Lodestar Licensing Group LLC

Some embodiments include an integrated assembly having a first deck. The first deck has first memory cell levels alternating with first insulative levels. A second deck is over the first deck. The second deck has second memory cell levels alternating with second insulative levels. A cell-material-pillar passes through the first and second decks. Memory cells are along the first and second memory cell levels and include regions of the cell-material-pillar. An intermediate level is between the first and second decks. The intermediate level includes a buffer region adjacent the cell-material-pillar. The buffer region includes a composition different from the first and second insulative materials, and different from the first and second conductive regions. Some embodiments include methods of forming integrated assemblies.

Memory devices, systems including memory devices, and methods of operating memory devices are described, in which memory device are configured to add variable delays to a command. The variable delays may be provided by a host device (e.g., a test equipment) using a test mode of the memory devices. Alternatively, the variable delays may be stored in nonvolatile memory (NVM) components of the memory devices. Further, mode registers of the memory devices may be set to indicate that the command is associated with the variable delays stored in the NVM components. Further, the memory devices may include delay components configured to add the variable delays to the command. Such variable delays facilitate staggered execution of the command across multiple memory devices so as to avoid (or mitigate) issues related to an instantaneous, large amount of current drawn from a power supply connected to the memory devices.

Systems and methods for providing autonomous vehicle assistance are disclosed. In one embodiment, a method is disclosed comprising detecting a service condition in response to a fault occurring at an autonomous vehicle at a first location; coordinating service with a nearby service provider, the service provider providing a time window and a second location; predicting that the autonomous vehicle will be free to fulfill the service; driving the autonomous vehicle to the second location of the service provider during the time window; and returning the autonomous vehicle to the first location after the service is completed.

Microelectronic devices-having at least one conductive contact structure adjacent a silicide region-are formed using methods that avoid unintentional contact expansion and contact reduction. A first metal nitride liner is formed in a contact opening, and an exposed surface of a polysilicon structure is thereafter treated (e.g., cleaned and dried) in preparation for formation of a silicide region. During the pretreatments (e.g., cleaning and drying), neighboring dielectric material is protected by the presence of the metal nitride liner, inhibiting expansion of the contact opening. After forming the silicide region, a second metal nitride liner is formed on the silicide region before a conductive material is formed to fill the contact opening and form a conductive contact structure (e.g., a memory cell contact structure, a peripheral contact structure).

Embodiments of the disclosure are drawn to apparatuses and methods for a multi-bit duty cycle monitor. A clock signal may be provided to a memory in order to synchronize one or more operations of the memory. The clock signal may have a duty cycle which is adjusted by a duty cycle adjustor of the memory. The duty cycle of the adjusted clock signal may be monitored by a multi-bit duty cycle monitor. The multi-bit duty cycle monitor may provide a multi-bit signal which indicates if the duty cycle of the adjusted clock signal is above or below a target duty cycle value (or if the duty cycle is outside tolerances around the target duty cycle). The multi-bit duty cycle monitor may provide the multi-bit signal while access operations of the memory are occurring.

The present disclosure includes apparatuses and methods related to memory with an artificial intelligence (AI) accelerator. An example apparatus can include receive a command indicating that the apparatus operate in an artificial intelligence (AI) mode and perform AI operations using an AI accelerator based on a status of a number of register on the controller. The AI accelerator can include hardware, software, and or firmware that is configured to perform operations (e.g., logic operations, among other operations) associated with AI operations. The hardware can include circuitry configured as an adder and/or multiplier to perform operations, such as logic operations, associated with AI operations.

The invention relates to a system and method for navigating an autonomous driving vehicle (ADV) that utilizes ADV an-onboard computer and/or one or more ADV control system nodes in an ADV network platform. The on-board computer receives sensor data concerning one or more occupants occupying an ADV and/or the ADV itself and, upon a detection of an event, automatically initiates a dynamic routing algorithm that utilizes artificial intelligence to re-route the ADV to another destination, for example a healthcare facility. One or more embodiment of the system and method include an ADV on-board computer and/or one or more ADV network platform nodes that utilize in-memory processing to aid in the generation of routing, health and navigational information to advantageously navigate an ADV.

A vehicle is personalized to perform at least one action (e.g., control of acceleration or navigation of the vehicle) based on configuration data for a user of the vehicle. For example, when a car is rented by a user that is a driver, the car recognizes the driver and sets itself up accordingly. In some cases, an application on a mobile device of a user communicates the settings to the car when the user rents and/or hails the car. In one example, the mobile device may carry preference settings that can be downloaded to a ride-sharing vehicle or a rented vehicle to adjust controls relevant to the role of the driver.

Systems, methods and apparatus of intelligent wear-leveling with reduced write-amplification for data storage devices configured on autonomous vehicles. For example, a data storage device of a vehicle includes: storage media components; a controller configured to store data into and retrieve data from the storage media components according to commands received in the data storage device; an address map configured to map between: logical addresses specified in the commands received in the data storage device, and physical addresses of memory cells in the storage media components; and an artificial neural network configured to receive, as input and as a function of time, operating parameters indicative a data access pattern, and generate, based on the input, a prediction to determine an optimized operation for wear leveling among memory cells in the data storage device. The controller is configured to perform the optimized operation for wear leveling based on the prediction.

Memory devices, systems including memory devices, and methods of operating memory devices are described, in which memory device are configured to add variable delays to a command. The variable delays may be provided by a host device (e.g., a test equipment) using a test mode of the memory devices. Alternatively, the variable delays may be stored in nonvolatile memory (NVM) components of the memory devices. Further, mode registers of the memory devices may be set to indicate that the command is associated with the variable delays stored in the NVM components. Further, the memory devices may include delay components configured to add the variable delays to the command. Such variable delays facilitate staggered execution of the command across multiple memory devices so as to avoid (or mitigate) issues related to an instantaneous, large amount of current drawn from a power supply connected to the memory devices.