Abstract: Described herein are advanced artificial intelligence agents for modeling physical interactions. In one embodiment, an apparatus to provide an active artificial intelligence (AI) agent includes at least one database to store physical interaction data and compute cluster coupled to the at least one database. The compute cluster automatically obtains physical interaction data from a data collection module without manual interaction, stores the physical interaction data in the at least one database, and automatically trains diverse sets of machine learning program units to simulate physical interactions with each individual program unit having a different model based on the applied physical interaction data.

Abstract: Provided herein are methods and systems for reducing roughness of an EUV resist and improving etched features. The methods involve descumming an EUV resist, filling divots of the EUV resist, and protecting EUV resists with a cap. The resulting EUV resist has smoother features and increased selectivity to an underlying layer, which improves the quality of etched features. Following etching of the underlying layer, the cap may be removed.

Abstract: Fiber-reinforced organic polymer aerogels, articles of manufacture and uses thereof are described. The reinforced aerogels include a fiber-reinforced organic polymer matrix having an at least bimodal pore size distribution with a first mode of pores having an average pore size of less than or equal to 50 nanometers (nm) and a second mode of pores having an average pore size of greater than 50 nm and a thermal conductivity of less than or equal to 30 mW/m·K at a temperature of 20° C.

Abstract: Methods and systems for advanced and augmented training of deep neural networks (DNNs) using synthetic data and innovative generative networks. A method includes training a DNN using synthetic data, training a plurality of DNNs using context data, associating features of the DNNs trained using context data with features of the DNN trained with synthetic data, and generating an augmented DNN using the associated features.

Abstract: A resource optimization system is offered for use in managing large scale projects. The resource optimization system has a resource optimization tool configured to receive a plurality of inputs. The plurality of inputs represent at least one task associated with the large scale project and are inputted into a resource optimization tool for a data processing procedure. An optimization module is contained within the resource optimization tool and configured to perform the data processing procedure on each of the plurality of inputs as well as exogenous disturbances inputted into the optimization module. The optimization module returns an optimization result based on the data processing procedure to reflect the management and progress of the project under evaluation.

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: A new model is introduced into a particular domain that receives a routing of a dialog from a speech processing component. A method associated with the model includes running a set of test utterances through the speech processing component that enables a spoken language dialog with a user to establish a base line score associated with processing for the set of test utterances. The speech processing component determines an intent of the user and routes the spoken language dialog to a network-based domain based on the intent. The method includes establishing an automatic test run of the set of test utterances to obtain a current score and, when a threshold associated with a difference between the current score and the base line score is breached, switching, at the network-based domain, from the false accept detection model to a second model.

Abstract: The present application relates to use of hexokinase-2 and a kit for detecting rare tumor cells in body fluid sample. The present application, based on a principle of abnormal tumor cell energy metabolism, conducts a vitro detection by using a glycolysis marker hexokinase-2 (HK2) as a marker, and assists localization and selection of the rare tumor cells by an addressable microporous array chip or a glass sheet, so as to implement a detection on rare tumor cells having high glycolysis activity in a cancer patient's body fluid sample.

Abstract: An implant (500) comprises an elastic deformation portion (51) and a connection portion (52) connected with the proximal end (511) of the elastic deformation portion (51), wherein the elastic deformation portion (51) is covered by an elastic outer layer (55); the proximal end of the connection portion (52) is surrounded by a tightening ring (58); and the proximal end of the elastic outer layer (55) is covered by the tightening ring (58). Since the proximal end of the elastic outer layer (55) of the implant (500) is surrounded by a tightening ring (58), the elastic outer layer (55) is closely attached on the connecting portion (52) of the implant (500), such that the elastic outer layer (55) can be prevented from being rolled over from the surface of the implant (500) when the implant (500) is implanted, thereby improving safety of lung volume reduction surgery.

Abstract: Skin smoothing is applied to images using a bilateral filter and aided by a skin map. In one example a method includes receiving an image having pixels at an original resolution. The image is buffered. The image is downscaled from the original resolution to a lower resolution. A bilateral filter is applied to pixels of the downscaled image. The filtered pixels of the downscaled image are blended with pixels of the image having the original resolution, and the blended image is produced.

