The progressive advance of technology has seen an increase in businesses moving from traditional to digital platforms to transact with consumers. Convenience through technology is being carried out by businesses by implementing Artificial Intelligence (AI) techniques on their digital platforms. One AI technique that is growing in its application and use is chatbots. Some examples of chatbot technology are virtual assistants like Amazon's Alexa and Google Assistant, and messaging apps, such as WeChat and Facebook messenger.

Unlike Tay, Xiaoice remembers little bits of conversation, like a breakup with a boyfriend, and will ask you how you're feeling about it. Now, millions of young teens are texting her every day to help cheer them up and unburden their feelings — and Xiaoice remembers just enough to help keep the conversation going. Young Chinese people are spending hours chatting with Xiaoice, even telling the bot "I love you".
Chatbots have come a long way since then. They are built on AI technologies, including deep learning, natural language processing and  machine learning algorithms, and require massive amounts of data. The more an end user interacts with the bot, the better voice recognition becomes at predicting what the appropriate response is when communicating with an end user.
As you roll out new features or bug fixes to your bot, it's best to use multiple deployment environments, such as staging and production. Using deployment slots from Azure DevOps allows you to do this with zero downtime. You can test your latest upgrades in the staging environment before swapping them to the production environment. In terms of handling load, App Service is designed to scale up or out manually or automatically. Because your bot is hosted in Microsoft's global datacenter infrastructure, the App Service SLA promises high availability.
Ein Chatterbot, Chatbot oder kurz Bot ist ein textbasiertes Dialogsystem, welches das Chatten mit einem technischen System erlaubt. Er hat je einen Bereich zur Textein- und -ausgabe, über die sich in natürlicher Sprache mit dem dahinterstehenden System kommunizieren lässt. Chatbots können, müssen aber nicht in Verbindung mit einem Avatar benutzt werden. Technisch sind Bots näher mit einer Volltextsuchmaschine verwandt als mit künstlicher oder gar natürlicher Intelligenz. Mit der steigenden Computerleistung können Chatbot-Systeme allerdings immer schneller auf immer umfangreichere Datenbestände zugreifen und daher auch intelligente Dialoge für den Nutzer bieten. Solche Systeme werden auch als virtuelle persönliche Assistenten bezeichnet.
Amazon’s Echo device has been a surprise hit, reaching over 3M units sold in less than 18 months. Although part of this success can be attributed to the massive awareness-building power of the Amazon.com homepage, the device receives positive reviews from customers and experts alike, and has even prompted Google to develop its own version of the same device, Google Home.
A chatbot is a computer program that simulates human conversation through voice commands or text chats or both. Chatbot, short for chatterbot, is an Artificial Intelligence (AI) feature that can be embedded and used through any major messaging applications. There are a number of synonyms for chatbot, including "talkbot," "bot," "IM bot," "interactive agent" or "artificial conversation entity."
In 2000 a chatbot built using this approach was in the news for passing the “Turing test”, built by John Denning and colleagues. It was built to emulate the replies of a 13 year old boy from Ukraine (broken English and all). I met with John in 2015 and he made no false pretenses about the internal workings of this automaton. It may have been “brute force” but it proved a point: parts of a conversation can be made to appear “natural” using a sufficiently large definition of patterns. It proved Alan Turing’s assertion, that this question of a machine fooling humans was “meaningless”.
Once the chatbot is ready and is live interacting with customers, smart feedback loops can be implemented. During the conversation when customers ask a question, chatbot smartly give them a couple of answers by providing different options like “Did you mean a,b or c”. That way customers themselves matches the questions with actual possible intents and that information can be used to retrain the machine learning model, hence improving the chatbot’s accuracy.
Chatbots currently operate through a number of channels, including web, within apps, and on messaging platforms. They also work across the spectrum from digital commerce to banking using bots for research, lead generation, and brand awareness. An increasing amount of businesses are experimenting with chatbots for e-commerce, customer service, and content delivery.
In other words, bots solve the thing we loathed about apps in the first place. You don't have to download something you'll never use again. It's been said most people stick to five apps. Those holy grail spots? They're increasingly being claimed by messaging apps. Today, messaging apps have over 5 billion monthly active users, and for the first time, people are using them more than social networks.
In this article, we shed a spotlight on 7 real-world chatbots/virtual assistants across industries that are in action and reaping value for their parent companies. From streamlined operations and saved human productivity to increased customer engagement, the following examples are worth a read if you’ve ever considered leveraging chatbot technology for your business (or are curious about the possibilities).
Natural Language Processing (NLP) is the technological process in which computers derive meaning from natural human inputs. NLP-Based Conversational Bots are machine learning bots that exploit the power of artificial intelligence, which gives them a “learning brain.” These types of conversational bots have the ability to understand natural language, and do not require specific instructions to respond to questions as observed in types of chatbots such as Scripted and Structured Conversational Bots.

