Google Patente

The present disclosure is generally directed to a modular busbar assembly that can be adjusted to fit varying rack power targets and connector interfaces, accommodating multiple connector geometries along one cost-effective assembly. The modular busbar assembly enables high power densities at powershelf regions by accommodating single- and double-pole connectors and connector contacts at various positions relative to the modular busbar assembly. The modular busbar assembly is customizable because the auxiliary busbar geometry may be altered independently from the primary busbar geometry.

The invention relates to a computer-implemented method to facilitate verified service requests by a user computing device, comprising receiving application program code distributed by an application service system, wherein the application program code comprises identifying information; extracting the identifying information from the application program code resident on the user computing device; transmitting an access request to the application service system, wherein the access request comprises the identifying information extracted from the application program code resident on the user computing device; receiving, from the application service system, an access token comprising the identifying information extracted from the application program code resident on the user computing device; and transmitting a service request including the access token to the application service system.

A slidable fiber optic adaptor slidable relative to a mounting support configured to be mounted to a fiber optic tray in a panel assembly is provided for fiber optic interconnection. The slidable adaptor may be slidable between a non-extended position and an extended position. Thus, when the fiber optic connectors having different polarities are connected to the slidable adaptors, the slidable fiber optic adaptor may be pulled out in the extended position to allow the fiber optic connectors with different polarities to be in a staggered configuration, thus, providing sufficient space therebetween for finger access for operators or technicians for ease of cable inspection and management.

The technology is generally directed to the continued use of a link between nodes of a network in which at least one of the lanes in the link has failed. Rather than identify the link as a failure in response to a lane failure, the traffic may be redistributed amongst the remaining lanes in the link. The redistribution of traffic may result in the link operating in a degraded mode. To mitigate the reduced traffic capacity of the degraded mode, the remaining links may be overclocked, such that the bandwidth of each link is increased to return the link to a traffic capacity corresponding to the initial capacity. In some examples, the traffic may be diverted to a redundant, otherwise inactive lane, thereby allowing for the traffic to be transmitted and received via the link, without any degradation in the performance of the link.

An example computing system retrieves information from one or more applications, and receives an indication of a natural language input. The computing system applies a machine learning model to at least a portion of the information and at least a portion of the indication of the natural language input to generate instructions for generating at least one graphical component, e.g., a custom widget. The instructions may include a temporal parameter for the at least one graphical component, in which the computing system may update, based on the temporal parameter, the instructions for generating the at least one graphical component to update the at least one graphical component.

The present application relates to systems and methods for regulating power for one or more electronic devices. In accordance with aspects of the disclosure, one or more micro-controllers are configured to regulate both peak and average power being consumed by devices within the system. The power being consumed within the system can be determined over different durations of time and multiple independent feedback loops may be used to regulate power within the system. In addition, the system can include a feedback loop that is configured to allow the system to enter into a low-power mode.

Generally disclosed herein is an approach for an optimized data computation for machine learning (ML) operations using a plurality of small-sized ML accelerators integrated into a general-purpose compute system-on-chip (SoC). One or more processors of the general-purpose compute SoC may be configured to receive a workload and divide the workload into a plurality of sub-workloads. The plurality of sub-workloads may be distributed among the plurality of small-sized ML accelerators. Each of the plurality of the ML accelerators can be configured to output a partial outcome. The outputs from each ML accelerator can be combined using atomic store operations using a dedicated opcode and a specified memory address.

Example embodiments of the present disclosure provide for an example method including obtaining data associated with media channels. The example method includes obtaining, by a computing device of a first platform, first channel data associated with a first media channel of an entity, the first media channel being on a first platform. Additionally, the method can include obtaining second channel data associated with a second media channel of the entity, the second media channel being on a second platform. Moreover, the method can include processing, using a machine-learning model, the first channel data and the second channel data to determine an allocation of resources to the first media channel and the second media channel. Furthermore, the method can include generating and presenting a recommendation based on the determination.

