Abstract: A planter suitable for block seeds that relates to agricultural seeding machinery includes a frame, a fertilizing tank, a fertilizing box, a seeding mechanism, a control mechanism, a seed box, a ridging mechanism, land wheels, a seeding furrower, a fertilizing furrower, a seed-clearing mechanism, and a replanting mechanism. The fertilizing furrower, the fertilizing tank, the fertilizing box, the seeding furrower, the land wheels, the seeding mechanism, the control mechanism, the seed box, and the ridging mechanism are mounted in turn from one end to an opposite end of the frame. A photoelectric sensor of an active infrared intrusion detector is adopted to dynamically monitor the presence of seed potatoes on a seed-discharge spoon in a conveying process. Seeds are replanted with the control mechanism when the seeds are sowed with an empty spoon.

Abstract: In an example embodiment, a generator model such as a large language model (LLM) is leveraged to generate embeddings for both pieces of content and users. The embeddings map the pieces of content and the users into the same latent n-dimensional space. The embeddings are then fine-tuned using a two-tower deep neural network, with one of the towers representing users and the other tower representing content. The two-tower deep neural network is trained to optimize the embeddings over some shared goal, such as user engagement with content, and uses information such as user interactions with content in that process. A clustering technique, such as K-nearest neighbor (kNN) can then be used to identify a grouping of top user/content pairs based on similarity between users and content, as reflected in the embeddings. For a given piece of content, therefore, the top users from that cluster can then be recommended as an audience for the content.

Abstract: In an example embodiment, a framework is presented that utilizes a large language model (LLM) to aid in the generation of targeting criteria, namely in generating portions of information that will be used to generate a target audience for a particular media item, based in part on the media item itself. More specifically, the LLM is used to produce a suggestion of one or more facets of a target audience, wherein each facet is a category of information for users within the target audience. The LLM is then also used to produce a plurality of segments within the one or more suggested facets. The produced facets and segments may then be used to create a target audience for the media item, even in a cold-start environment where no information about a desired audience is provided by the entity wishing to distribute the media item.

Abstract: In an example embodiment, a generator model such as a large language model (LLM) is leveraged to generate embeddings for both pieces of content and users. The embeddings map the pieces of content and the users into the same latent n-dimensional space. The embeddings are then fine-tuned using a two-tower deep neural network, with one of the towers representing users and the other tower representing content. The two-tower deep neural network is trained to optimize the embeddings over some shared goal, such as user engagement with content, and uses information such as user interactions with content in that process. A clustering technique, such as K-nearest neighbor (kNN) can then be used to identify a grouping of top user/content pairs based on similarity between users and content, as reflected in the embeddings. For a given piece of content, therefore, the top users from that cluster can then be recommended as an audience for the content.

Abstract: A planter suitable for block seeds that relates to the technical field of agricultural seeding machinery is disclosed. The planter includes a frame, a fertilizing tank, a fertilizing box, a seeding mechanism, a control mechanism, a seed box, a ridging mechanism, land wheels, a seeding furrower, a fertilizing furrower, a seed-clearing mechanism, and a replanting mechanism. The fertilizing tank, the fertilizing furrower, the fertilizing box, the seeding furrower, the seeding mechanism, the land wheels, the control mechanism, the seed box, and the ridging mechanism are mounted in turn from one end to the other end of the frame. A photoelectric sensor of an active infrared intrusion detector is adopted to dynamically monitor the presence of the seed potatoes on a seed-discharge spoon in a conveying process. Seeds are replanted with the control mechanism when the seeds are sowed with an empty spoon.

Abstract: Embodiments of the disclosed technologies include configuring a first machine learning model to generate and output suggested message content based on first correlations between message content and message acceptance data, where the first machine learning model includes a first encoder-decoder model architecture, configuring a second machine learning model to generate and output message evaluation data based on second correlations between the message content and the message acceptance data, where the second machine learning model includes a second encoder-decoder model architecture, coupling an output of the first machine learning model to an input of the second machine learning model, and coupling an output of the second machine learning model to an input of the first machine learning model.

