated with the user account, wherein at least a portion of the identifying information is received from a third party. The example method may also include identifying, based on the identifying information, a predetermined search pattern, wherein the predetermined search pattern was generated based on a prior search request associated with a second user account and identifying information associated with the second user account.

Abstract: An apparatus is configured to receive a first plurality of directive data structures, each directive data structure of the first plurality of directive data structures including a one or more first support control requirements associated with a supported platform and allocation of resources to a support matrix associated with the supported platform, the support matrix including a plurality of slots. The apparatus is further configured to allocate one or more resource data structures of a plurality of resource data structures to one or more of the plurality of slots of the support matrix according to the first plurality of directive data structures, and receive a slot allocation compliance matrix, where the slot allocation compliance matrix includes one or more compliance indications associated with the plurality of slots.

Abstract: Described are systems and processes for providing safety guidance in generating images to prevent the inclusion of harmful content and/or concepts in the generated images. Statistical properties may be determined for the dimensions of a noise vector at each time step of a diffusion denoising process to determine dimensions that have high risks of manifesting restricted content and/or are loosely correlated to an input prompt, and targeting the determined dimensions in applying one or more safety guidance vectors to noise vectors at each time step of the diffusion denoising process based on the statistical properties. This facilitates the generation of images that maintains alignment of the generated output image with the input text prompt while effectively implementing safety guidance to avoid harmful content and/or concepts.

Abstract: An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which, when executed by the processing circuitry, cause the network system to obtain first traffic session metrics data and execute a machine learning model to determine a traffic prediction based on the first traffic session metrics data. The instructions cause the network system to obtain second traffic session metrics data and determine an anomaly in traffic based on a comparison of the traffic prediction and the second traffic session metrics data. The instructions cause the network system to, based on the determination of the anomaly, generate an indication of the anomaly.

Abstract: In general, techniques are described for a computing system that generates a first graph representative of a of a first application topology of a distributed application at a first time that includes a first plurality of nodes of a computing infrastructure across a plurality of layers. The computing system generates a second graph representative of a second application topology of the distributed application at a second time. The computing system determines, based on a comparison of the first graph and the second graph, that a path has changed. Based on the determination that the path has changed, the computing system outputs an indication that an alarm indicative of an issue in the computing infrastructure is caused by the change to the path.

Abstract: Techniques for determining that processing with respect to a user input will result in an error and ranking clusters of features associated with the user input based on a likelihood that the feature caused the error are described. The system receives user input data, extracts features corresponding to the user input data, and clusters the features based on a similarity to features of other user inputs. The resulting clusters and the user input data are processed to determine whether processing of the user input data will result in an error and a list of the clusters ranked based on a likelihood that the corresponding feature caused the error. Based on the ranked list of the clusters, an error type is attributed to the error and steps for re-configuring a component causing the error are determined.

Abstract: Systems and techniques for moderating responses of a generative language model are described herein. Some user inputs to a generative language model may include biases, misinformation, and other references to moderated content. To prevent the generative language model from generating responses that promote these forms of moderated content, the techniques described determine a policy corresponding to the determined moderated content category of the user input. The determined policy may correspond to a template of instructions for how the generative language model is to respond to such moderated content. The output of the generative language model may also be moderated before being presented to the user.

Abstract: In general, techniques are described for managing a distributed application based on call paths among the multiple services of the distributed application that traverse underlying network infrastructure. In an example, a method comprises determining, by a computing system, and for a distributed application implemented with a plurality of services, a call path from an entry endpoint service of the plurality of services to a terminating endpoint service of the plurality of services; determining, by the computing system, a corresponding network path for each pair of adjacent services from a plurality of pairs of services that communicate for the call path; and based on a performance indicator for a network device of the corresponding network path meeting a threshold, performing, by the computing system, one or more of: reconfiguring the network; or redeploying one of the plurality of services to a different compute node of the compute nodes.

Abstract: In an approach for interpreting one or more astronomical events and activating a network of telescopes for optimized observation of the one or more astronomical events, a processor monitors for a set of published content regarding the one or more astronomical events. Responsive to detecting the set of published content, a processor extracts, interprets, and correlates the set of published content to identify an area in space related to the one or more astronomical events for observation. A processor implements a monitoring system, wherein the monitoring system includes one or more registered telescopes of a network of telescopes to autonomously observe the area. A processor signals the one or more registered telescopes to capture an image of the one or more astronomical events. Responsive to the one or more registered telescopes capturing the image, a processor classifies one or more objects in the image. A processor publishes the image.

Abstract: Provided is a method of providing information by an electronic apparatus, the method including obtaining a first information request for a first item including information on a first quantity of the first item from a first terminal of a first user, identifying that a first stock keeping unit (SKU) corresponding to the first item is one of a plurality of SKUs arranged in first-type zone groups within a plurality of fulfillment centers, determining a product delivery date (PDD) of the first item based on at least one of information on a time of obtaining the first information request, information on a type of a camp corresponding to a first address set as a delivery location by the first user, stock information of the first-type zone groups, and the information on the first quantity, and providing the first terminal with information on the PDD of the first item.

Abstract: A circuit includes a control circuit branch and a discharge circuit branch. The control circuit branch is electrically coupled between a control input node and a negative node. The control circuit branch includes a p-type transistor (MP), a diode, and a first n-type transistor (MN1). A source node of MP is electrically coupled to the control input node. The diode has an anode and a cathode. The anode is electrically coupled to a drain node of MP. A drain node of MN1 is electrically coupled to the cathode. A source node of MN1 is electrically coupled to the negative node. The discharge circuit branch is electrically coupled between the negative node and a discharge node. The discharge circuit branch includes a second n-type transistor (MN2). A drain node of MN2 is electrically coupled to the negative node. A gate node of MN2 is electrically coupled to the cathode.

Abstract: Code generation techniques from a digital image are described. In one or more examples, layout data is extracted from a digital image. The layout data describing a layout of elements included in the digital image. Markup language code is generated over one or more iterations of candidate markup code using a machine-learning model based on the digital image and the layout data and determining whether a similarity threshold is reached by comparing a candidate digital image generated using the candidate markup code with the digital image. The markup language code is output responsive to determining the similarity threshold is reached.

Abstract: A system and method are provided to configure a network for onboarding of devices. A hierarchical parameter data file describing configuration parameters of the plurality of devices, such as a Yet Another Next Generation (YANG) model, is received. A parameter database file including a plurality of configuration parameters is populated, with at least one of the configuration parameters being derived from content of the hierarchical parameter data file, and a parameter library is generated based on the parameter database file. A class definition file is generated based on at least one of the database file and the hierarchical parameter data file. Then, for a network function, a corresponding configuration file is generated based on the parameter library and the class definition file, and is provided to the network function for implementation.