A method (400) includes receiving a time series anomaly detection query (20) from a user (12) and training one or more models (212) using a set of time series data values (152). For each respective time series data value in the set, the method includes determining, using the trained models, an expected data value for the respective time series data value and determining a difference between the expected data value and the respective time series data value. The method also includes determining that the difference between the expected data value and the respective time series data value satisfies a threshold (314). In response to determining that the difference between the expected data value and the respective time series data value satisfies the threshold, the method includes determining that the respective time series data value is anomalous and reporting the anomalous respective time series data value (152A) to the user.

A computer-implemented method comprising: receiving, by an application (108) executing on a user device (102) that is not an application store, a single content response from a content server (120), wherein the single content response comprises both digital content (112) referencing a second application that is not installed on the user device and application store data (116) for the second application; in response to receiving the single content response and when the application is an active application, providing, by the active application and in a user interface (110) of the active application, the digital content concurrently with an application store user interface (114) that includes (i) the application store data for the second application and (ii) an install element (118) for triggering installation of the second application on the user device from within the active application; detecting user interaction with the install element provided within the user interface of the active application; and in response to detecting the user interaction with the install element, triggering a download of the second application independent of launching an application for the application store.

A hash table system, including a plurality of hash tables, associated with respective hash functions, for storing key-value pairs; an overflow memory for storing key-value pairs moved from the hash tables due to collision; and an arbiter for arbitrating among commands including update commands, match commands, and rehash commands, wherein for each system clock cycle, the arbiter selects as a selected command one of an update command, a match command, or a rehash command, and wherein the hash table system completes execution of each selected command within a bounded number of system clock cycles.

A system for managed data transfer in compute network, includes a first data store and a second data store. A data transfer agent and one or more servers plan and implement a data transfer to move data stored in the first data store to the second data store via the data transfer agent. The data agents are centrally managed by a control plane and are initialized with authentication credentials that are needed to effectuate the data transfer. The source data universe and the destination data universe may have different authentication interfaces. The data transfer agent will use a first credential to access data at the source and a second credential to copy the requested data to the destination.

In accordance with aspects of the disclosure, an OLAP database is used to store a plurality of tables that are each associated with a particular client or tenant and which are each configured in accordance with a table-specific schema of metadata. A catalog service can be configured to allow for efficient read and write operations in connection with the tables stored within the OLAP database.

This system and method described herein provide for efficient monitoring of machine learning models in a data warehouse toolset integrated with a cloud platform. Computation of statistics and anomalies for training data and serving data for the machine learning models may be distributed across physical shards in the data warehouse. Computed results may be converted to a format compatible with external platforms. Model monitoring may be supported using table valued functions (TVFs) to compute descriptive statistics of data and to compute the feature distribution difference between two different pieces of data, a scalar function to validate statistics, and an internal task handler to parse monitoring statistics results and save it as a job to make it visualizable.

A method includes detecting a session between a mobile device and an alternative playback device. In response to detecting that the session has been established, the method also includes presenting a graphical user interface (GUI) on a screen of a mobile device of a user including a voice search GUI element representing a voice search, receiving a user selection of the voice search GUI element, receiving an audio input of the user to request a search of one or more media items, the audio input specifying one or more search criteria for the search, and submitting a textual search query derived from the audio input for processing, wherein a result of the search is to be presented to the user on a screen of the alternative playback device.

A method performed by a device having, and a system comprising, a plurality of sensor controllers, wherein each sensor controller of the plurality of sensor controllers is configured to implement a respective decimation filter that is configured to generate a single sample output from multiple input samples generated by a corresponding sensor of a plurality of sensors. The method comprises, and a non-master sensor controller of the plurality of sensor controllers is configured to perform operations comprising, detecting, by a first sensor controller of the plurality of sensor controllers, an update in a memory for the first sensor controller; determining, based on the update and by the first sensor controller, whether to operate the first sensor controller as a first master sensor controller; and in response to determining to operate the first sensor controller as the first master sensor controller, configuring the first sensor controller in a master controller mode, wherein a sensor controller in the master controller mode is configured to generate a sync signal upon receiving a threshold number of input samples generated by the respective sensor for the sensor controller, and wherein the sync signal causes each sensor controller in the plurality of sensor controllers operating in a non-master controller mode to implement the respective decimation filter to generate the single sample output.