Context: When a NLU algorithm analyzes a sentence, it does not have the history of the user conversation. It means that if it receives the answer to a question it has just asked, it will not remember the question. For differentiating the phases during the chat conversation, it’s state should be stored. It can either be flags like “Ordering Pizza” or parameters like “Restaurant: ‘Dominos’”. With context, you can easily relate intents with no need to know what was the previous question.
Designing for conversational interfaces represents a big shift in the way we are used to thinking about interaction. Chatbots have less signifiers and affordances than websites and apps – which means words have to work harder to deliver clarity, cohesion and utility for the user. It is a change of paradigm that requires designers to re-wire their brain, their deliverables and their design process to create successful bot experiences.
A chatbot (also known as a talkbots, chatterbot, Bot, IM bot, interactive agent, or Artificial Conversational Entity) is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods.[1] Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatterbots use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.

aLVin is built on the foundation of Nuance’s Nina, the intelligent multichannel virtual assistant that leverages natural language understanding (NLU) and cognitive computing capabilities. aLVin interacts with brokers to better understand “intent” and deliver the right information 24/7; the chatbot was built with extensive knowledge of LV=Broker’s products, which accelerated the process of being able to answer more questions and direct brokers to the right products early on
Dan uses an example of a text to speech bot that a user might operate within a car to turn windscreen wipers on and off, and lights on and off. The users’ natural language query is processed by the conversation service to work out the intent and the entity, and then using the context, replies through the dialog in a way that the user can understand.
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.
Note — If the plan is to build the sample conversations from the scratch, then one recommended way is to use an approach called interactive learning. We will not go into the details of the interactive learning here, but to put it in simple terms and as the name suggests, it is a user interface application that will prompt the user to input the user request and then the dialogue manager model will come up with its top choices for predicting the best next_action, prompting the user again to confirm on its priority of learned choices. The model uses this feedback to refine its predictions for next time (This is like a reinforcement learning technique wherein the model is rewarded for its correct predictions).
There are different approaches and tools that you can use to develop a chatbot. Depending on the use case you want to address, some chatbot technologies are more appropriate than others. In order to achieve the desired results, the combination of different AI forms such as natural language processing, machine learning and semantic understanding may be the best option.
Marketing teams are increasingly interested in leveraging branded chatbots, but most struggle to deliver business value. My recently published report, Case Study: Take A Focused And Disciplined Approach To Drive Chatbot Success, shows how OCBC Bank in Singapore is bucking the trend: The bank recently created Emma, a chatbot focused on home loan leads, which […]

Chatbots are often used online and in messaging apps, but are also now included in many operating systems as intelligent virtual assistants, such as Siri for Apple products and Cortana for Windows. Dedicated chatbot appliances are also becoming increasingly common, such as Amazon's Alexa. These chatbots can perform a wide variety of functions based on user commands.

