Abstract: In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.

Abstract: In some aspects, methods and systems may use consumption timestamps to ensure consistency between data used during inference and data used to train a machine learning model. Specifically, methods and systems may generate a consumption timestamp corresponding to the time at which the streaming data is received or inserted into a database. The consumption timestamp may be used as a synchronization point for any related data that may be requested (e.g., via an API). After streaming data is received, the consumption timestamp may be generated and assigned to any data that is requested in connection with the streaming data. The streaming data, related data, and consumption timestamp may be included in a data snapshot that is provided to a machine learning model for inference (e.g., real-time inference) or training.

Abstract: In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.

Abstract: In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.

Abstract: In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.

Abstract: The disclosed technology involves autonomously identifying goals and sub-goals from a user utterance and generating responses to the user based on the goals and sub-goals.

Abstract: In certain embodiments, pre-chat intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. Within ten seconds of the chat initiation request, the candidate questions may be simultaneously presented on the chat interface. Based on negative feedback obtained via the chat interface with respect to the candidate questions, additional candidate questions matching the second set of predicted intents may be presented on the chat interface. In some embodiments, the negative feedback may be provided to the prediction model to update configurations of the prediction model.

Abstract: In certain embodiments, pre-chat intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. Within ten seconds of the chat initiation request, the candidate questions may be simultaneously presented on the chat interface. Based on negative feedback obtained via the chat interface with respect to the candidate questions, additional candidate questions matching the second set of predicted intents may be presented on the chat interface. In some embodiments, the negative feedback may be provided to the prediction model to update configurations of the prediction model.

Abstract: In certain embodiments, pre-chat intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain predicted intents of the user. For each intent of the current intents, a candidate question may be selected from a question set based on the candidate question matching the intent. Within ten seconds of the chat initiation request, the candidate questions may be simultaneously presented on the chat interface. A user selection of a first question of the candidate questions may be obtained via the chat interface responsive to the presentation of the candidate questions. Based on the user selection and the first question matching a first intent of the predicted intents, the first intent may be provided as reference feedback for the prediction model.