Implementations set forth herein relate to an automated assistant that is responsive to spoken utterances spoken by multiple different users simultaneously, or otherwise within a narrow window of time, in furtherance of initializing one or more actions. For instance, when a primary user is interacting with an automated assistant, a secondary user may also provide a spoken utterance. In response, the automated assistant can selectively determine whether any input from the secondary user should affect a request from the primary user. In some instances, the automated assistant can elect to either disregard the secondary input, separately respond to the secondary input, or use some amount of content of the secondary input to further the request from the primary user. Incorporation of secondary input when fulfilling a primary request can be fluidly performed to resemble human conversation and eliminate any unnecessary engagement between the automated assistant and the users.

Implementations are directed to generating voice-based chatbot policy override(s) and/or utilizing voice-based chatbot policy override(s) in conjunction with existing voice-based chatbot(s). The voice-based chatbot policy override(s) can correspond to, for example, machine learning (ML) model(s) that supplement functionality of the existing voice-based chatbot(s). Notably, the voice-based chatbot policy override(s) are associated with rule(s) (e.g., by virtue of training the ML model(s) that correspond to the voice-based chatbot policy override(s)) for when the voice-based chatbot policy override(s) should be utilized in lieu of the existing voice-based chatbot(s) in responding to spoken utterance(s) of human user(s) engaged in corresponding conversation(s) with the voice-based chatbot policy override(s). Nonetheless, from a perspective of the human user(s), it appears as if they are still engaging in the corresponding conversations with the existing voice-based chatbot(s). Thus, the functionality of the existing voice-based chatbot(s) can be supplemented without having to re-train the existing voice-based chatbot(s).

Systems and methods for managing deployment of applications and services within a network having a plurality of edge platforms. A domain name service (DNS) request from a client device requesting for content from a third-party provider is modified to include location information indicating a client device location. A deployment manager uses the location information in the modified request to select a nearby edge platform for servicing the request. Changes to the edge platform servicing the request may be imitated based on changes in location information received in future requests. The deployment manager may also maintain a database to track resources that are already deployed in nearby edge platforms, conserving resources when selecting the edge platforms to service requests. The deployment manager also directs third-party content providers to the edge platform using a separate service so that communication with third-party content providers does not share the location information.

Aspects of the disclosure are directed to a side sideband interface (SSBI). The SSBI is a die-to-die (D2D) interface configured for various protocols to enable cross-die communication with higher robustness and flexibility and lower cost. The SSBI includes a control status register (CSR) wrapper containing the CSRs for configuring and monitoring the SSBI, a protocol handler for converting the various protocols both to and from a standard streaming interface as well as performing arbitration, and a link layer for performing serialization and deserialization of data as well as flow control management and error detection.

A method that includes receiving a plurality of workloads (102), each associated with respective security criteria (104) and scheduled for execution on a distributed computing system (140) divided into a plurality of security rings (160) each associated with a respective subset of computing devices (162) of the distributed computing system that is physically isolated from the other security rings. For each respective workload, the method includes determining, using the respective security criteria, a security level (410) of the respective workload and identifying, using the security level of the respective workload, one or more of the plurality of security rings that are eligible for executing the respective workload. The method also includes executing the respective workload on one or more computing devices selected from one of the respective subsets of computing devices associated with the identified one or more of the plurality of security rings eligible for executing the respective workload.

