Abstract: In one embodiment, multiplier circuitry multiplies operands of a first format. One or more storage register circuits store digital bits corresponding to an operand and another operand of the first format. A decomposing circuit decomposes the operand into a first plurality of operands, and the other operand into a second plurality of operands. Each multiplier circuit multiplies a respective first operand of the first plurality of operands with a respective second operand of the second plurality of operands to generate a corresponding partial result of a plurality of partial results. An accumulator circuit accumulates the plurality of partial results using a second format to generate a complete result of the second format that is stored in the accumulator circuit. A conversion circuit truncates the complete result of the second format and converts the truncated result into an output result of an output format.

Abstract: A processor having a functional slice architecture is divided into a plurality of functional units (“tiles”) organized into a plurality of slices. Each slice is configured to perform specific functions within the processor, which may include memory slices (MEM) for storing operand data, and arithmetic logic slices for performing operations on received operand data. The tiles of the processor are configured to stream operand data across a first dimension, and receive instructions across a second dimension orthogonal to the first dimension. The timing of data and instruction flows are configured such that corresponding data and instructions are received at each tile with a predetermined temporal relationship, allowing operand data to be transmitted between the slices of the processor without any accompanying metadata. Instead, each slice is able to determine what operations to perform on received data based upon the timing at which the data is received.

Abstract: A processor having a functional slice architecture is divided into a plurality of functional units (“tiles”) organized into a plurality of slices. Each slice is configured to perform specific functions within the processor, which may include memory slices (MEM) for storing operand data, and arithmetic logic slices for performing operations on received operand data. The tiles of the processor are configured to stream operand data across a first dimension, and receive instructions across a second dimension orthogonal to the first dimension. The timing of data and instruction flows are configured such that corresponding data and instructions are received at each tile with a predetermined temporal relationship, allowing operand data to be transmitted between the slices of the processor without any accompanying metadata. Instead, each slice is able to determine what operations to perform on received data based upon the timing at which the data is received.

Abstract: A system receives a predictive model and receives one or more runtime constraints. The system generates a directed acyclic graph (DAG) of the predictive model indicating dependencies. The system compiles the predictive model into first instructions for a first processor based on the one or more runtime constraints and the DAG. The system packages first instructions, the one or more runtime constraints, and the DAG of the predictive model in a first binary. The system recompiles the predictive model into second instructions for a second processor based on the runtime constraints and the DAG stored in the first processor. The system packages the second instructions, the DAG, and the runtime constraints in a second binary.

Abstract: A system receives a predictive model and receives one or more runtime constraints. The system generates a directed acyclic graph (DAG) of the predictive model indicating dependencies. The system compiles the predictive model into first instructions for a first processor based on the one or more runtime constraints and the DAG. The system packages first instructions, the one or more runtime constraints, and the DAG of the predictive model in a first binary. The system recompiles the predictive model into second instructions for a second processor based on the runtime constraints and the DAG stored in the first processor. The system packages the second instructions, the DAG, and the runtime constraints in a second binary.

Abstract: A method comprises receiving a kernel used to convolve with an input tensor. For a first dimension of the kernel, a square block of values for each single dimensional vector of the kernel that includes all rotations of that single dimensional vector is generated. For each additional dimension of the kernel, group blocks of an immediately preceding dimension into sets of blocks, each set of blocks including blocks of the immediately preceding dimension that are aligned along a vector that is parallel to the axis of the dimension; and generate, for the additional dimension, one or more blocks of values, each block including all rotations of blocks within each of the sets of blocks of the immediately preceding dimension. The block of values corresponding to the last dimension in the additional dimensions of the kernel is output as the expanded kernel.

Abstract: A system receives a predictive model and receives one or more runtime constraints. The system generates a directed acyclic graph (DAG) of the predictive model indicating dependencies. The system compiles the predictive model into first instructions for a first processor based on the one or more runtime constraints and the DAG. The system packages first instructions, the one or more runtime constraints, and the DAG of the predictive model in a first binary. The system recompiles the predictive model into second instructions for a second processor based on the runtime constraints and the DAG stored in the first processor. The system packages the second instructions, the DAG, and the runtime constraints in a second binary.

Abstract: Methods are provided for the adjuvant treatment of operable HER2-positive primary breast cancer in human patients by administration of pertuzumab in addition to chemotherapy and trastuzumab. The methods reduce the risk of recurrence of invasive breast cancer or death for a patient diagnosed with HER2-positive early breast cancer (eBC) compared to administration of trastuzumab and chemotherapy, without pertuzumab.

Abstract: A memory structure having 2m read ports allowing for concurrent access to n data entries can be constructed using three memory structures each having 2m?1 read ports. The three memory structures include two structures providing access to half of the n data entries, and a difference structure providing access to difference data between the halves of the n data entries. Each pair of the 2m ports is connected to a respective port of each of the 2m?1-port data structures, such that each port of the part can access data entries of a first half of the n data entries either by accessing the structure storing that half directly, or by accessing both the difference structure and the structure containing the second half to reconstruct the data entries of the first half, thus allowing for a pair of ports to concurrently access any of the stored data entries in parallel.

Abstract: Embodiments of the disclosures made herein are directed to devices, apparatuses, systems and methods for facilitating cleaning of an imaging element of imaging devices used with robotic systems. Devices, apparatuses, systems and methods in accordance with the disclosures made herein provide a lens cleaning device configured to perform one or more cleaning events to remove contaminating matter from an imaging element (e.g., lens) of an imaging device (e.g., a laparoscope). In preferred embodiments, such devices, apparatuses, systems and methods are adapted specifically for facilitating in-vivo cleaning of an imaging element of imaging devices that are used with robotic surgical systems. Advantageously, embodiments of such robotic surgical system implementations enable a surgeon to readily resolve sub-optimal visualization of the surgical field during robotic (e.g., laparoscopic) surgical procedures.

