Insidiously and persistently, Facebook is chipping away at other messaging platforms and moving their users to Facebook Messenger. If they keep it up, by the end of 2017 there will be as many people on Messenger (currently 900 million) as Facebook (1.674 billion). But, counterintuitive as that strategy seems (why bifurcate resources on two fronts) that is all part of Mark Zuckerberg’s avec nous le deluge.
Despite all efforts during almost half a century, most chatbots are still easily uncovered, but over the next decades they will definitely get smarter and finally we will distinguish human beings by them giving us silly answers as opposed to the much smarter chatbots. All of this will really start accelerating as soon as one single chatbot is smarter than one single human being. They will then be able to learn from each other, instead of learning from human beings, their knowledge will explode and they will be able to design even better learning mechanisms. In the long run, we will learn language from chatbots instead of the other way around.

According to Richard Wallace, chatbots development faced three phases over the past 60 years. In the beginning, chatbot only simulated human-human conversations, using canned responses based on keywords, and it had almost no intelligence. Second phase of development was strictly associated with the expansion of Internet, thanks to which a chatbot was widely accessed and chatted with thousands of users. Then, the first commercial chatbot developers appeared. The third wave of chatbots development is combined with advanced technologies such as natural language processing, speech synthesis and real-time rendering videos. It comprises of chatbot appearing within web pages, instant messaging, and virtual worlds.
^ "From Russia With Love" (PDF). Retrieved 2007-12-09. Psychologist and Scientific American: Mind contributing editor Robert Epstein reports how he was initially fooled by a chatterbot posing as an attractive girl in a personal ad he answered on a dating website. In the ad, the girl portrayed herself as being in Southern California and then soon revealed, in poor English, that she was actually in Russia. He became suspicious after a couple of months of email exchanges, sent her an email test of gibberish, and she still replied in general terms. The dating website is not named. Scientific American: Mind, October–November 2007, page 16–17, "From Russia With Love: How I got fooled (and somewhat humiliated) by a computer". Also available online.
Chatbots talk in almost every major language. Their language (Natural Language Processing, NLP) skills vary from extremely poor to very clever intelligent, helpful and funny. The same counts for their graphic design, sometimes it feels like a cartoonish character drawn by a child, and on the other hand there are photo-realistic 3D animated characters available, which are hard to distinguish from humans. And they are all referred to as ‘chatbots’. If you have a look at our chatbot gallery, you will immediately notice the difference.