A method in a radio access network, RAN, communicating with a user equipment, UE, the method comprising: sending to the UE a conditional configuration and a corresponding condition for a conditional PSCell addition or change procedure, wherein the corresponding condition is to be satisfied before the UE can communicate via a candidate cell of the RAN using the conditional configuration; after sending the conditional configuration and the corresponding condition, and before the corresponding condition is satisfied, receiving UE information from the UE, the UE information including a preferred configuration, in-device coexistence, IDC, assistance information, sidelink information, or multicast and/or broadcast service, MBS, interest information; and after the corresponding condition is satisfied, again receiving the UE information from the UE.

Devices, systems, and methods for isolating an insect pupa from an aqueous solution including a plurality of insect pupae. An isolation device may include a primary channel through which the aqueous solution and insect pupae travel, an outlet, and a secondary channel that intersects the primary channel. The secondary channel may transport a fluid to add it to the primary channel between an inlet and the outlet. When the sealable outlet is closed, an insect pupa located downstream of the intersection of the primary and secondary channels remains stationary while any insect pupae upstream of the intersection are pushed towards the inlet. The systems and methods describe herein may also provide for identifying and sorting insect pupae.

Estimating throughput for an input program executing on a processing architecture by calculating a plurality of cumulative distribution functions (CDFs) for each parameter of a plurality of parameters for describing processing architectures, the CDFs of the plurality of CDFs corresponding to respective ones of values for the parameter, and each CDF of the plurality of CDFs specifying a cumulative distribution of throughput calculations associated with the corresponding value and the input program, and the pluralities of CDFs generated for the parameters making up a set of pluralities of CDFs; and using the set of pluralities of CDFs and a machine learning model to estimate the throughput for the input program executing on the processing architecture based on a set of parameter values specifying the processing architecture.

Aspects of the disclosure are directed to enhancing RAG through a structured schema for RAG that captures a wider range of RAG techniques to serve as a foundation for improving performance and an optimization framework for efficiently serving the wider range of RAG techniques based on significant performance variability across RAG workloads. The optimization framework may achieve up to a 2x increase or more in query per second (QPS) per chip compared to alternative RAG frameworks built on LLM-system extensions.

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A method for on-device AI during a virtual meeting includes receiving, at a first client device of a first participant of one or more participants of a virtual meeting, a request to perform a task pertaining to the virtual meeting from a second client device of a second participant of the plurality of participants; obtaining, at the first client device, first text data based on first audio data associated with a first audio stream produced by the second client device; performing, using an AI model of the first client device and using the first text data as input to the AI model, the task pertaining to the virtual meeting; and providing, by the first client device, information associated with the performed task pertaining to the virtual meeting to the second client device.

Provided are methods, systems, devices, and tangible non-transitory computer readable media for offline mapping and navigation. The disclosed technology determines a current region associated with a current location of a navigation device. Predicted travel destinations from the current region are determined based on aggregated travel data. The aggregated travel data can include previous travel destinations from within the current region. Based on the current region and the predicted travel destinations, additional regions associated with the current region are determined. Further, connectivity information is determined based on network data. The connectivity information is associated with network connectivity within the additional regions. The additional regions is prioritized based on the connectivity information. Furthermore, portions of offline map data associated with the respective additional regions are sent to the navigation device in an order partly based on the priority of the additional regions.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speaker diarization are disclosed. In one aspect, a method includes the actions of receiving audio data corresponding to an utterance. The actions further include determining that the audio data includes an utterance of a predefined hotword spoken by a first speaker. The actions further include identifying a first portion of the audio data that includes speech from the first speaker. The actions further include identifying a second portion of the audio data that includes speech from a second, different speaker. The actions further include transmitting the first portion of the audio data that includes speech from the first speaker and suppressing transmission of the second portion of the audio data that includes speech from the second, different speaker.

