Every passing day, we are hearing some breakthrough for Artificial Intelligence. We read about the Humanoid – Sophia, Google’s AI winning game GO and several other things. It is very apparent that AI and Machine Learning together would be able to replace several tasks that are based on methods and logic. Chatbots are already here which are sending out responses to humans. VPAs (Virtual Personal Assistants) are able to help with complex travel bookings as well. However, what is missing currently is these chatbots or VPAs do not understand human emotions – as yet. Emotion AI is all about bringing in emotion or empathy to the artificial intelligence so that the human-machine interaction is more human-like.
With the increased penetration of internet and mobile, user-generated content is growing at a rapid pace. Also with a cut-throat race to acquire a customer or even to retain a customer, every brand or company needs to understand what their customers are saying. People write their reviews on various websites, facebook, tweet about it or post photos with comments. If brands or companies want to understand if their brand is being talked about in a positive way or a negative way, what they need is to carry out Sentiment Analysis on this data.
But, what is Sentiment Analysis?
As the name suggests, it is the analysis of data to find out what that data is representing. Are there more happy emotions or sad emotions or there is anger. The Sentiment Analysis tools capture data from various sources. Various types of algorithms are run on this data to identify the emotions appearing in the data. Natural Language Processing (NLP) and Machine Learning (ML) are important backbones of this analysis. NLP allows the tool to process human language. ML allows the tool to learn various moods appearing in the data.
Humans have weird ways to express themselves. When someone says “Wow!!”, it could mean real appreciation or it could mean sarcasm. We also say “Hating <brand> is not really my thing” – which may be a positive comment about the brand. Or when we say “He was so aggressive, but then I used to like him” – it represents mixed emotions. “I really love my phone, and I’d hate to lose it” – two different emotions about two different entities. And I can go on and on. Hence the tool has to learn all such variations and then come up with a score which would help the brands and businesses to improve their services. Or such score could also be used to create a marketing plan around the emotions.
The tool analyses words, context, the frequency of words, their occurrences with other words and then starts giving you insights. Take a look at the data gathered from tweets during Chennai Rains in 2015.
You can read the full analysis and see how sentiment analysis could be useful even during crisis situations. Or take a look at data that was analyzed on World Book Day about two biggest e-commerce players (then!!). As you would see, the analysis suggests a marketing plan based on the Sentiment Analysis.
Natural Language Processing (NLP), Machine Learning, Supervised Machine Learning
RPA – Robotic Process Automation
RPA stands for Robotic Process Automation. It is a process automation concept which allows business users to automate their tasks with minimal help from technical teams. We all are familiar with automation and have done it in some or the other form in our lives. May it be scheduling an event or automating test cases using tools like Silk, Selenium or some scripting language. While test case automation is relevant for technical teams, the business teams have very low relevance for this kind of automation.
So, RPA is not for technical folks?
Yes, you are right. Primary benefit of RPA is for business users. Think like your clerical team is getting additional hand – a robotic hand – to do all the mechanical, mundane work. Typically your back office teams end up doing tasks which are of repetitive nature. Any repetitive task done by a human is prone to errors as well as delays due to boredom. However, RPA helps businesses automate such tasks and get the human beings to do some intelligent tasks such as direct customer interactions, which in turn prove beneficial for the business Growth.
What All Things RPA can do?
RPA can read data from various sources such as emails or excel files, process them and then put into your application in a required format. Once the RPA software is trained to do this, it will continue to execute as long as we want, without any errors or delays. Typical RPA softwares can read emails, excel files. You can train those software on your data entry software to enter data read from email or excel file. If you need, RPA can also open websites and extract data in the format that you want.
The RPA software is termed as “low-code” or “no-code”. This is primarily because they do not need much coding. Even business users can configure and train the RPA software to perform the required tasks and to do it repetitively.
Essentially RPA implementation can give you huge benefits in terms of time savings, cost savings, error free data entry and thus overall process efficiency.
