Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: Methods, systems, and media for determining playlist title coherence and quality are provided. In some embodiments, a method for generating playlist recommendations includes: determining, using a hardware processor, a title of a playlist; generating, using the hardware processor, a byte-level representation of the title based on the title of the playlist; determining, using the hardware processor, an embedded representation of the title based on the byte-level representation; determining, using the hardware processor, a perplexity score of the title by inputting the embedded representation of the title into a trained language model, wherein the perplexity score is an output of the trained language model; and causing, using the hardware processor, a recommendation based on the perplexity score of the title to be presented.

Abstract: A system for acoustic behavior feedback includes a light emitter and a microphone. Ambient sound data from the microphone may be compared to a threshold sound level, and one of a plurality of settings for the light emitter may be selected based at least in part on the comparison between the ambient sound data and threshold sound level. Each of the plurality of settings corresponds to a respective sound level alert as feedback for at least one person proximate the microphone and the light emitter.

Abstract: Systems and methods for recognizing polling questions from a conference call discussion are provided. One or more text strings including a textual form of one or more verbal phrases provided by one or more participants of a conference call are identified. The one or more text strings are provided as input to a trained machine learning model. One or more outputs from the trained machine learning model are obtained. A level of confidence that a verbal phrase of the one or more verbal phrase provided by the one or more participants includes a question associated with polling during the conference call is extracted from the one or more outputs. In response to a determination that the level of confidence satisfies a confidence criterion, the verbal phrase is designated as a polling question presented during the conference call.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for constructing and programming quantum hardware for machine learning processes. A Quantum Statistic Machine (QSM) is described, consisting of three distinct classes of strongly interacting degrees of freedom including visible, hidden and control quantum subspaces or subsystems. The QSM is defined with a programmable non-equilibrium ergodic open quantum Markov chain with a unique attracting steady state in the space of density operators. The solution of an information processing task, such as a statistical inference or optimization task, can be encoded into the quantum statistics of an attracting steady state, where quantum inference is performed by minimizing the energy of a real or fictitious quantum Hamiltonian. The couplings of the QSM between the visible and hidden nodes may be trained to solve hard optimization or inference tasks.

Abstract: Implementations relate to role change requests that can be delayed and/or implemented according to circumstances associated with an interaction between a user and an automated assistant. A role change request can cause a designation of auxiliary devices (e.g., earbuds and/or any other peripheral devices) to be changed, and at least cause a different auxiliary device to be tasked with directly communicating with a principal device (e.g., a cellular phone). For instance, when an auxiliary device is requesting a role change request during an assistant interaction, an operating system of the principal device can identify factors that form the basis for determining whether to immediately implement the role change request or, instead, to delay or refuse implementation of the role change request. When the factors indicate that the role change request is not particularly urgent, the operating system can cause the role change request to be delayed until the assistant interaction is complete.

Abstract: Methods, systems, and apparatus for receiving a request that includes a user identifier of a user that submitted a search query and an entity identifier of an entity that is referenced by the search query, identifying a plurality of knowledge elements that are related to the entity, identifying, in a consumption database, one or more items that have been indicated as consumed by the user and that are associated with the entity that is referenced by the search query, assigning rank scores to the plurality of knowledge elements, based at least on identifying the one or more items, selecting one or more of the knowledge elements from among the knowledge elements based at least on the rank scores assigned to the knowledge elements, and providing, in response to the request, information associated with the entity and the one or more selected knowledge elements.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using additive and subtractive noise for preserving the privacy of users. In one aspect, a method includes obtaining a first set of genuine user group identifiers that identify user groups that include a user as a member. A second set of user group identifiers is generated for the user by removing zero or more genuine user group identifiers from the first set to generate the second set and adding, to the second set, one or more fake user group identifiers for user groups that do not include the user as a member. A probabilistic data structure is generated based on the second set of user group identifiers. The probabilistic data structure is transmitted. Data indicating a set of digital components including at least one digital component selected based on the probabilistic data structure is received.

Abstract: A global-level manager access a work order from a client and parameters associated with the work order. A service level agreement to meet the work order parameters is determined. The service level agreement includes a price. An indication is received from the client that the service level agreement is accepted. The one or more input files are partitioned into multiple shards, and the work order into multiple jobs. The jobs are distributed among a plurality of clusters to be processed using underutilized computing resources in the clusters. The job outputs are combined to form the work order output. The jobs are monitored to insure that the deadline for completion of the work order will be met.

