Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network.

Abstract: Methods, systems and computer program products are provided for creating and retrieving an immutable digital testimony involving activating a process on a device with a unique identifier and authenticating the creator of an immutable digital testimony using a unique user ID registered with a testimony network. The device activates associated cameras to generate a media stream. Frames are hashed using a selected scheme to create stream hashes, forming a live stream hash, and capturing metadata to be recorded on a blockchain. The stream media and hashing scheme are transmitted to a cloud server for storage, with cloud or distributed file system (DFS) addresses retrieved to determine where the media is saved. The live stream media is encrypted and sent to the DFS, encrypted media addresses are received, and the stream media is saved locally on the device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network.

Abstract: Techniques for image segmentation of a digital pathology image may include accessing an input image that depicts a section of a tissue; and generating a segmentation image by processing the input image using a generator network, the generator network having been trained using a data set that includes a plurality of pairs of images. The segmentation image indicates, for each of a plurality of artifact regions of the input image, a boundary of the artifact region. At least one of the plurality of artifact regions depicts an anomaly that is not a structure of the tissue. Each pair of images of the plurality of pairs includes a first image of a section of a tissue, the first image including at least one artifact region, and a second image that indicates, for each of the at least one artifact region of the first image, a boundary of the artifact region.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network.

Abstract: A composition includes an aqueous colloidal dispersion of a nanomaterial. The nanomaterial includes, disposed on a surface of the nanomaterial, a first coupling agent including silane and a functional group including an amino acid. The nanomaterial includes, disposed on the surface of the nanomaterial, a second coupling agent including silane and a polymer with a molecular weight between 1,000 and 20,000.

Abstract: A method for transferring digital pathology annotations between images of a tissue sample may include identifying a first set of points for a geometric feature of a first image of a section of a tissue sample; identifying a corresponding second set of points for a corresponding geometric feature of a second image of a same tissue sample, the second image being an image of another section of the tissue sample; determining coordinates of the first set of points and coordinates of the second set of points; determining a transformation between the first set of points and the second set of points; and applying the transformation to a set of digital pathology annotations on the first image to transfer the set of digital pathology annotations within the first image to the second image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. One of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.

Abstract: A rent-to-own (RTO) transaction system and method includes a customer computer and retail computer. A product inventory is displayed on the customer computer, and a product selection is made by a customer via the customer computer. Identifying information is received from the customer, and based thereon, the identity of the customer is verified. An RTO agreement based on the product selection and the identifying information is developed and displayed on the customer computer. An execution of the RTO agreement is made by the customer via the customer computer and received by the retail computer.

Abstract: Embodiments disclosed herein relate to transition of a radio frequency module between a first operating state and a second operating state. The first and second states may be passive/slow (e.g., non-active) states or active/fast states. A passive state may include a sleep state, an idle state, an off state, or a low power state. An active state may include a receiving state or a transmitting state, for receiving and transmitting signals, respectively. If the first operating state is an active state and the second operating state is a passive state, the transition from the first operating state may be delayed such that the radio frequency module transitions directly from the first operating state to a third operating state. This enables the radio frequency module to avoid entering a passive second state with a slow settling time which can interfere with communications and operation of the radio frequency module.

Abstract: A composition includes an aqueous colloidal dispersion of a nanomaterial. The nanomaterial includes, disposed on a surface of the nanomaterial, a first coupling agent including silane and a functional group including an amino acid. The nanomaterial includes, disposed on the surface of the nanomaterial, a second coupling agent including silane and a polymer with a molecular weight between 1,000 and 20,000.

Abstract: A composition includes an aqueous colloidal dispersion of a nanomaterial. The nanomaterial includes, disposed on a surface of the nanomaterial, a first coupling agent including silane and a functional group including an amino acid. The nanomaterial includes, disposed on the surface of the nanomaterial, a second coupling agent including silane and a polymer with a molecular weight between 1,000 and 20,000.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a text summarization neural network.