Abstract: Embodiments of the disclosed technologies include receiving first message attribute data and inputting the first message attribute data to a first machine learning model. The first machine learning model is configured to generate and output suggested message content based on first correlations between message content and message acceptance data. The first machine learning model generates a first set of message content suggestions based on the first message attribute data, and selects at least one message content suggestion from the first set of message content suggestions based on message evaluation data. Feedback data related to the selected at least one message content suggestion is received. The first machine learning model is tuned based on the feedback data. The tuned first machine learning model generates a second set of message content suggestions based on the first message attribute data.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, a passivation film stack is provided and includes a silicon oxide layer disposed on a workpiece, a nitrogen-rich silicon nitride layer disposed on the silicon oxide layer, and a hydrogen-rich silicon nitride layer disposed on the nitrogen-rich silicon nitride layer. The hydrogen-rich silicon nitride layer has a greater hydrogen concentration than the nitrogen-rich silicon nitride layer.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, a passivation film stack is provided and includes a silicon oxide layer disposed on a workpiece, a nitrogen-rich silicon nitride layer disposed on the silicon oxide layer, and a hydrogen-rich silicon nitride layer disposed on the nitrogen-rich silicon nitride layer. The hydrogen-rich silicon nitride layer has a greater hydrogen concentration than the nitrogen-rich silicon nitride layer.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, methods for depositing silicon nitride materials are provided and include heating a workpiece to a temperature of about 200° C. to about 250° C., exposing the workpiece to a deposition gas during a plasma-enhanced chemical vapor deposition process, and depositing a nitrogen-rich silicon nitride layer on the workpiece. The deposition gas contains a silicon precursor, a nitrogen precursor, and a carrier gas. A molar ratio of the silicon precursor to the nitrogen precursor to the carrier gas within the deposition gas is about 1:a range from about 4 to about 8:a range from about 20 to about 80, respectively.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, methods for depositing silicon nitride materials are provided and include heating a workpiece to a temperature of about 200° C. to about 250° C., exposing the workpiece to a deposition gas during a plasma-enhanced chemical vapor deposition process, and depositing a nitrogen-rich silicon nitride layer on the workpiece. The deposition gas contains a silicon precursor, a nitrogen precursor, and a carrier gas. A molar ratio of the silicon precursor to the nitrogen precursor to the carrier gas within the deposition gas is about 1:a range from about 4 to about 8:a range from about 20 to about 80, respectively.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, a passivation film stack contains a silicon oxide layer disposed on a workpiece and a nitrogen-rich silicon nitride layer disposed on the silicon oxide layer. The nitrogen-rich silicon nitride layer has a silicon concentration of about 20 at % to about 35 at %, a nitrogen concentration of about 40 at % to about 75 at %, and a hydrogen concentration of about 10 at % to about 35 at %. In one or more examples, the passivation film stack contains the silicon oxide layer, the nitrogen-rich silicon nitride layer, and a third layer containing any type of silicon nitride, such as nitrogen-rich silicon nitride and/or hydrogen-rich silicon nitride.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for depositing metal silicide layers on substrates and chamber components. In one embodiment, a method of forming a hardmask includes positioning the substrate having a target layer within a processing chamber, forming a seed layer comprising metal silicide on the target layer and depositing a tungsten-based bulk layer on the seed layer, wherein the metal silicide layer and the tungsten-based bulk layer form the hardmask. In another embodiment, a method of conditioning the components of a plasma processing chamber includes flowing an inert gas comprising argon or helium from a gas applicator into the plasma processing chamber, exposing a substrate support to a plasma within the plasma processing chamber and forming a seasoning layer including metal silicide on an aluminum-based surface of the substrate support.