Abstract: Methods, systems and apparatus for correcting a result of a quantum computation.

Abstract: Some implementations are directed to generating a personal database entry for a user based on free-form natural language input formulated by the user via one or more user interface input devices of a computing device of the user. The generated personal database entry may include one or more terms of the natural language input and descriptive metadata determined based on one or more terms of the natural language input and/or based on contextual features associated with receiving the natural language input. Some implementations are directed to generating, based on one or more personal database entries of a user, output that is responsive to further free-form natural language input of the user. For example, one or more entries that are responsive to further natural language input of the user can be identified based on matching content of those entries to one or more search parameters determined based on the further input.

Abstract: Methods, systems and apparatus for performing indexed operations using a unary iteration quantum circuit. In one aspect, a method includes encoding an index value in an index register comprising index qubits; encoding the index value in a control register comprising multiple control qubits; and repeatedly computing and uncomputing the control qubits to perform, conditioned on the state of the control qubits, the operation on one or more target qubits corresponding to the index value, wherein during the encoding, computing and uncomputing: the multiple control qubits are made available in sequence, and the multiple control qubits correspond to a one-hot encoding of the encoded index value.

Abstract: In general, the subject matter described in this disclosure can be embodied in a display panel. The display panel includes a first area of multiple pixels that has a first density of light emitting diodes (LEDs), and that has an equal representation of LEDs of a first color, a second color, and a third color. Each pixel in the first area has: (i) a first sub-pixel comprising an LED of the first color, (ii) a second sub-pixel comprising an LED of the second color, and (iii) a third sub-pixel comprising an LED of the third color. The display panel includes a second area of multiple pixels that borders the first area, that has a second density of LEDs that is lower than the first density, and that has an unequal representation of LEDS of the first color, the second color, and the third color.

Abstract: An aspect of the disclosed technology is a replay unit that enables replaying computations on unused or empty ALU slots. The replay unit may be added on a per lane basis or within a lane in a SIMD unit or device.

Abstract: Dynamically adapting provision of notification output to reduce distractions and/or to mitigate usage of computational resources. In some implementations, an automated assistant application predicts a level of engagement for a user and determines, based on the predicted level of engagement (and optionally future predicted level(s) of engagement), provisioning (e.g., whether, when, and/or how) of output that is based on a received notification. For example, the automated assistant application can, based on predicted level(s) of engagement, determine whether to provide any output based on a received notification, determine whether to suppress provision of output that is based on the received notification (e.g.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing location tagging. The radar system has sufficient spatial resolution to recognize different external environments associated with different locations (e.g., recognize different rooms or different locations within a same room). Using the radar system, the smart device can achieve spatial awareness and automatically activate user-programmed applications or settings associated with the different locations. In this way, the radar system enables the smart device to provide a location-specific shortcut for various applications or settings. With the location-specific shortcut, the smart device can improve the user's experience and reduce the need to repeatedly navigate cumbersome interfaces.

Abstract: Systems and methods of the present disclosure are directed to a method for predicting semantic similarity between documents. The method can include obtaining a first document and a second document. The method can include parsing the first document into a plurality of first textual blocks and the second document into a plurality of second textual blocks. The method can include processing each of the plurality of first textual blocks and the second textual blocks with a machine-learned semantic document encoding model to obtain a first document encoding and a second document encoding. The method can include determining a similarity metric descriptive of a semantic similarity between the first document and the second document based on the first document encoding and the second document encoding.

Abstract: Systems and methods are provided that train a machine-learned language encoding model through the use of a contrastive learning task. In particular, the present disclosure describes a contrastive learning task where the encoder learns to distinguish input tokens from plausible alternatives. In some implementations, on each training example the proposed method masks out some subset (e.g., 15%) of the original input tokens, replaces the masked tokens with samples from a “generator” (e.g., which may be a small masked language model), and then trains the encoder to predict whether each token comes from the original data or is a replacement produced by the generator.

Abstract: A computing system and method that can be used for a mapping system that can recommend paths for navigational routing to a primary user. In particular, a primary user may be interested in navigational routes that secondary users, who may be the same or different from the primary user, have taken in the past. Even more particularly, the mapping systems described herein can provide improved user navigational services by leveraging the insight that users who have previously been in a similar situation (e.g., on vacation, in icy conditions, etc.) may wish to take the same route as they did the last time. Alternatively, users may desire to take routes based on routes which were taken by other users who are connected (e.g., via social media, address books, etc.).