The Future of Real-World Chatbots

Image Credit
  • text generation (great GPT-2 examples here)
  • summarization (see Pegasus)
  • text to code (tools made with GPT-3)
  • text to image (if it sounds like sci-fi just check DALL-E)
  • question answering on tables (here and here)
  • Understand user request, e.g. create a “query”
  • Retrieve information, e.g. execute the “query” and get a “response”
  • Take an action with that information, e.g. continue the conversation, request more information, post an order, etc. (here we use the “response” of the “query)

Natural Language Understanding? 😰

What we’ve got here is failure to communicate….and we could say that there are many communication pain points between a bot and a user.

  • User: How much is the millennium falcon?
  • Bot: It costs $1.234
  • User: ok, thanks
  • Bot: You’re welcome
  • User: And what about the centennial falcon?
  • Bot: It costs $ 1.454
  • User: Ok, and what colors do you have the millennium falcon? Do you accept Bitcoin?
  • User: Ok, and would you send a red millennium falcon to my address? And do you accept Bitcoins?
  • User: Ok, and would you send a millennium falcon to my address?
  • Bot: We don’t have your address on file, would like to set one up?
  • User: Oh, and do you accept bitcoins? And yes, please add Skywalker Ave. 4321
  • Bot: I’m afraid we don’t accept Bitcoin, but we do use Ethereum, would that work?
  • User: Oh, yes!
  • Bot: So we’ll be sending you a millennium falcon to Skywalker Ave. 4321, and the total is 0.62 ETH, is that ok?
  • User: Yes, but wait, can I have it in red?
  • Hi, I want a coffee, please. Daddy, can I have a muffin? (a child speaks in the background).
  • Hi, I want a coffee, please. Do you want a muffin? (here the person is asking someone else…) and can I get a muffin?

The future?

Given all these interesting challenges of building a bot — a number of different solutions and machine learning models can come into play.

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Zubair Talib

Zubair Talib

Loves Technology, Startups, and Tacos.