Abstract: An optical module includes a shell, a circuit board, a light source and a silicon optical chip. The light source is configured to emit light. The silicon optical chip includes a modulator, and the modulator is configured to receive the light emitted by the light source and modulate the light into an optical signal. The circuit board includes a first sampling circuit, a second sampling circuit and a processing circuit. The first sampling circuit is configured to generate a first sampling signal. The second sampling circuit is configured to generate a second sampling signal. The processing circuit is configured to receive the first sampling signal and the second sampling signal, and send a driving signal to the modulator according to a difference between an amplitude of the first sampling signal and an amplitude of the second sampling signal, so as to control an electric heating of the modulator.

Abstract: A new model is introduced into a particular domain that receives a routing of a dialog from a speech processing component. The speech processing component is engaged in the dialog with a user and the speech processing component routes the dialog to the particular network-based domain according to a determination by the speech processing component that the user has an intent to perform a task handled by the domain. The model detects, at the domain, whether the user has the proper intent associated with the domain by using the user utterance in its entirety to yield a detection result. When the user does not have the proper intent based on the detection result, the domain drops the user utterance.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a tuple of respective input sequences to generate an output. In one aspect, one of the systems includes a neural network comprising a plurality of encoder neural networks and a head neural network, each encoder neural network configured to: receive a respective input sequence from the tuple; process the respective input sequence using one or more encoder network layers to generate an encoded representation comprising a sequence of tokens; and process each of some or all of the tokens in the sequence of tokens using a projection layer to generate a lower-dimensional representation, and the head neural network configured to: receive lower-dimensional representations of a respective proper subset of the sequence of tokens generated by the encoder neural network; and process the lower-dimensional representations to generate the output.

Abstract: A method manufacturing a spacer for a pipe-in-pipe system includes mixing aerogel particles with a polymer to form a mixture in which the particles are dispersed in the polymer. The resulting mixture is moulded and the polymer is solidified to form the spacer or a component of the spacer, in which the dispersed, particles are suspended in a matrix of the solidified polymer.

Abstract: Described herein are advanced artificial intelligence agents for modeling physical interactions. An apparatus to provide an active artificial intelligence (AI) agent includes at least one database to store physical interaction data and compute cluster coupled to the at least one database. The compute cluster automatically obtains physical interaction data from a data collection module without manual interaction, stores the physical interaction data in the at least one database, and automatically trains diverse sets of machine learning program units to simulate physical interactions with each individual program unit having a different model based on the applied physical interaction data.

Abstract: Skin smoothing is applied to images using a bilateral filter and aided by a skin map. In one example a method includes receiving an image having pixels at an original resolution. The image is buffered. The image is downscaled from the original resolution to a lower resolution. A bilateral filter is applied to pixels of the downscaled image. The filtered pixels of the downscaled image are blended with pixels of the image having the original resolution, and the blended image is produced.

Abstract: A system for performing a machine learning task on a network input is described. The system includes one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to implement (i) multiple sorting networks in which each sorting network is configured to sort vector blocks in a sequence of vector blocks to generate a sorted sequence of vector blocks; and (ii) a sorting attention neural network configured to perform the machine learning task on the input sequence by executing multiple sorting attention mechanisms using the sorting networks.

Abstract: An embodiment of a computer-implemented method generates a filtered set of region proposals for a digital image processing network. The method comprises generating a keypoint count map for a digital image, wherein the keypoint count map indicates how many keypoints have been detected near different pixels in the digital image. The method also comprises generating a keypoint integral image, wherein the keypoint integral image comprises a summed area table that is based on the keypoint count map. The method also comprises generating object existence indicators for an initial region set for the digital image based on the keypoint integral image, and extracting a keypoint-filtered region set from the initial region set based on the object existence indicators. The method may also comprise using the keypoint-filtered region set as region proposal input for an object proposal subsystem. Other embodiments are described and claimed.