How To Build First Bot Application using Microsoft Bot Framework
Source Code Link: https://github.com/akhonzadairshad/iBots
What are bots?
Bots are software programs that perform automated, repetitive, pre-defined tasks. These tasks can include almost any interaction with software that has an API.
These tasks can range from making dinner reservations, to get an update on a support request, to check competitors’ prices on their websites.
You’ll notice that the definition of bots does not necessarily include the concepts of artificial intelligence (AI) or machine learning (ML).
What are bots used for?
The range of bot capabilities is huge since bots can interact with so many different kinds of software.
In early 2016, many early bots are/were informational in nature. You interact with the bot, and it grabs data from its own database and surfaces it to the user. The CNN bot is a perfect example – it just pushes notifications of new content you might be interested to you:
CNN bot user experience
Techcrunch bot on Telegram does the same thing:
TechCrunch bot UX on the telegram
These kinds of bots are good proof-of-concept, if not very compelling from a user experience perspective.
Where do bots live?
Bots can live and work in lots of places, including the internet at large (search engine spiders), message apps (Facebook Messenger, Skype, etc), or on internal networks (bots monitoring system status).
Right now, most of the industry focus is on bots in messaging apps. Time spent in messaging apps has recently surpassed time spent in social networks:
messaging apps have surpassed social networks in minutes of use per day
And the audiences are huge. Over 2.5 billion people have at least 1 messaging app on their phone. The largest messaging apps from an MAU perspective are:
messaging application monthly active users
Are bots a new thing?
The idea behinds bots go back 65+ years. In his 1950 paper Computing Machinery and Intelligence, Alan Turing laid out the idea behind what is now known as the Turing Test. A human and a computer would be interrogated entirely by text messages, and the interrogator wouldn’t know which was which. Turing argued that if the human interrogator couldn’t tell the human and the computer apart, we should call the computer intelligent since we judge other people’s intelligence in exactly this way.
This kind of format and interaction model is really the canonical format for the term “chatbot”. The entire reason that the bot exists is to be chatting with, and there is no other goal of the interaction, besides seeing what the bot will say.
This chatbot model went on to see some successes in 1966 with ELIZA, and in 1972 with PARRY, where both chatbots came close to passing the Turing Test. More recently, Cleverbot and Eugene Goostman have come close to passing.
Why is there so much attention on bots now?
Three things – the capabilities, the addressable market, and a “newish” communication channel.
Bot developers need to pay strict attention to how their bot is perceived by the user in this (currently) uncluttered and personal space of messaging. If the bot is sending too many updates, demands too much interaction, or generally starts to feel spammy, people are going to rebel.
This is not an issue if the signal-to-noise ratio of interacting with a bot is very high. But given this is a new human-computer-interaction model, and it takes place in a space that’s perceived as relatively personal (messaging), the development of good bot UX is critical. If a bot doesn’t deliver value to a user in a way that’s superior to another channel, people will just opt out:
unsubscribing from cnn bot
What’s the business model for bots?
There are lots of possible business models, but we haven’t reached product-market fit in the U.S. yet. We don’t yet have any stand-alone bots that consumers pay for and describe a sustainable business by themselves.
Next, the user’s choice of mode of interaction will dictate what platforms they have access to, and sometimes what the primary interface will be. For example, if they want a voice-only interaction, the choices are either Apple voice or Amazon Echo, and the first bot they interact with to navigate the space will be either Siri or Alexa, respectively.
On the other hand, if a user picks a standalone messaging app like Telegram, the landscape opens up considerably. There isn’t a “gatekeeper” assistant, and the visitor has a different problem, which is bot discovery.
Other companies like That bottle are taking a search-engine-like automated approach, building lists of bots, classifying them and ranking them according to a set of signals. The result is a list of bots ranked by popularity and user feedback.
http://botnerds.com/what-are-bots/