Converstational AI Frameworks

5 Natural Language Platforms

Natural Language Platforms

Using an established Natural Language Platforms make it easier for developers to design and deploy conversational systems to users as well as helps developers reach more users and also the capability to interface to Internet of Things (IoT) devices.

Most natural language processing platforms today handle the two key aspects related to natural language processing and understanding. They more or less all follow a similar methodology whereby they interpret a users utterance, then map it against intents that are created in order to respond to the user’s utterance.

These Conversational Language Platform benefit from having a huge amount of computing resources  powering the back-end which is therefore capable of supporting a larger language model, as well as benefit from having a diverse language set from  a wide range of users from around the world. As a result these web service frameworks tend to offer improved natural language understanding capabilities when compared with a stand-alone system.

Each of these natural language platforms offer similar services, however how they are constructed, function and interact with other systems vary from platform to platform.

Amazon Lex

Amazon Lex is a fully managed artificial intelligence (AI) service with advanced natural language models to design, build, test, and deploy conversational interfaces in applications.The Alexa Skills kit utilizes Lex and allows developers to “teach” Alexa new skills. Users access these new abilities by asking Alexa questions or making requests.These short interactions, are meant to expedite human-computer interaction. [1]

IBM Watson Assistant

Watson Assistant is a chatbot that provides exceptional customer service. We call it a virtual assistant because it’s much more than just an FAQ wrapped in a personality. Watson Assistant gives fast, consistent, and accurate answers across any application, device, or channel (including voice). Using artificial intelligence (AI), Watson Assistant is able to learn from customer conversations, improving its ability to resolve issues the first time and working to keep your customers from getting frustrated. [2]

Google Dialogflow

Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into mobile apps, web application, device, bot and interactive voice response systems. Dialogflow can provide new and engaging ways for users to interact with existing systems and  can analyze multiple types of input from users  including text or audio inputs (phone or voice recording). It can also respond either through text or with synthetic speech. [3]

Meta Wit

Wit is a natural Language Platform developed by Meta (Formerly Facebook). We are building the AI platform that helps 200,000+ developers create apps that understand human language. That’s an ambitious goal and our approach is different: We provide developers everywhere with a simple way to build apps that understand text and voice commands, and learn from every interaction. We leverage the community: what Wit.ai learns is shared among developers.[4]

Microsoft LUIS

Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot. [5]

  1. Source: https://aws.amazon.com/lex/
  2. Source: https://www.ibm.com/products/watson-assistant
  3. Source: https://cloud.google.com/dialogflow
  4. Source: https://wit.ai/
  5. Source: https://www.luis.ai/

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A Pragmatic Guide to Conversational AI Copyright © 2022 by Ross Bigelow is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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