Abstract: The described techniques and apparatuses enable memory-request priority up-leveling. A memory request is received over a virtual channel, VC, and is then added to a memory-request buffer with an original priority-level for the memory request and an indication that the memory request is associated with a virtual channel identification, VCID, of the VC. Related memory requests within the memory-request buffer are also indicated as being associated with the VCID. Responsive to determining that an up-level indication for the VCID is asserted over a side channel, the original priority-levels of the memory request, and other memory-requests in the memory-request buffer having an indication of the VCID, are increased to respective up-leveled priority levels. Responsive to determining that the up-level indication is no longer asserted, the up-leveled priority levels are returned to respective original priority-levels.

Abstract: Implementations relate to managing multimedia content that is obtained by large language model(s) (LLM(s)) and/or generated by other generative model(s). Processor(s) of a system can: receive natural language (NL) based input that requests multimedia content, generate a response that is responsive to the NL based input, and cause the response to be rendered. In some implementations, and in generating the response, the processor(s) can process, using a LLM, LLM input to generate LLM output, and determine, based on the LLM output, at least multimedia content to be included in the response. Further, the processor(s) can evaluate the multimedia content to determine whether it should be included in the response. In response to determining that the multimedia content should not be included in the response, the processor(s) can cause the response, including alternative multimedia content or other textual content, to be rendered.

Abstract: In some aspects, a method includes executing a streaming application configured to stream a media content item on a display of a television device, and receiving, from the streaming application, a request to generate a token. The method includes, in response to the request, obtaining a user identifier of a user account of a media platform, obtaining a plurality of signals used to select promoted content for the user account, generating the token to include the user identifier and the plurality of signals, and encrypting the token to generate an encrypted token. The encrypted token is configured to be included in a fetch request to retrieve a promoted content item, personalized to the user account, from a promoted content server associated with the media platform. The promoted content item is configured to be inserted into playback of the media content item by the streaming application.

Abstract: Data are maintained in a distributed computing system that describe a graph. The graph represents relationships among items. The graph has a plurality of vertices that represent the items and a plurality of edges connecting the plurality of vertices. At least one vertex of the plurality of vertices includes a set of label values indicating the at least one vertex's strength of association with a label from a set of labels. The set of labels describe possible characteristics of an item represented by the at least one vertex. At least one edge of the plurality of edges includes a set of label weights for influencing label values that traverse the at least one edge. A label propagation algorithm is executed for a plurality of the vertices in the graph in parallel for a series of synchronized iterations to propagate labels through the graph.

Abstract: A media application obtains a video that includes an audio portion. The media application separates the audio portion into a plurality of channels, where each channel corresponds to a particular audio source. An on-screen classifier model obtains an indication of whether the particular audio source for each channel is depicted in the video. An audio-type classifier model determines, an auditory object classification for each channel. The media application determines a respective gain for each channel based on the indication of whether the particular audio source for the channel is depicted in the video and the auditory object classification for the channel. The media application modifies each channel by applying the respective gain. The media application mixes the modified channels with the audio portion to generate a combined audio.

Abstract: A hosted storage system receives a storage request that includes a single object and conforms to an API implemented by the hosted storage system. The API is designed to only support a single object in a storage request. The hosted storage system, in response to determining that the single object is an archive file, extracts each of the bundled files from the archive file and stores each of the extracted files in the hosted storage system such that each of the extracted files is separately accessible by the client system over the network.

Abstract: A computer implemented method includes providing a user interface to a user that includes an original image and an option to generate a high-resolution portion of the original image. The method includes receiving a selection of the option to generate the high-resolution portion of the original image and dimensions of a portion of the original image. The method includes providing the portion of the original image as input to a machine-learning model. The method includes generating, with the machine-learning model, the high-resolution image. The method includes updating the user interface to include the high-resolution portion of the original image.

Abstract: A method includes receiving an audible response to a query, and prior to playing back the audible response, providing, for output from an acoustic speaker, an alignment output audio stream that encodes an audio watermark. The method also includes receiving an alignment input audio stream captured by a microphone array and encoding an acoustic echo of the audio watermark, processing the alignment input audio stream to detect the acoustic echo, and determining a time alignment value between the alignment output audio stream and the alignment input audio stream. The method also includes playing back a response output audio stream that encodes the audible response and receiving an input audio stream. The input audio stream includes acoustic echo corresponding to the audible response played back. The method also includes processing the input audio stream to generate a respective target audio signal that cancels the acoustic echo.

Abstract: A method includes obtaining labeled training data including a plurality of spoken terms spoken during a conversation. For each respective spoken term, the method includes generating a corresponding sequence of intermediate audio encodings from a corresponding sequence of acoustic frames, generating a corresponding sequence of final audio encodings from the corresponding sequence of intermediate audio encodings, generating a corresponding speech recognition result, and generating a respective speaker token representing a predicted identity of a speaker for each corresponding speech recognition result. The method also includes training the joint speech recognition and speaker diarization model jointly based on a first loss derived from the generated speech recognition results and the corresponding transcriptions and a second loss derived from the generated speaker tokens and the corresponding speaker labels.

