Abstract: An RFID module attached to a quick connector is arranged to send latched confirmation information to a RFID reader verifying that a pipe is latched to the connector body. A latch mechanism retained on the connector body is arranged to cooperate with the RFID module. In a pipe insertion position, the latch mechanism is positioned to allow the pipe to be inserted into an internal passage of the connector body and to shield and block radio frequencies sent from the RFID reader to reach the RFID module. Moving the latch mechanism to a latched position retains the pipe to the connector body and unshields the RFID module to allow reading of latched confirmation information from the RFID module.

Abstract: An online system facilitates various functions using machine learning model microservices. A tuning mechanism tunes various configuration parameters for each microservice that control allocation of computing resources and other configurations of physical and/or virtual machines that implement the microservices. Tuning may be performed in part by executing tests under various configurations and evaluating an objective function associated with the different configurations. Furthermore, parameters of the objective function may be set based on a trained learning model that learns baseline parameters and weights of the objective function based on historical data.

Abstract: In some embodiments, a trench isolation structure is formed from a first layer with enough carbon to sufficiently resist a dielectric etching process and a second, outer layer with surface wetting properties that allow it to adhere with the dielectric material that is to be etched.

Abstract: An online system performs an inference task in conjunction with the model serving system and/or interface system to generate relevant product images for query auto-completion and query suggestion to help users better navigate their search experience. The online system generates a collection of query suggestions using search query log mining. For each query suggestion in the collection of query suggestions, the online system retrieves one or more catalog images that depict the query suggestion from a product catalog. The online system constructs a prompt to a text-to-image model including the query suggestion, and a request to generate one or more query images based on the query suggestion. The online system receives the query images from the text-to-image model and ranks the catalog and query images to identify an image to display to the user in association with the query suggestion.

Abstract: A language model is used to generate autosuggestions to complete or revise a user's partial search query. An initial partial query is applied to the language model to generate query candidates for completing the search query. The language model may generate the query candidates as additional or alternate tokens for the partial search query. When the user revises the partial query, the previously-generated candidates can be re-used to reduce subsequent processing time for generating additional candidates. The previously-generated candidates are compared with the revised partial query to select which of the candidates to be re-used and expanded for generating additional tokens. Additional tokens can be generated in parallel for the previously-generated candidates or with model values from the previous generation, enabling the tokens to be generated effectively with reduced latency consistent with user expectations for search-related autosuggestions.

Abstract: An online system uses benchmarking tests to identify indexing algorithms for an embedding database. To perform these benchmarking tests, the online system receives a set of parameters for configuring an embedding database. For example, the parameters may include a performance parameter and a latency parameter. The online system generates algorithm scores for a set of candidate indexing algorithms based on the parameters. Specifically, the online system tests each of the candidate indexing algorithms by generating a testing database based on a subset of the entries for the full database and by performing benchmarking tests on the testing database. The online system uses these tests to compute performance metrics for each candidate indexing algorithm and uses those performance metrics to compute an algorithm score for each indexing algorithm. The online system uses the computed algorithm scores to select an indexing algorithm for the embedding database.

Abstract: A language model is used to generate autosuggestions to complete or revise a user's partial search query. An initial partial query is applied to the language model to generate query candidates for completing the search query. The language model may generate the query candidates as additional or alternate tokens for the partial search query. When the user revises the partial query, the previously-generated candidates can be re-used to reduce subsequent processing time for generating additional candidates. The previously-generated candidates are compared with the revised partial query to select which of the candidates to be re-used and expanded for generating additional tokens. Additional tokens can be generated in parallel for the previously-generated candidates or with model values from the previous generation, enabling the tokens to be generated effectively with reduced latency consistent with user expectations for search-related autosuggestions.

Abstract: An online system performs an inference task in conjunction with the model serving system and/or interface system to generate relevant product images for query auto-completion and query suggestion to help users better navigate their search experience. The online system generates a collection of query suggestions using search query log mining. For each query suggestion in the collection of query suggestions, the online system retrieves one or more catalog images that depict the query suggestion from a product catalog. The online system constructs a prompt to a text-to-image model including the query suggestion, and a request to generate one or more query images based on the query suggestion. The online system receives the query images from the text-to-image model and ranks the catalog and query images to identify an image to display to the user in association with the query suggestion.

Abstract: An online system uses benchmarking tests to identify indexing algorithms for an embedding database. To perform these benchmarking tests, the online system receives a set of parameters for configuring an embedding database. For example, the parameters may include a performance parameter and a latency parameter. The online system generates algorithm scores for a set of candidate indexing algorithms based on the parameters. Specifically, the online system tests each of the candidate indexing algorithms by generating a testing database based on a subset of the entries for the full database and by performing benchmarking tests on the testing database. The online system uses these tests to compute performance metrics for each candidate indexing algorithm and uses those performance metrics to compute an algorithm score for each indexing algorithm. The online system uses the computed algorithm scores to select an indexing algorithm for the embedding database.

Abstract: A variation testing system environment for simulating adaptive experiments of objects is disclosed. An experiment system conducts one or more simulations of an adaptive experiment that includes a plurality of variants of an object. Simulation results based on the one or more simulations are generated that are indicative of at least an estimated amount of time to conduct a real-world adaptive experiment based on the one or more simulations.