Consider a case where backoffice worker receives address verification request from companies agent over email. The worker needs to open that email, read address and attachment. She would need to verify address details from third party application or website and then make a phone call for contact number verification. Currently, a human worker does all these tasks. With RPA, all of this could be done by a software.
RPA software providers:
- Automation Anywhere
Automation, Artificial Intelligence, Business Process Management (BPM), Robotics
AR – Augmented Reality
As is evident from the name, AR (Augmented Reality) is about augmenting the reality through the use of computer or computer aided devices. I would pull out scene from Minority Report to give an instant example of Augmented Reality:
While the data is projected using computer, the images etc are moved using hand gestures. The glass screen that is seen is a real world whereas the projected images are virtual. The actions are virtual but they result into some real action. All this is achieved using Augmented Reality.
What’s Latest in Augmented Reality space?
Minority Report was in 2002. Technology is much advanced now and it several things are happening on this front. (BTW – researchers have recreated Minority Report using AR).
PokemonGo game became very popular due to usage of AR in the gaming activities (2016).
Snapchat introduced AR into their app and every phone has become a device which can create images or videos with some emojis added to the reality. Snapchat launched this feature in Sept-2017.
Alexa assisted glasses will be introduced in CES (2018). If you watch that interview, it would be an advanced version of Google Glass (2013) where person wearing the glasses would be able to talk to Alexa fitted in the glasses and responses would be projected in front of the eyes!!
Augmented Reality VS Virtual Reality
It is often easy to confuse Augmented Reality with Virtual Reality. However, there’s an important and basic difference between these two technologies. In AR, reality is augmented by computer generated inputs such as sounds / videos etc. Whereas in VR (Virtual Reality), entire environment is created with the help of computer and computer aided devices. In AR, user can see real world, whereas in VR, user is completely immersed in the virtual world.
Interesting Use Cases:
- Virtual Dressing Room for e-commerce
- Immersive Learning using Mixed Reality
- Surgeons can see real time patient data while surgery is in progress using virtual retina displays
Virtual Reality, HMDs, Eye Glasses, Mixed Reality, Google Glass
Chatbot is a computer program that communicates with a human either via audio or text. It is built with a specific purpose in mind and usually have a very narrower scope.
Is Chatbot same as Personal Assistant like Siri/Cortana?
Personal assistants like Siri or Cortana have a far wider scope. They can answer questions related to current weather conditions. Or they can tell you jokes or recommend currently running movie. Whereas chatbots have a very specific function such as selling a product or providing help related to a product. They can also guide you through FAQ. But they can’t do more than that.
Typically chatbot assumes lot of human traits. It can have a photo of its own or it can have a name of its own. A chatbot can be mentioned in a conversation or it could be called out using name. It could be added to a group conversation or one could have one-to-one chat with the chatbot.
This type of chatbot uses NLP (Natural Language Processing) to understand human questions and responses and responds in such a fashion that human can understand.
Rule Based Chatbot
This type of chatbot presents the information in a very structured manner and doesn’t really understand conversational language. e.g. Instead of asking “Would you like to have a pizza or pasta?”, it would prompt “Choose your option: 1. Pizza 2. Pasta” etc. NLP is missing in these types of chatbots.
Historically there have been several types of bots such as crawlers, scarpers etc. All these are automated programs and were meant to do specific tasks, but they didn’t communicate with humans directly. Chatbot is advanced version of bots where bots are communicating with Humans. Essentially they are helping humans answering their questions or even selling some products to humans.
Some chatbots can initiate conversation proactively (after first initiation by human) whereas others need humans to start the interaction everytime. Proactive feature could be used by news websites to push the top stories or breaking news to humans who had initiated chat at least once and had opted in to receive these kind of notifications.
- Selling a product
- Providing account balance to authenticated customers
- Handle call center kind of work
- Send top news items
- Send movie recommendation
Developers can choose from variety of platforms and software options to build and deploy chatbots quickly.