It’s hard to swing a $400 juicer in Silicon Valley these days without hitting a chatbot. Advances in artificial intelligence have enabled these talkative assistants to become a reality, and they’re now cropping up in many different forms.
Facebook has greatly improved its chatbot game in Messenger, and everyone from Mastercard to Maroon 5 are climbing on board. In a way, voice-controlled Chatbots are computer programs which were engineered to converse in spoken or written form with humans. They are usually used in dialogue systems with a limited topic range. For example, they can answer basic customer questions or help you buy the correct train ticket. drive personal assistants like Siri on our phones and in our living rooms. It’s enough to make you believe the A bot is a piece of code, which does a predefined set of actions on behalf of someone. Bots are used to manage Twitter Followers, they answer email requests or order more supplies as soon a certain item runs low. are taking over. Except they’re not, at least not yet. The technologies that drive chatbots, and those related to machine and in particular, need to advance before “conversation” becomes a standard interface. Some of the needs are obvious, like improved recognition, while others are more subtle, like the ability for chatbots to signal what services they have to offer. Here are some areas where these talkative bits of need to improve before they really take off.
Advances in and Natural Language Processing (NLP) is the part of the technology world concerned with language. Natural language means that the language is produced by or for humans. This website for example is all written in natural language. NLP ranges from speech recognition, to language synthesis, it also involves tasks such as machine translation or information retrieval.
Remember the early days of the web, when pages were a sea of flashing neon and blue links? That’s where chatbots are today. If bots are to reach ubiquity, people need to be able to ask questions and place orders using natural language.
Know your customer
A huge part of any implementation is understanding context. Much as marketing and sales are searching for that mythical 360-degree view of the customer, chatbots need to know more about the individuals they interact with — who they are, how they got here, what they’re looking for and what they did in the past.
Machines chatting with machines
The web is an amazingly interconnected place. Type any product into Google and you’re instantly connected to merchants that have the exact product you’re looking for in stock. Chatbots need to evolve in a similar way, so they can intelligently hand users off to each other and seamlessly take over a communication.
Illuminating what’s on offer
If I interact with an app or a web page, I can instantly see which services are available through links and other elements on the screen. Chatbots don’t have this visual language. When you talk to a chatbot, you’re going in with your eyes closed. What can I ask it? What does it do? Interacting with a chatbot for the first time, people need to know.
Chatbots will provide infinitely better service when they can read facial features and inflections in tone to understand the emotion of the person they’re communicating with. This is partly about simple customer service — if the user is becoming frustrated or angry, it may be time to hand the conversation off to a human. […]