An object of the present invention is to generate a single portfolio assuming a plurality of targets as a specific objective of investment management, and also to make it possible to easily generate a plurality of portfolios having the same objective followed by comparing and contrasting of the plurality of portfolios. To this end, an investment management assistance server 10 that generates, based on input information, portfolio information for suggesting investment management for objective achievement set by a customer includes: objective display means 13 that displays predetermined objective information selectable by a customer through an input operation; interview display means 14 for displaying predetermined interview information to which the customer is allowed to respond through an input operation; and portfolio generation/display means 15 for generating predetermined portfolio information based on the objective information and interview information which are selected and responded to through an input operation, and causing the customer terminal 30 to display the predetermined portfolio information in a visually recognized manner. The portfolio generation/display means 15 is configured to generate portfolio information for suggesting a single investment management corresponding to one or more pieces of objective information selected by the customer.

An object of the present invention is to generate a single portfolio assuming a plurality of targets as a specific objective of investment management, and also to make it possible to easily generate a plurality of portfolios having the same objective followed by comparing and contrasting of the plurality of portfolios. To this end, an investment management assistance server 10 that generates, based on input information, portfolio information for suggesting investment management for objective achievement set by a customer includes: objective display means 13 that displays predetermined objective information selectable by a customer through an input operation; interview display means 14 for displaying predetermined interview information to which the customer is allowed to respond through an input operation; and portfolio generation/display means 15 for generating predetermined portfolio information based on the objective information and interview information which are selected and responded to through an input operation, and causing the customer terminal 30 to display the predetermined portfolio information in a visually recognized manner. The portfolio generation/display means 15 is configured to generate portfolio information for suggesting a single investment management corresponding to one or more pieces of objective information selected by the customer.

Aspects of the disclosure relate to using machine learning methods for chatbot selection. A computing platform may train a plurality of machine learning models, each corresponding to a chatbot. The computing platform may train an additional machine learning model to route queries to the plurality of machine learning models based on contents of the queries. The computing platform may receive a query, and may analyze the query using the additional machine learning model. The computing platform may route, based on the query analysis, the query to the plurality of machine learning models. The computing platform may generate, using the plurality of machine learning models, a response to the query. The computing platform may send the response to the query and one or more commands directing a client device to display the response to the query, which may cause the client device to display the response to the query.

Methods, systems and apparatuses to enable an optimum bin selection by implementing a neural network with a network scheduling and configuration tool (NST), the method includes: configuring an agent with a critic function from neural networks wherein the agent neural network represents each bin of the collection of bins in the network that performs an action, and a critic function evaluates a criteria of success for performing the action; processing, by a scheduling algorithm, the VLs by the NST; determining one or more reward functions using global quality measurements based on criteria comprising: a lack of available bins, a lack of available VLs, and successfully scheduling operations of a VL into a bin; and training the network based on a normalized state model of the scheduled network by using input data sets to arrive at an optimum bin selection.

A computer-implemented method and system for generating a recommendation that is personalized to achieve an enhanced sales outcome for a persona based on a multivariate artificial intelligence (AI) data model from an integrated dataset using explainable artificial intelligence (AI) models. The integrated dataset includes the people datasets, the organization datasets, and the customer datasets. one or more derived key drivers are derived from the multivariate AI data model. The derived key drivers and contextual sales activities are correlated with historical and real-time sales outcomes to train a first explainable AI model. The explainable sales outcomes are coupled with attributes, and activities of the persona to train a second explainable AI model. The second explainable AI model generates a recommendation that includes an automated reminder and an activity execution, to achieve the enhanced sales outcomes for the persona and the business.

An apparatus in a network of apparatuses includes a first processing unit that has: a first measurement unit configured to receive items and take physical measurements, a first memory storing parameters that are useful for categorizing the items based on the physical measurements taken from the items and characteristics calculated using the physical measurements, and a first processing module including an artificial intelligence program. The first processing module automatically selects a source from which to receive new parameters based on similarity between physical measurements taken by the first processing unit and physical measurements that were taken by the sources, automatically modifies at least some of the parameters that are stored in the first memory with the new parameters received from the source and with measurements taken by the first processing unit to generate modified parameters, and transmitting a subset of the modified parameters to one or more recipients.

An artificial intelligence device according to an embodiment of the present disclosure may receive voice data corresponding to viewing information and a search command from a display device, convert the received voice data into text data, obtain a first query indicating intention of the converted text data, convert the first query into a second query based on the viewing information, obtain a search result corresponding to the converted second, and transmit the obtained search result to the display device.

A method and an apparatus for organization and detection of homogeneous and heterogeneous swarms of devices and application of swarm intelligence using swarm intelligence framework are provided. The Swarm Intelligence Framework provides a generic platform for realizing solutions involving Swarm Intelligence Technology via flexible container-based Algorithm Plug-in Architecture which is essential to utilize Swarm Intelligence Framework for various scenarios and use cases, including dynamically loading and using the Swarm Detection Algorithm.

A system includes a development system and a digital assistance system. The development system includes a network interface configured to communicate with a plurality of communication channels, a processing system configured to interface with a project management subsystem, a scheduling subsystem, and the network interface, and an application programming interface configured to receive a command sequence for the project management subsystem and the scheduling subsystem. The digital assistance system includes a natural language processing engine configured to interface with a voice-enabled communication session through one of the communication channels. The digital assistance system also includes a command generator configured to generate the command sequence based on one or more requested tasks detected through the voice-enabled communication session and provide the command sequence to the application programming interface to execute the one or more requested tasks.

In one embodiment, a method comprises: tracking, by a first security agent executed within a user network device, a plurality of wireless data networks that are available for connection by the user network device for secure communications with a second network device in a secure peer-to-peer data network, and maintaining a history of each of the wireless data networks; determining for each of the wireless data networks, by the first security agent, a corresponding risk assessment that identifies a corresponding risk in encountering a cyber threat on the corresponding wireless data network; and supplying, to a second security agent executed within the user network device, a recommendation for connecting to a wireless data link identified as avoiding the cyber threat during the secure communications, wherein the user network device has a two-way trusted relationship with the second network device in the secure peer-to-peer data network.