What do you think of when you’re hungry? Bots want to know. Image credit: Pexels.
“I’m hungry. Shall we do Japanese or Italian today?” You message your teammate.
Within a few seconds, you receive a reply. “Would you like to place your order with these restaurants?”
Except that the reply isn’t from your friend. It’s from a bot.
At Tech in Asia Singapore 2017, we gained surprising insights into artificial intelligence (AI) bots and assistants.
From left: Tak Lo, managing director of AI accelerator Zeroth.ai, Jeremy Seow, senior product manager of Zendesk, and Virginia Yang, head of product of Mimetic.ai. Image credit: Tech in Asia.
Think of how customers will start connecting with your bot
“AI is the next electricity,” says Tak Lo, managing director of Zeroth.ai. Zeroth.ai is an accelerator program for early-stage AI startup.
If AI is electricity, then natural language processing (NLP) would be its juice.
It’s the fundamental building block of bots, which could range from customer service chat bots to Evie, the AI scheduling assistant by Mimetic.ai.
To get bots right, Jeremy Seow, senior product manager of customer service software Zendesk, says that on top of studying NLP, bot builders need to think of entry points – the moment that a customer gets hooked onto your product.
“In my experience, the more successful bot builders are those that really thought through the ways people connect to the bot,” observes Seow.
Facebook introduced an AI bot with Delivery.com where you can order food in a chat with a friend. Using this example, Seow points out that when we speak with friends, we don’t usually say, “I want to order food.” Instead, we say phrases like “I am hungry” or “I want to pick up pizza”.
Seow gives another example – ecommerce. An online shopping platform may want a bot to answer “shipping returns” and build NLP around that specific phrase.
The hard part isn’t coming up with the algorithm, it’s gathering data
Bots won’t take over the human race – yet
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