The same deep learning technologies (ASR – Automatic Speech Recognition NLU – Natural Language Understanding) that power Amazon Alexa available to you for use in your own conversational applications
Bot – A bot contains all of the components of a conversation.
Intent – An intent represents a goal that the bot’s user wants to achieve (buying a plane ticket, scheduling an appointment, or getting a weather forecast, and so forth).
Utterance – An utterance is a spoken or typed phrase that invokes an intent. “I want to book a hotel” or “I want to order flowers” are two simple utterances.
Slots – Each slot is a piece of data that the user must supply in order to fulfill the intent. Slots are typed; a travel bot could have slots for cities, states or airports.
Prompt – A prompt is a question that asks the user to supply some data (for a slot) that is needed to fulfill an intent.
Fulfillment – Fulfillment is the business logic that carries our the user’s intent. Lex supports the use of Lambda functions for fulfillment.
@bentossell apart from getting a foot in the door, what is the innovation here? How would you say this is better than ms bot framework or watson conversation, just to name a couple?
Timing couldn't be better! Just started a new project and wasn't happy with the other options out there. Looking forward to seeing if Lex fits the bill for us. 🙌🏽
Sorta shocked this got so few upvotes! This is pretty big news and a really useful way to leverage Amazon's deep learning tech (the same that they use in Alexa).
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