Abstract: A method for predicting customer long-term behavior using LLM-based modeling is described. The online system receives a representation of a stimulus or treatment that is presented to a user and generates a summary of a simulated user profile. The online system performs an inference task in conjunction with the model serving system or interface system to infer one or more actions that will likely be performed in response to the representation of the stimulus based on the simulated user profile. The online system computes a surrogate measure based on the response received from the model serving system and computes a correlation coefficient between the surrogate measure and a true metric of interest from collected experiment data. Responsive to determining a correlation coefficient greater than a threshold value, the online system predicts the true metric of interest based on the surrogate measure.

Abstract: An online system performs inference requests in conjunction with the model serving system to perform AI (text-based LLM or multi-modal transformer)-generated integration test variants. Instead of rigid code-specified integration tests, the LLM creates integration test variants that follow a specification. Given one or more files from the codebase of an application and a specification for integration testing, the LLM compiles an integration test including a series of actions (e.g., API calls) as runnable code and assertions about the state of the application after the actions are executed.

Abstract: An online system performs an inference task in conjunction with the model serving system and/or interface system to generate relevant product images for query auto-completion and query suggestion to help users better navigate their search experience. The online system generates a collection of query suggestions using search query log mining. For each query suggestion in the collection of query suggestions, the online system retrieves one or more catalog images that depict the query suggestion from a product catalog. The online system constructs a prompt to a text-to-image model including the query suggestion, and a request to generate one or more query images based on the query suggestion. The online system receives the query images from the text-to-image model and ranks the catalog and query images to identify an image to display to the user in association with the query suggestion.

Abstract: Control techniques for controlling a reliability of a spinning reserve of a wind turbine to be tailored to a user's reliability preference are disclosed. In one aspect, a control technique includes operating a wind turbine in a spinning reserve mode to provide a spinning reserve; calculating an available power of the wind turbine when operating in the spinning reserve mode; defining a reliability band around the calculated available power; selecting a reliability factor that defines a probability that a reliable available power within the reliability band is below the real available power; determining the reliable available power based on the selected reliability factor and the reliability band; determining a power setpoint for the wind turbine based on a difference between a desired spinning reserve and the determined reliable available power; and controlling the wind turbine to operate in the spinning reserve mode in accordance with the power setpoint.

Abstract: In some embodiments, the strength of the work function (WF) for P-type MOS transistors may be boosted by doping a gate layer surface using a plasma oxidation treatment after a metallic nitride (e.g., MoN film) has been deposited.

Abstract: The online system is configured to efficiently handle user requests by choosing a suitable prompt from a pre-curated library and selecting one of a plurality of large language models (LLMs) to respond to the user queries. These prompts are tailored for compatibility with different LLMs. When a user query is received, the system simultaneously forwards it to multiple LLMs and receives diverse responses. Performance metrics are then generated based on these multiple responses, aiding in the selection of the most suitable LLM. The chosen LLM is used for processing subsequent queries from the same user. This approach not only ensures that users receive high-quality, prompt responses but also optimizes the system's performance by dynamically selecting the most efficient LLM based on both quality and speed.

Abstract: The present disclosure is directed to generating datastore checkpoints. In particular, the methods and systems of the present disclosure may generate, within a datastore, data representing multiple checkpoints. Each checkpoint of the checkpoints may correspond to a respective record of the datastore and may represent a common shared value for a field based at least in part on which the datastore is ordered. Based at least in part on the checkpoints, the datastore may be queried to produce one or more responsive records to one or more criteria of the query. Based at least in part on the responsive record(s), training data may be generated. The training data may be utilized for training one or more machine learning (ML) models configured to process input based at least in part on values for the field based at least in part on which the datastore is ordered.

Abstract: An online system may receive a registration of an application for a language model gateway configured as an intermediary between users and a first machine-learned language model. The online system may monitor a conversation associated with the application using the language model gateway. The conversation is between a user of the application and the first machine-learned language model and includes a prompt from the user directed toward the first machine-learned language model. The online system may extract the prompt and compile an input for a second machine-learned language model that is fine-tuned to improve prompts. The input may be the prompt and one or more criteria to improve the prompt. The online system may provide the input to the second machine-learned language model. The online system may determine a suggested improvement to the prompt using the second machine-learned language model and provide the suggested improvement to the user.

Abstract: A modular retention clip for retaining elongated articles to a structure includes a clamping body having first and second body portions of a first rigid material positionable between an open position and an engaged position. Isolation portions of a second resilient material are attached to the first and second body portions that contact and retain the elongated articles in the engaged position. A living hinge integrally connects the first and the second body portions and a latching member is arranged to be captured within a receiving cavity retaining the first and second body portions together. At least one mounting pin extends from the second body portion. A bracket having a receiving portion and a mounting portion has at least one hole in the receiving portion that accepts the mounting pin to fix the clamping body to the bracket. The bracket mounting portion attaches the bracket to the structure.

Abstract: A language model is used to generate autosuggestions to complete or revise a user's partial search query. An initial partial query is applied to the language model to generate query candidates for completing the search query. The language model may generate the query candidates as additional or alternate tokens for the partial search query. When the user revises the partial query, the previously-generated candidates can be re-used to reduce subsequent processing time for generating additional candidates. The previously-generated candidates are compared with the revised partial query to select which of the candidates to be re-used and expanded for generating additional tokens. Additional tokens can be generated in parallel for the previously-generated candidates or with model values from the previous generation, enabling the tokens to be generated effectively with reduced latency consistent with user expectations for search-related autosuggestions.