Chatbots are used in a diverse fashion, across all verticals and on many different types of channel, e.g. websites, social messaging, etc. In business their application accelerated rapidly in 2019, leading Van Baker, research vice president at Gartner, to predict that: “By 2020, over 50% of medium to large enterprises will have deployed product chatbots."[17]
Despite all efforts during almost half a century, most chatbots are still easily uncovered, but over the next decades they will definitely get smarter and finally we will distinguish human beings by them giving us silly answers as opposed to the much smarter chatbots. All of this will really start accelerating as soon as one single chatbot is smarter than one single human being. They will then be able to learn from each other, instead of learning from human beings, their knowledge will explode and they will be able to design even better learning mechanisms. In the long run, we will learn language from chatbots instead of the other way around.
Efforts by servers hosting websites to counteract bots vary. Servers may choose to outline rules on the behaviour of internet bots by implementing a robots.txt file: this file is simply text stating the rules governing a bot's behaviour on that server. Any bot that does not follow these rules when interacting with (or 'spidering') any server should, in theory, be denied access to, or removed from, the affected website. If the only rule implementation by a server is a posted text file with no associated program/software/app, then adhering to those rules is entirely voluntary – in reality there is no way to enforce those rules, or even to ensure that a bot's creator or implementer acknowledges, or even reads, the robots.txt file contents. Some bots are "good" – e.g. search engine spiders – while others can be used to launch malicious and harsh attacks, most notably, in political campaigns.[2]
The term Chatbot is closely related to chat bot and chatterbot. Chatterbot is more popular in relation to chatbot who talk a lot, and is not necessary very intelligent in processing the user answers. Chat bot is used by technical people who consider the word ‘bot’ as a normal term for ‘robotised actions’, and for them ‘chat bot’ is a special kind of bot. The term Chatbot is actually the most popular amongst these three terms and has the broadest meaning.
MEOKAY is one of the top tools to create a conversational Messenger bot. It makes it easy for both skilled developers and non-developers to take part in creating a series of easy to follow steps. Within minutes, you can create conversational scenarios and build advanced dialogues for smooth conversations. Once you are done, link and launch your brand new chatbot.
Social networking bots are sets of algorithms that take on the duties of repetitive sets of instructions in order to establish a service or connection among social networking users. Various designs of networking bots vary from chat bots, algorithms designed to converse with a human user, to social bots, algorithms designed to mimic human behaviors to converse with behavioral patterns similar to that of a human user. The history of social botting can be traced back to Alan Turing in the 1950s and his vision of designing sets of instructional code that passes the Turing test. From 1964 to 1966, ELIZA, a natural language processing computer program created by Joseph Weizenbaum, is an early indicator of artificial intelligence algorithms that inspired computer programmers to design tasked programs that can match behavior patterns to their sets of instruction. As a result, natural language processing has become an influencing factor to the development of artificial intelligence and social bots as innovative technological advancements are made alongside the progression of the mass spreading of information and thought on social media websites.
The chatbot uses keywords that users type in the chat line and guesses what they may be looking for. For example, if you own a restaurant that has vegan options on the menu, you might program the word “vegan” into the bot. Then when users type in that word, the return message will include vegan options from the menu or point out the menu section that features these dishes.
Want to initiate the conversation with customers from your Facebook page rather than wait for them to come to you? Facebook lets you do that. You can load email addresses and phone numbers from your subscriber list into custom Facebook audiences. To discourage spam, Facebook charges a fee to use this service. You can then send a message directly from your page to the audience you created.
Have you checked out Facebook Messenger’s official page lately? Well, now you can start building your own bot directly through the platform’s landing page. This method though, may be a little bit more complicated than some of the previous ways we’ve discussed, but there are a lot of resources that Facebook Messenger provides in order to help you accomplish your brand new creation. Through full-fledged guides, case studies, a forum for Facebook developers, and more, you are sure to be a chatbot creating professional in no time.
What began as a televised ad campaign eventually became a fully interactive chatbot developed for PG Tips’ parent company, Unilever (which also happens to own an alarming number of the most commonly known household brands) by London-based agency Ubisend, which specializes in developing bespoke chatbot applications for brands. The aim of the bot was to not only raise brand awareness for PG Tips tea, but also to raise funds for Red Nose Day through the 1 Million Laughs campaign.
However, web based bots are not as easy to set up as a stand-alone chatbot application. Setting up a web-based chatbot requires at least minimal experience with HTML, JavaScript and Artificial Intelligence Markup Language (AIML). Additionally, any sort of “fancy” features, such as Text To Speech, or an animated avatar, would have to be created and integrated into your chatbot’s page, and certain features, such as voice recognition, are either unavailable, or are severely limited.
Interface designers have come to appreciate that humans' readiness to interpret computer output as genuinely conversational—even when it is actually based on rather simple pattern-matching—can be exploited for useful purposes. Most people prefer to engage with programs that are human-like, and this gives chatbot-style techniques a potentially useful role in interactive systems that need to elicit information from users, as long as that information is relatively straightforward and falls into predictable categories. Thus, for example, online help systems can usefully employ chatbot techniques to identify the area of help that users require, potentially providing a "friendlier" interface than a more formal search or menu system. This sort of usage holds the prospect of moving chatbot technology from Weizenbaum's "shelf ... reserved for curios" to that marked "genuinely useful computational methods".

Smooch acts as more of a chatbot connector that bridges your business apps, (ex: Slack and ZenDesk) with your everyday messenger apps (ex: Facebook Messenger, WeChat, etc.) It links these two together by sending all of your Messenger chat notifications straight to your business apps, which streamlines your conversations into just one application. In the end, this can result in smoother automated workflows and communications across teams. These same connectors also allow you to create chatbots which will respond to your customer chats…. boom!
In Azure portal, paste the Facebook App ID, Facebook App Secret and Page Access Token values copied from the Facebook Workplace previously. Instead of a traditional pageID, use the numbers following the integrations name on its About page. Similar to connecting a bot to Facebook Messenger, the webhooks can be connected with the credentials shown in Azure.

The “web-based” solution, which runs on a remote server, is generally able to be reached by the general public through a web page. It constitutes a web page with a chatbot embedded in it, and a text form is the sole interface between the user (you) and the chatbot. Any “upgrades” or improvements to the interface are solely the option and responsibility of the botmaster.
In this era of information, businesses are able to take advantage of social media platforms to aid communication between their brand and their customers. Such seamless connectivity allows for a more transparent business exchange between the brand and its consumers. Just a decade ago, direct consumer brand interaction was either relatively impossible, or lengthy and cumbersome at the best. Social media has since then bridged this gap.
×