Abstract: A method for distributing encryption keys includes receiving a table associated with a particular user, the table including a plurality of data blocks and splitting the table into a plurality of tablets including a corresponding portion of data blocks. The method also includes generating a resource key uniquely associated with the table and for each tablet generating a unique data encryption key for the corresponding tablet to encrypt with the unique data encryption key. The method also includes encrypting each data encryption key with the resource key and distributing control of each encrypted tablet and each corresponding encrypted data encryption key to a plurality of tablet servers, each controlling one or more of the encrypted tablets. The resource key transmits to a remote entity causing the remote entity to encrypt the resource key with a user key associated with the particular user and transmit the encrypted resource key.

Abstract: A method includes receiving a conversational training dataset including a plurality of conversational training samples, each training sample associated with a corresponding conversation and including: corresponding audio data characterizing a corresponding current utterance spoken by a user during a current turn in the corresponding conversation; a corresponding context for the corresponding current utterance including a transcript of a previous turn in the corresponding conversation that precedes the current turn; a corresponding ground-truth transcription of the corresponding current utterance; and a CoT annotation representing a corresponding logical relationship between the corresponding current utterance and the previous turn.

Abstract: The present disclosure provides systems and methods for transmitting data to a pair of truly wireless devices. A first device, which may be considered the primary device, may determine a first data packet was received. The first device may also determine the first data packet was not received by a second device of the pair of truly wireless devices. In response to determining the second device did not receive the first data packet, the first device may request the first data packet be retransmitted.

Abstract: A method includes receiving, for presentation to a user of a user device, image data representing an image. The method also includes generating, using a textual story generative model, based on the image data, a textual story for the image, and generating, based on the textual story for the image, textual story audio data representing the textual story for the image. The method further includes providing, for audible output from the user device, the textual story audio data.

Abstract: A method for managing cloud infrastructure includes receiving, from a user of a user device, a cloud infrastructure modification request requesting modification to cloud infrastructure. The cloud infrastructure modification request includes abstract configuration data derived from a user interaction with a graphical user interface (GUI) executing on the user device. The method includes translating the abstract configuration data into a configuration command. The configuration command describes a configuration of the cloud infrastructure. The method includes updating a configuration file with the configuration command. The configuration file includes one or more cloud infrastructure specifications for the cloud infrastructure and is controlled by a source control management system. The method includes provisioning, using the updated configuration file, the cloud infrastructure.

Abstract: This document describes systems and techniques for implementing personalized suggestions for a user interacting with a facility management system based on contextual metadata to assist the user in controlling the facility management system. For example, a system includes a request module configured to receive a request from a user. A metadata module is configured to access and identify metadata related to a content or context of the request. A large language model (LLM) module is configured to receive the request and the metadata and to generate a suggestion relevant to the content or context of the request. A suggestion module is configured to present the suggestion to the user.

Abstract: A computer-implemented method includes receiving a natural language command from a user that requests a digital assistant to provide a notification to a user device associated with the user upon occurrence of a particular event. The method also includes processing the natural language command using a natural language understanding module to determine one or more event conditions that each indicate the occurrence of the particular event and obtaining event information of the particular event. While the user device is in a notification silencing mode, the method includes determining that at least one of the one or more event conditions is satisfied and providing the notification for output from the user device in response to determining that at least one of the one or more event conditions is satisfied. The notification, when output from the user device, notifies the user of the occurrence of the particular event.

Abstract: This document describes systems and techniques for presenting intermediate media to a user that has presented a media request. In aspects, a media request for requested media is received from an input device. The media request is provided to a media service to serve the requested media to a requested device. The media request is processed to identify attributes of the media request indicative of a subject matter of the requested media. Based on the identified attributes of the media request, intermediate media is accessed including one or more images related to the identified attributes. The intermediate media is delivered to the requested device. Accordingly, the intermediate media provides content to engage the user while the user waits for the requested media to be delivered.

Abstract: A method includes receiving training data that includes unspoken text utterances, un-transcribed non-synthetic speech utterances, and transcribed non-synthetic speech utterances. Each unspoken text utterance is not paired with any corresponding spoken utterance of non-synthetic speech. Each un-transcribed non-synthetic speech utterance is not paired with a corresponding transcription. Each transcribed non-synthetic speech utterance is paired with a corresponding transcription. The method also includes generating a corresponding synthetic speech representation for each unspoken textual utterance of the received training data using a text-to-speech model. The method also includes pre-training an audio encoder on the synthetic speech representations generated for the unspoken textual utterances, the un-transcribed non-synthetic speech utterances, and the transcribed non-synthetic speech utterances to teach the audio encoder to jointly learn shared speech and text representations.

Abstract: A method for speech conversion includes receiving, as input to an encoder of a speech conversion model, an input spectrogram corresponding to an utterance, the encoder including a stack of self-attention blocks. The method further includes generating, as output from the encoder, an encoded spectrogram and receiving, as input to a spectrogram decoder of the speech conversion model, the encoded spectrogram generated as output from the encoder. The method further includes generating, as output from the spectrogram decoder, an output spectrogram corresponding to a synthesized speech representation of the utterance.