Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.

Abstract: A wafer testing apparatus includes a base, a chuck, a first lift device and a bridge assembly. The base is movable in a first axis direction. The chuck carries a component under test. The first lift device lifts or lowers the chuck relative to the base in the first axis direction, so as to correspondingly come into contact with or move away from the component under test. The bridge assembly includes an electrical connection device and a second lift device. The electrical connection device includes first and second connection modules electrically connected to each other. The second lift device lifts or lowers the electrical connection device relative to the base in the first axis direction, such that the first connection module correspondingly comes into contact with or moves away from a probe card, and the second connection module correspondingly comes into contact with or moves away from the chuck.

Abstract: This disclosure describes systems that identify one or more models (e.g., large language models and/or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.

Abstract: A semiconductor device and method of fabricating a semiconductor device involves formation of a trench above a fin (e.g. a fin of a FinFET device) of the semiconductor device and formation of a multi-layer dielectric structure within the trench. The profile of the multi-layer dielectric structure can be controlled depending on the application to reduce shadowing effects and reduce cut failure risk, among other possible benefits. The multi-layer dielectric structure can include two layers, three layers, or any number of layers and can have a stepped profile, a linear profile, or any other type of profile.

Abstract: A de-flicker system includes a compensation gain estimation circuit and a flicker removal circuit. The compensation gain estimation circuit receives a plurality of flicker-dependent frames with sliding bandings, and estimates a compensation gain for each of the plurality of flicker-dependent frames according to the flicker-dependent frames. The flicker removal circuit applies flicker compensation to each of the flicker-dependent frames according to the compensation gain.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.

Abstract: An electroplating apparatus is adapted to electroplate an object to be plated having through holes. The electroplating apparatus includes a plating tank, a first anode plate parallel to a second anode plate in the plating tank, a cathode plate connected to the object to be plated, a first sensing module, and a second sensing module. The cathode plate and the object to be plated are in the plating tank and between the first anode plate and the second anode plate. The first sensing module includes a light source between the object to be plated and the first anode plate, and a light sensor between the object to be plated and the second anode plate. The second sensing module includes a first electrical sensor between the object to be plated and the first anode plate, and a second electrical sensor between the object to be plated and the second anode plate.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.

Abstract: Devices and methods for making a polymer with a porous layer from a solid piece of polymer are disclosed. In various embodiments, the method includes heating a surface of a solid piece of polymer to a processing temperature and holding the processing temperature while displacing a porogen layer through the surface of the polymer to create a matrix layer of the solid polymer body comprising the polymer and the porogen layer. In at least one embodiment, the method also includes removing at least a portion of the layer of porogen from the matrix layer to create a porous layer of the solid piece of polymer.

Abstract: A wireless communication method and system are disclosed. After a station is wireless connected to an agent, the agent monitors airtime of each link of the station to report a first link status to a controller. The controller collects the first link status and detects scenarios based on the first link status. The controller determines to select among an initial second link and a candidate second link status as a second link status based on whether a throughput of the candidate second link status is higher than a throughput of first link status. The controller informs the second link status to the agent, and the controller wireless communicates with the agent over bands corresponding to the second link status.

Abstract: A method for motion prediction includes receiving spatial information output by a radio-wave sensor, wherein the spatial information includes position and velocity of at least one point; receiving an image captured by a camera; tracking at least one object based on the spatial information and the image to obtain a consolidated tracking result; predicting a motion trajectory of the at least one object based on the consolidated tracking result to obtain a prediction result; and controlling the camera according to the prediction result.

Abstract: A semiconductor device includes a first stacked structure, a second stacked structure, a first vertical connector, and a second vertical connector. The first stacked structure includes a first stacked wafer and a first bonding layer. The first stacked wafer includes multiple first dielectric bonding interfaces. The second stacked structure includes a second stacked wafer and a second bonding layer. The second stacked wafer includes multiple second dielectric bonding interfaces. The first bonding layer is bonded and electrically connected to the second bonding layer, such that there is a hybrid bonding interface between the first stacked structure and the second stacked structure. The first vertical connector penetrates the first dielectric bonding interfaces and is electrically connected to the first bonding layer. The second vertical connector penetrates the second dielectric bonding interfaces and is electrically connected to the second bonding layer.

Abstract: A position fine-tuning structure includes a first plate, a second plate and a guide slider. A top surface of the first plate is recessed with a first linear groove. A bottom surface of the second plate is recessed with a second linear groove. The bottom surface of the second plate directly covers the top surface of the first plate, so that the second linear groove is orthogonal to and in communication with to the first linear groove. The guide slider includes a first pillar and a second pillar which are overlapped with and orthogonal to each other. The first pillar is parallel to the first linear groove and slidably located within the first linear groove, and the second pillar is parallel to the second linear groove and slidably located within the second linear groove.

Abstract: An electronic device includes a substrate, a sensor, an inner cover, a water proof member, and an outer cover. The sensor is disposed on the substrate. The inner cover is disposed on the substrate and covers the sensor. The inner cover includes an opening. The water proof member is disposed on the inner cover and covers the opening. The outer cover is disposed on the substrate and covers the inner cover, so that a drainage chamber is formed between the inner cover and the outer cover. The drainage chamber communicates with outside through a first hole and a second hole. The first hole and the second hole are staggered with the opening. A portion of the drainage chamber between the first hole and the second hole acts as a drainage channel. A length of the drainage channel is greater than a diameter of the opening.

Abstract: An electronic device includes a first substrate, a second substrate, a sensor, a lid, a water proof member, and an outer cover. The first substrate includes a first inner cavity and a through hole. The second substrate is stacked on the first substrate so as to form a second inner cavity and a straight airflow channel. The sensor is disposed on the first substrate, covers the through hole, and includes a back cavity. The lid is disposed on the second substrate, covers the second inner cavity, and includes an opening. The water proof member covers the opening. The outer cover is disposed on the lid and forms a drainage chamber with the lid. The outer cover includes a first hole and a second hole connecting the drainage chamber to the outside. The first hole and the second hole are staggered from the opening.

Abstract: A method includes forming a gate stack over a semiconductor region, etching the semiconductor region to form a source/drain recess aside of the gate stack, depositing a first dielectric layer, wherein a portion of the first dielectric layer is in the source/drain recess, performing a treatment process on the first dielectric layer, depositing a second dielectric layer on the first dielectric layer, and etching the second dielectric layer and the first dielectric layer. A first portion of the first dielectric layer and a second portion of the second dielectric layer remain at a bottom of the source/drain recess to form a dielectric region. A source/drain region is deposited in the source/drain recess and over the dielectric region.

Abstract: A memory device includes a bottom electrode, a buffer element, a metal-containing oxide portion, a resistance switch element, and a top electrode. The buffer element is over the bottom electrode. The metal-containing oxide portion is over the buffer element, in which the metal-containing oxide portion has a same metal material as that of the buffer element. The resistance switch element is over the metal-containing oxide portion. The top electrode is over the resistance switch element.