Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

At an artificial intelligence-based service, an indication of a similarity group of items of a data stream is obtained. A subset of the stream items is to be included in an ordered collection and presented via an interface which allows one or more types of interactions. Using a first data set which includes interaction records of items in the similarity group, one or more machine learning models are trained to predict a relevance metric associated with a particular type of interaction. A predicted value of the relevance metric is obtained from a trained version of a model and stored.

Disclosed herein includes a system, a method, and a device for performing a convolution on data of a current layer of a neural network, including a plurality of channels arranged in a first order and partitioned into a plurality of first partitions according to the first order. Each first partition includes a result of a convolution on a corresponding partition of channels in data of a previous layer of the neural network. The device shifts the plurality of channels arranged in the first order to a second order, partition the shifted plurality of channels into a plurality of second partitions, according to the second order. For each of the plurality of second partitions, the device performs a convolution on channels of the shifted plurality of channels that are in the corresponding second partition.

Systems and methods are described for unified processing of indexed and streaming data. A system enables users to query indexed data or specify processing pipelines to be applied to streaming data. In some instances, a user may specify a query intended to be run against indexed data, but may specify criteria that includes not-yet-indexed data (e.g., a future time frame). The system may convert the query into a data processing pipeline applied to not-yet-indexed data, thus increasing the efficiency of the system. Similarly, in some instances, a user may specify a data processing pipeline to be applied to a data stream, but specify criteria including data items outside the data stream. For example, a user may wish to apply the pipeline retroactively, to data items that have already exited the data stream. The system can convert the pipeline into a query against indexed data to satisfy the users processing requirements.

Systems and methods are described for unified processing of indexed and streaming data. A system enables users to query indexed data or specify processing pipelines to be applied to streaming data. In some instances, a user may specify a query intended to be run against indexed data, but may specify criteria that includes not-yet-indexed data (e.g., a future time frame). The system may convert the query into a data processing pipeline applied to not-yet-indexed data, thus increasing the efficiency of the system. Similarly, in some instances, a user may specify a data processing pipeline to be applied to a data stream, but specify criteria including data items outside the data stream. For example, a user may wish to apply the pipeline retroactively, to data items that have already exited the data stream. The system can convert the pipeline into a query against indexed data to satisfy the users processing requirements.

A mechanism is described for facilitating smart collection of data and smart management of autonomous machines. A method of embodiments, as described herein, includes detecting one or more sets of data from one or more sources over one or more networks, and combining a first computation directed to be performed locally at a local computing device with a second computation directed to be performed remotely at a remote computing device in communication with the local computing device over the one or more networks, where the first computation consumes low power, wherein the second computation consumes high power.

Traditionally, learning speech synthesis and speech recognition were investigated as two separate tasks. This separation hinders incremental development for concurrent synthesis and recognition, where partially-learned synthesis and partially-learned recognition must help each other throughout lifelong learning. This invention is a paradigm shift—we treat synthesis and recognition as two intertwined aspects of a lifelong learning robot. Furthermore, in contrast to existing recognition or synthesis systems, babies do not need their mothers to directly supervise their vocal tracts at every moment during the learning. We argue that self-generated non-symbolic states/actions at fine-grained time level help such a learner as necessary temporal contexts. Here, we approach a new and challenging problem—how to enable an autonomous learning system to develop an artificial motor for generating temporally-dense (e.g., frame-wise) actions on the fly without human handcrafting a set of symbolic states. Here the artificial motor corresponds to a combination of a multiplicity of robotic effectors, including, but not limited to, speaking, singing, dancing, riding a bike, swimming, and driving a car. The self-generated states/actions are Muscles-like, High-dimensional, Temporally-dense and Globally-smooth (MHTG), so that these states/actions are directly attended for concurrent synthesis and recognition for each time frame. Human teachers are relieved from supervising learner's motor ends. The Candid Covariance-free Incremental (CCI) Principal Component Analysis (PCA) is applied to develop such an artificial speaking motor where PCA features drive the motor. Since each life must develop normally, each Developmental Network-2 (DN-2) reaches the same network (maximum likelihood, ML) regardless of randomly initialized weights, where ML is not just for a function approximator but rather an emergent Turing Machine. The machine-synthesized sounds are evaluated by both the neural network and humans with recognition experiments. Our experimental results showed learning-to-synthesize and learning-to-recognize-through-synthesis for phonemes. This invention corresponds to a key step toward our goal to close a great gap toward fully autonomous machine learning directly from the physical world.

The present disclosure provides method and apparatus for providing a response to a user in a question-answering session. A message may be received in the session, the session being between the user and an electronic conversational agent. Context information is extracted from a context database based at least on the message. Fact information and emotion information are obtained from at least one of the message and the context information. The fact information is associated with at least one fact, and the emotion information is associated with emotions towards the at least one fact. A response is generated based at least on the fact information and the emotion information. The response is provided to the user.

Smart livestock management method and system based on Internet of things. The smart livestock management system may include a gate. The gate may include a frame forming a moving path of an animal, an external device disposed in the frame and configured to radiate electromagnetic waves toward the moving path and to receive identification information and bio information of the animal from an implant device inserted into the body of the animal passing through the moving path, and a camera configured to obtain image data of the animal passing through the moving path.

Smart livestock management method and system based on Internet of things. The smart livestock management system may include a gate. The gate may include a frame forming a moving path of an animal, an external device disposed in the frame and configured to radiate electromagnetic waves toward the moving path and to receive identification information and bio information of the animal from an implant device inserted into the body of the animal passing through the moving path, and a camera configured to obtain image data of the animal passing through the moving path.