International Business Machines Corporation

Airbnb, Inc.

Ana Paula Appel

Renato Luiz De Freitas Cunha

Claudio Santos Pinhanez

Paulo Rodrigo Cavalin

Bruno Silva

Vagner Figueredo De Santana

Maira Athanazio De Cerqueira Gatti

Rogerio Abreu De Paula

Andre Gama Leal

Eduardo Rocha Rodrigues

Heloisa Caroline De Souza Pereira Candello

Alecio Pedro Delazari Binotto

Marisa Affonso Vasconcelos

Victor Fernandes Cavalcante

Igor Cerqueira Oliveira

Renan Francisco Santos Souza

Luis Gregorio Moyano

Vagner F De Santana

Percival Silva De Lucena

Victor Boa Juliani

Henrique Von Atzingen Do Amaral

Marcela Megumi Terakado

Ricardo Vieira Borges Franco

Utz Bacher

Jaione Tirapu Azpiroz

Julio Nogima

Lucas Correia Villa Real

Sergio Varga

Ricardo Luis Ohta

Paul Llamas Virgen

Maira Gatti De Bayser

Carmen Nilda Mena Paz

Marcia Ito

Stefany Mazon

Silvia C S Bianchi

Ariane Hernandes Amadeu

Mauro Carlos Pichiliani

Melina De Vasconcelos Alberio Guerra

Maysa Malfiza Garcia De Macedo

Bernardo Nunes Goncalves

Marcos V Landivar Paraiso

Edson G Pereira

Vagner F Santana

Heloisa C De S P Candello

Renato L De F Cunha

Victor Henrique Alves Ribeiro

Gabriel Louzada Malfatti

Guilherme Custodio De Souza

Romelia H Flores

Carlos Eduardo Buzeto

Manuel Soares Pereira Da Rocha Junior

Allana Paola Paoli Neves

Paula Fernanda Pereira

Alexandre Alves

A topic for building a new intent on which to train a chatbot can be received. A database of chatbot training data can be searched for a candidate intent having meta-knowledge similar to the received topic. Utterances associated with the candidate intent can be extracted. The received topic and the extracted utterances can be input to a trained machine learning model. The trained machine learning model generates example utterances for the new intent. The new intent with the generated example utterances can be used as training data for training the chatbot.

Training example generation to create new intents for chatbots

Managing licenses is provided. Evidence required for compliance with conditions set forth in a license is received from a client device of a designated user via a network. An analysis of the evidence is performed using machine learning based on a set of criteria to determine whether the evidence is valid. It is determined, using machine learning, whether the evidence is valid based on the analysis of the evidence. The evidence required for the compliance with the conditions set forth in the license is sent to a regulatory agency via the network to maintain the license for an entity in response to the determining that the evidence is valid based on the analysis of the evidence.

License compliance failure risk management

Techniques are described with respect to a system, method, and computer program product for visualizing gaming virtual objects. An associated method includes analyzing a physical object within a physical space; rendering a virtual object associated with the physical object based on the analysis; optimizing the virtual object within a virtual environment associated with the physical space; and integrating the optimized virtual object into the virtual environment.

Augmenting objects for immersive gaming environments

An approach to identifying architectures of machine learning models meeting a user defined constraint. The approach can receive input associated with evaluating machine learning models from a user. The approach can determine acceptable architectural templates to evaluate the machine learning models based on the input and determine a list of architectures and metrics based on a calculation of maximum neural network sizes of the acceptable architectural templates not exceeding the constraint. The approach can send the list of architectures and metrics to the user for selection.

Automated machine learning model selection

A system for initiating web containers and isolating network traffic to web containers is described. The system initiates and uses web containers for associated web-based resources, such as domain addresses owned by a single entity. When a web container for a domain address has not been initiated, the system determines an owner of the domain address and any domain addresses associated with the owner and initiates a web container for the domain address and the associated domains. When a user navigates to the domain addresses associated with the determined owner, the system isolates the network activity to the initiated web container.

Internet activity compartmentalization

The present disclosure provides for crop yield estimation by identifying, via image processing, a field in which a crop is grown; identifying a plurality of regions within the field; identifying, by processing growth metrics via a model, a plurality of data collection points in the plurality of regions, wherein a given data collection point of the plurality of data collection points within a given region of the plurality of regions is identified by multivariate analysis as representative of growing conditions in the given region; receiving in-field data linked to the data collection points of the plurality; and predicting a yield for the crop in the field based on the in-field data.