Aspects of the disclosure are directed to a system for incorporating a CVBG (Chirped Volume Bragg Grating) into a prism to form a P-CVBG (Prism-Chirped Volume Bragg Grating) optical element for channel dispersion compensation. A prism region is configured to receive optical signals with multiple wavelengths and provide the wavelengths to the CVBG region by spatially separating the optical signals into various wavelengths. The CVBG region is configured to compensate for dispersion of the multiple wavelengths by reflecting the various wavelengths at different depths within the gratings of the CVBG region.

A customer gains access to cloud networking resources through a customer device, such as a router providing a point of presence (POP) to the network. Due to limitations of remote equipment such as routers, complete routing information for data packets may not be available from the origin due to the dynamic nature of the network and security requirements. Proxy machines are placed at the network edge that serve as a proxy for routing network data packets to the virtual network Placing proxy machines at the network edge requires space, power and maintenance of the programmable processing machines serving as proxies. Techniques for bypassing proxy machines to reduce network congestion and latency are described. Data packets are selected to bypass proxies when additional routing information is not needed for the packet. Proxy machines may be implemented as virtual machines within a data center hosting the virtual network.

A method (400) for remote attestation includes establishing, using a cryptographic protocol (20), a communication session (22) between a first computing device (10a) and a second computing device (10b). The communication session includes communications encrypted by an ephemeral session key (24). The method includes receiving, at the first communication device via the communication session, from the second computing device, an attestation request (172) requesting the first computing device to provide an attestation report (162). The method includes generating, by the first computing device, the attestation report based on the ephemeral session key and sending, using the communication session, the attestation report to the second computing device.

One aspect is a method for recovering a rename map table for an out-of-order processor after a flush operation, the method includes executing, by an out-of-order processor, instructions including a flush operation resulting from a branch misprediction of a branch instruction. The out-of-order processor includes a reorder buffer tracking a program order for the instructions and a rename map table mapping multiple logical registers to multiple physical registers. The method also includes, in response to executing the flush operation, grouping the instructions, ordered from oldest to youngest according to the program order tracked in the reorder buffer, into multiple of segments, comparing the multiple segments to identify segments that contain a youngest superset of instructions that wrote to the multiple logical registers between a head of the reorder buffer and the branch instruction, and performing a recovery walk of the identified segments to recover the rename map table.

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A method includes identifying, by a processor, a media stream comprising a sequence of encoded video frames and estimating, in the sequence of video frames, a share of video frames that are fragmented into respective pluralities of network packets, wherein each plurality of network packets comprises a network packet having a size below a predefined packet threshold size. Whether the share exceeds a predefined threshold value is determined and responsive to determining that the share exceeds a predefined threshold value, a target bitrate of the video stream is reduced.

Techniques are described herein for improving performance of machine learning model(s) and thresholds utilized in determining whether automated assistant function(s) are to be initiated. A method includes: receiving, via one or more microphones of a client device, audio data that captures a spoken utterance of a user; processing the audio data using a machine learning model to generate a predicted output that indicates a probability of one or more hotwords being present in the audio data; determining that the predicted output satisfies a secondary threshold that is less indicative of the one or more hotwords being present in the audio data than is a primary threshold; in response to determining that the predicted output satisfies the secondary threshold, prompting the user to indicate whether or not the spoken utterance includes a hotword; receiving, from the user, a response to the prompting; and adjusting the primary threshold based on the response.

Implementations set forth herein relate to an automated assistant that can initialize execution of an assistant command associated with an interpretation that is predicted to be responsive to a user input, while simultaneously providing suggestions for alternative assistant command(s) associated with alternative interpretation(s) that is/are also predicted to be responsive to the user input. The alternative assistant command(s) that are suggested can be selectable such that, when selected, the automated assistant can pivot from executing the assistant command to initializing execution of the selected alternative assistant command(s). Further, the alternative assistant command(s) that are suggested can be partially fulfilled prior to any user selection thereof. Accordingly, implementations set forth herein can enable the automated assistant to quickly and efficiently pivot between assistant commands that are predicted to be responsive to the user input.

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