Abstract: Embodiments of the present disclosure generally relate to nitrogen-rich silicon nitride and methods for depositing the same, and transistors and other devices containing the same. In one or more embodiments, a passivation film stack contains a silicon oxide layer disposed on a workpiece and a nitrogen-rich silicon nitride layer disposed on the silicon oxide layer. The nitrogen-rich silicon nitride layer has a silicon concentration of about 20 at % to about 35 at %, a nitrogen concentration of about 40 at % to about 75 at %, and a hydrogen concentration of about 10 at % to about 35 at %. In one or more examples, the passivation film stack contains the silicon oxide layer, the nitrogen-rich silicon nitride layer, and a third layer containing any type of silicon nitride, such as nitrogen-rich silicon nitride and/or hydrogen-rich silicon nitride.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for depositing metal silicide layers on substrates and chamber components. In one embodiment, a method of forming a hardmask includes positioning the substrate having a target layer within a processing chamber, forming a seed layer comprising metal silicide on the target layer and depositing a tungsten-based bulk layer on the seed layer, wherein the metal silicide layer and the tungsten-based bulk layer form the hardmask. In another embodiment, a method of conditioning the components of a plasma processing chamber includes flowing an inert gas comprising argon or helium from a gas applicator into the plasma processing chamber, exposing a substrate support to a plasma within the plasma processing chamber and forming a seasoning layer including metal silicide on an aluminum-based surface of the substrate support.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for depositing metal silicide layers on substrates and chamber components. In one embodiment, a method of forming a hardmask includes positioning the substrate having a target layer within a processing chamber, forming a seed layer comprising metal silicide on the target layer and depositing a tungsten-based bulk layer on the seed layer, wherein the metal silicide layer and the tungsten-based bulk layer form the hardmask. In another embodiment, a method of conditioning the components of a plasma processing chamber includes flowing an inert gas comprising argon or helium from a gas applicator into the plasma processing chamber, exposing a substrate support to a plasma within the plasma processing chamber and forming a seasoning layer including metal silicide on an aluminum-based surface of the substrate support.

Abstract: Implementations of the present disclosure generally relate to the fabrication of integrated circuits. More particularly, the implementations described herein provide techniques for deposition of thick hardmask films on a substrate. In one implementation, a method of forming a hardmask layer on a substrate is provided. The method comprises applying a chucking voltage to a substrate positioned on an electrostatic chuck in a processing chamber, forming a seed layer comprising boron on a film stack disposed on a substrate by supplying a seed layer gas mixture in the processing chamber while maintaining the chucking voltage, forming a transition layer comprising boron and tungsten on the seed layer by supplying a transition layer gas mixture in the processing chamber and forming a bulk hardmask layer on the transition layer by supplying a main deposition gas mixture in the processing chamber.

Abstract: Embodiments of the present disclosure generally relates a shadow frame including two opposing major side frame members adjacent to two opposing minor side frame members coupled together with a corner bracket, wherein the corner bracket includes a corner inlay having legs that extend in directions generally orthogonal to each other.

Abstract: Embodiments of the present disclosure generally relates a shadow frame including two opposing major side frame members adjacent to two opposing minor side frame members coupled together with a corner bracket, wherein the corner bracket includes a corner inlay having legs that extend in directions generally orthogonal to each other.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for depositing metal silicide layers on substrates and chamber components. In one embodiment, a method of forming a hardmask includes positioning the substrate having a target layer within a processing chamber, forming a seed layer comprising metal silicide on the target layer and depositing a tungsten-based bulk layer on the seed layer, wherein the metal silicide layer and the tungsten-based bulk layer form the hardmask. In another embodiment, a method of conditioning the components of a plasma processing chamber includes flowing an inert gas comprising argon or helium from a gas applicator into the plasma processing chamber, exposing a substrate support to a plasma within the plasma processing chamber and forming a seasoning layer including metal silicide on an aluminum-based surface of the substrate support.