Crop yield estimation

A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question can be provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.

Predicting user question in question and answer system

In response to identifying one or more applications on a computing device, terms and conditions associated with the one or more applications are identified. A knowledge base based on the identified terms and conditions is generated. The knowledge base includes a determination of sensitive information of a user required by each of the identified one or more applications. Secondary associations of the identified one or more applications are identified from a plurality of external data sources with information related to the identified one or more applications. In response to identifying the secondary associations, it is determined whether sensitive information about the user is found in one or more of the identified secondary associations. In response to determining that sensitive information about the user is found, an advisory is transmitted to the user.

Managing sensitive user information

Chatbot logs can be received. The chatbot logs can be clustered or classified into clusters of potential intents. Trending topics can be detected by analyzing at least social media content. Semantic similarities between the potential intents and the trending topics can be computed. Based on the computed semantic similarities, at least one of the potential intents to at least one of the trending topics can be correlated. Training of the chatbot using the chatbot logs associated with the correlated potential intent can be triggered.

Conversational systems content related to external events

An example operation may include one or more of storing existing chaincode relationships of a group of blockchain peers within a blockchain network, identifying a new chaincode to implement for one or more blockchain peers among the group of blockchain peers of the blockchain network based on the existing chaincode relationships among the group of blockchain peers, and transmitting a message to the one or more blockchain peers with a suggestion to implement the new chaincode.

Chaincode recommendation based on existing chaincode

A method of automatically creating new intents and assigning examples to those new intents in a dialog system includes generating at least one predicted intent from an intent concept graph by combining two or more nodes of the intent concept graph. A graph embedding is generated of the at least one predicted intent. A sentence embedding is generated from examples from a call log. The graph embedding of the at least one predicted intent is then matched with the examples from the sentence embedding and the at least one predicted intent, with the examples, is connected into a dialog system.

Concept prediction to create new intents and assign examples automatically in dialog systems

Techniques for maintaining a knowledge database system based on user interactions with the database system are described herein. An aspect includes generating a user interface based on a knowledge database comprising a plurality of entities, wherein the user interface comprises a plurality of user interface elements, each user interface element of the plurality of user interface elements corresponding to one or more of the plurality of entities of the knowledge database. Another aspect includes receiving a user interaction corresponding to the user interface. Another aspect includes updating the knowledge database based on the received user interaction, wherein updating the knowledge database based on the received user interaction includes determining a user interface element associated with the received user interaction, mapping the determined user interface element to a first entity of the plurality of entities of the knowledge database, and performing a weight update corresponding to the first entity.

Maintaining a knowledge database based on user interactions with a user interface

A microservice and the recipe for that microservice are automatically created by modifying a local environment in an integrated development environment executing on a computing system to construct a desired microservice, recording commands entered while modifying the local environment, computing a list of changes from the recorded commands that change the local environment and compiling the list of changes into a recipe comprising commands and dependencies sufficient to assemble an operating system and software files that are sufficient to instantiate the desired microservice.

Automated microservice creation based on user interaction

A method, a computer program product, and a computer system manage tree risk. The method includes receiving images corresponding to a geographic area. The method includes determining whether a first tree captured in at least one of the images has a condition exhibiting a tree risk that poses a hazard above an acceptable threshold. As a result of the first tree having the condition above the acceptable threshold, the method includes generating a notification identifying the first tree and a location of the first tree. The method includes transmitting the notification to a team equipped to remediate the condition of the first tree.

Managing tree risk

A product quality analysis and control system is provided. The product quality analysis and control system includes a processing system that is configured to receive data of objective qualities of a product from multiple data gathering modules. Each of the multiple data gathering modules is respectively positioned at corresponding nodes of a supply chain and is configured to receive from sensors data of objective qualities of a product when the product is at each of the corresponding nodes. The processing system includes a model repository and a data evaluation module. The data evaluation module is configured to select, from the model repository, a model associated with a type of the product and to use the model to analyze the data to identify changes in the objective qualities along the supply chain.

Product quality analysis and control

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São Paulo, Brazil

Ana Paula Appel