Eventually, a single chatbot could become your own personal assistant to take care of everything, whether it's calling you an Uber or setting up a meeting. Or, Facebook Messenger or another platform might let a bunch of individual chatbots to talk to you about whatever is relevant — a chatbot from Southwest Airlines could tell you your flight's delayed, another chatbot from FedEx could tell you your package is on the way, and so on.
Companies use internet bots to increase online engagement and streamline communication. Companies often use bots to cut down on cost, instead of employing people to communicate with consumers, companies have developed new ways to be efficient. These chatbots are used to answer customers' questions. For example, Domino's has developed a chatbot that can take orders via Facebook Messenger. Chatbots allow companies to allocate their employees' time to more important things.[10]
Two trends — the exploding popularity of mobile messaging apps and advances in artificial intelligence — are coinciding to enable a new generation of tools that enable brands to communicate with customers in powerful new ways at reduced cost. Retailers and technology firms are experimenting with chatbots, powered by a combination of machine learning, natural language processing, and live operators, to provide customer service, sales support, and other commerce-related functions.
LV= also benefitted as a larger company. According to Hickman, “Over the (trial) period, the volume of calls from broker partners reduced by 91 per cent…that means is aLVin was able to provide a final answer in around 70 per cent of conversations with the user, and only 22 per cent of those conversations resulted in [needing] a chat with a real-life agent.”
Back in April, National Geographic launched a Facebook Messenger bot to promote their new show about the theoretical physicist's work and personal life. Developed by 360i, the charismatic Einstein bot reintroduced audiences to the scientific figure in a more intimate setting, inviting them to learn about the lesser-known aspects of his life through a friendly, natural conversation with the man himself.
Companies use internet bots to increase online engagement and streamline communication. Companies often use bots to cut down on cost, instead of employing people to communicate with consumers, companies have developed new ways to be efficient. These chatbots are used to answer customers' questions. For example, Domino's has developed a chatbot that can take orders via Facebook Messenger. Chatbots allow companies to allocate their employees' time to more important things.[10]
The goal of intent-based bots is to solve user queries on a one to one basis. With each question answered it can adapt to the user behavior. The more data the bots receive, the more intelligent they become. Great examples of intent-based bots are Siri, Google Assistant, and Amazon Alexa. The bot has the ability to extract contextual information such as location, and state information like chat history, to suggest appropriate solutions in a specific situation.
This kind of thinking has lead me to develop a bot where the focus is as a medium for content rather than a subsitute for intelligence. So users create content much as conventional author, (but with text stored in spreadsheets rather than anywhere else). Very little is expected from the bot in terms of human behavious such as “learning”, “empathy”, “memory” and character”. Does it work?
According to this study by Petter Bae Brandtzaeg, “the real buzz about this technology did not start before the spring of 2016. Two reasons for the sudden and renewed interest in chatbots were [number one] massive advances in artificial intelligence (AI) and a major usage shift from online social networksto mobile messaging applications such as Facebook Messenger, Telegram, Slack, Kik, and Viber.”
In the early 90’s, the Turing test, which allows determining the possibility of thinking by computers, was developed. It consists in the following. A person talks to both the person and the computer. The goal is to find out who his interlocutor is — a person or a machine. This test is carried out in our days and many conversational programs have coped with it successfully.
If your interaction with a conversational bot is through a specific menu (where you interact through buttons but the bot does not understand natural language input), chances are you are talking to a bot with structured questions and responses. This type of bot is usually applied on messenger platforms for marketing purposes. They are great at conducting surveys, generating leads, and sending daily content pieces or newsletters.
As digital continues to rewrite the rules of engagement across industries and markets, a new competitive reality is emerging: “Being digital” soon won’t be enough. Organizations will use artificial intelligence and other technologies to help them make faster, more informed decisions, become far more efficient, and craft more personalized and relevant experiences for both customers and employees.
Need a Facebook bot? Well, look no further, as Chatfuel makes it easy for you to create your own Facebook and Telegram Chatbot without any coding experience necessary. It works by letting users link to external sources through plugins. Eventually, the platforms hope to open itself to third-party plugins, so anyone can contribute their own plugins and have others benefit from them.
Polly may be a business-focused application, but the chatbot is designed to improve workplace happiness. Using surveys and feedback, managers can keep track of how effectively their teams are working and address problems before they escalate. This doesn’t only mean organizations will run more productively, but that workers will be happier in their jobs.
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.
This chatbot aims to make medical diagnoses faster, easier, and more transparent for both patients and physicians – think of it like an intelligent version of WebMD that you can talk to. MedWhat is powered by a sophisticated machine learning system that offers increasingly accurate responses to user questions based on behaviors that it “learns” by interacting with human beings.
However, chatbots are not just limited to answering queries and providing basic knowledge. They can work as an aid to the teacher/instructor by identifying spelling and grammatical mistakes with precision, checking homework, assigning projects, and, more importantly, keeping track of students' progress and achievements. A human can only do so much, whereas a bot has virtually an infinite capacity to store and analyse all data.

AI, blockchain, chatbot, digital identity, etc. — there’s enough emerging technology in financial services to fill a whole alphabet book. And it’s difficult not to get swept off your feet by visions of bionic men, self-executing smart contracts, and virtual assistants that anticipate our every need. Investing in emerging technology is one of the main […]


The biggest benefit of having a conversational AI solution is the instant response rate. Answering queries within an hour translates into 7X increase in the likelihood of converting a lead. Customers are more likely to talk about a negative experience than a positive one. So nipping a negative review right in the bud is going to help improve your product’s brand standing.


There are NLP services and applications programming interfaces that are used to build the chatbots and make it possible for all type of businesses, small. Medium and large scale. The main point here is that Smart Bots have the potential to help increase your customer base by improving the customer support services and as a result boosts the sales as well as profits. They are an opportunity for many small and mid-sized companies to reach a huge customer base.
A chatbot (also known as a spy, conversational bot, chatterbot, interactive agent, conversational interface, Conversational AI, talkbot or artificial spy entity) is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods.[1] Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatbots use sophisticated natural language processing systems, but many simpler ones scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.
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