Abstract: An improved emergency response system is provided. The system includes a patient or subscriber location database having a schedule of patient or subscriber activities. In one implementation, an emergency services server detects when the patient or subscriber is having a possible medical event as indicated by medical physiologic data transmitted from a wireless communication device proximate the patient. A third party such as a technologist and/or doctor diagnoses the patient and determines whether treatment is required. If treatment is required, a phone located remotely from the patient is used to call an emergency services first responder from a public safety access point in the patient's location. The remotely located phone has an automatic location identification database record that is updated based on the patient's current location as indicate by the patient location database.

Abstract: Methods are provided for the adjuvant treatment of operable HER2-positive primary breast cancer in human patients by administration of pertuzumab in addition to chemotherapy and trastuzumab. The methods reduce the risk of recurrence of invasive breast cancer or death for a patient diagnosed with HER2-positive early breast cancer (eBC) compared to administration of trastuzumab and chemotherapy, without pertuzumab.

Abstract: Introduced here is a technique to create small compressed image files while preserving data quality upon decompression. Upon receiving an uncompressed data, such as an image, a video, an audio, and/or a structured data, a machine learning model identifies an object in the uncompressed data such as a house, a dog, a text, a distinct audio signal, a unique data pattern, etc. The identified object is compressed using a compression treatment optimized for the identified object. The identified object, either before or after the compression, is removed from the uncompressed data. The uncompressed data with the identified object removed is compressed using a standard compression treatment.

Abstract: The invention relates to a plant for generating negative emissions of CO2. The plant 100 comprises a gasifier 110, a lime kiln 130, a separator 150, and a CO2 permanent storage 170. The gasifier is suitable for receiving as input a fuel 111 and for producing as output a high-temperature syngas flow 114. The lime kiln is suitable for receiving as input carbonate mineral 131 and the high-temperature syngas flow, the lime kiln being further suitable for producing an oxide 134 and for releasing as output a flow of syngas 133 enriched with CO2. The separator is suitable for receiving as input a gas flow containing CO2 and for treating it so as to separately provide at least CO2 151. The CO2 permanent storage is suitable for enclosing along time the CO2. The invention also relates to a method for generating negative emissions of CO2.

Abstract: An improved emergency response system is provided. The system includes a patient or subscriber location database having a schedule of patient or subscriber activities. In one implementation, an emergency services server detects when the patient or subscriber is having a possible medical event as indicated by medical physiologic data transmitted from a wireless communication device proximate the patient. A third party such as a technologist and/or doctor diagnoses the patient and determines whether treatment is required. If treatment is required, a phone located remotely from the patient is used to call an emergency services first responder from a public safety access point in the patient's location. The remotely located phone has an automatic location identification database record that is updated based on the patient's current location as indicate by the patient location database.

Abstract: A computational array is implemented in which all operands and results are loaded or output from a single side of the array. The computational array comprises a plurality of cells arranged in n rows and m columns, each configured to produce a processed value based upon a weight value and an activation value. The cells receive weight and activation values are received via colinear weight and activation transmission channels that each extend across a first side edge of the computational array to provide weight values and activations values to the cells of the array. In addition, result values produced at a top cell of each of the m columns of the array are routed through the array to be output from the same first side edge of the array at a same relative timing at which the result values were produced.

Abstract: Introduced here is a technique to create small compressed image files while preserving data quality upon decompression. Upon receiving an uncompressed data, such as an image, a video, an audio, and/or a structured data, a machine learning model identifies an object in the uncompressed data such as a house, a dog, a text, a distinct audio signal, a unique data pattern, etc. The identified object is compressed using a compression treatment optimized for the identified object. The identified object, either before or after the compression, is removed from the uncompressed data. The uncompressed data with the identified object removed is compressed using a standard compression treatment.

Abstract: A predictive model utilizes a set of coefficients for processing received input data. To reduce memory usage storing the coefficients, a compression circuit compresses the set of coefficients prior to storage by generating a cumulative count distribution of the coefficient values, and identifying a distribution function approximating the cumulative count distribution. Function parameters for the determined function are stored in a memory and used by a decompression circuit to apply the function the compressed coefficients to determine the decompressed component values. Storing the function parameters may consume less memory in comparison to storing a look-up table for decompression, and may reduce an amount of memory look-ups required during decompression.

Abstract: A system may comprise a processor integrated circuit (IC) and a vector mapping sub-system that is separate from the processor IC and includes one or more ICs. The system may receive input data for processing by a predictive model and generate at least one memory address from the input data. At least one memory address may be provided to the vector mapping sub-system. The vector mapping sub-system generates a resulting vector of numbers based on the at least one memory address. The resulting vector can be a fixed length vector representation of the input data. The resulting vector is provided from the vector mapping sub-system to the processor IC. The processor IC executes one or more instructions for the predictive model using the resulting vector to generate a prediction. A corresponding method also is disclosed.

Abstract: A method of providing services to computing devices includes establishing a connection over the Internet with a computing device; receiving data from the computing device during the connection; extracting a signal from the data received from the computing device; estimating a relative age of the computing device based on the extracted signal; selecting a service from a plurality of services based on the estimated relative age of the computing device; and providing the selected service to the computing device.