MartechBrain | E18 – Tapan Barman on “Conversational AI”

In this episode, Rajesh Jain speaks to Tapan Barman, co-founder, mihup, about “Conversational AI: Re-imagining the Human-Machine Interface”

Transcript:

Rajesh Jain(host): Hi everyone, welcome to martech brain a net core initiative where we talk to some of the best brains in martech and in the tech space and delt deep into one topic. My guest today is Tapan Barman, co-founder of MIHUP. Tapan’s chosen topic for our conversation today is conversational AI reimagining the human machine interface, so human machine communications. So, welcome to martech brain Tapan.

Tapan Barman(Guest): Rajesh thank you so much for inviting me. It’s an honor and a privilege to be part of this  show. Thank you so much.

Rajesh: So, tell us more about MIHUP ? What does it do ? And then we”ll get to the wider topic linked with that.

Tapan: Sure, so  MIHUP is  “May I Help You Please” ,  if you consider the full name of the company , so we considered MIHUP as a  journey ,  which we have started in 2016 and we aim to build a company to create a greater impact for the society with some cool technology. So in the MIHUP what we are doing , we are building voice AI platform and we  help enterprise developers to add voice interface for any device applications, so that’s how it works and we initially  raised the investment from the access partners in 2016 and Subrato from excel wrote the first check to us and, i am the co-founder and i do have  Biplab and Sandipan Chattopadhyay was the co-founder of this company. So we are about  50 plus sort of missionary team  operating from Kolkata and Bangalore . So that’s about the company.

Rajesh: So what are the problems that MIHUP actually solves for companies?

Tapan:  So  look,  when  you are saying the voice AI platform  you look at the problem imagine, you are calling a call center and you are  navigating through a complex menu tree like  for this you press one for this you press two. Now we are helping  to remove the entire complex menu tree so that users can directly  talk to a system or the machine where machines can  answer most of the queries without human agents. So that’s the kind of problem we are trying to solve with the call center and also  when you are calling, any calls or you hear, the call can be recorded for the quality and training purposes but the manual keyword team can hardly analyze  one- two percent of the calls. So we are also helping enterprises to  sort of analyze 100 percent of the interactions to get all kinds of insights which is helping them to improve sales collection and everything. So that is one part of the problem which we are trying to solve with the help of MIHUP. On the other side we are also building a  virtual agent on the top of the platform for different kinds of  IOT applications, say for example smart cars . So we recently  deployed our virtual agent with TATA motors. They are using that virtual engine in their cars so that users can control everything inside the car just by talking, so that’s the kind of  problem area where we are trying to  build applications and trying to solve the problems.

Rajesh: So , in a way what you’re basically “saying it that for all of us speaking is the most natural interface rather than touching clicking and everything else that we have been doing all these years and you’re taking us back to the origins as it were how we would communicate, we are now communicating that way with machines”

Tapan: Absolutely ,  the way we come to take the example of  India where  90 percent of the population don’t speak in English, and most of the  applications or devices  if you see the interface is pretty complicated , it is not very user-friendly . So what you have found  most of the people are comfortable  to speak their own native language rather than typing  in the keyboards. That’s why I think  voice interfaces are the most intuitive , which can help users to express their interests  and desires in a more effective way. So that’s where it is going to be the change in the next era, where we’ll see a lot of voice devices happening in the market. So, I think these are the areas where  wires can play key roles in transforming the way we are  working with those digital devices. 

Rajesh: In fact we’ve already seen in the last few years the rising popularity of devices like alexa, and now with smart tvs. You have the remotes where you can actually speak .Anyone who has tried to type  using the tv remote, search terms etc it is very very painful, so voice becomes the natural way and even in car navigation systems like example , you talked about TATA motors, just speaking so put the ac on or play this or switch to this music station etc now become so much simpler rather than  trying to navigate through the dashboards.

Tapan: And also  those are absolutely  some of the important and relevant use cases which are happening around us and also I think, if you look at the perspective of a farmer who just wants to understand which  season is appropriate for say ABC for cultivation . So, how we can get the best help from some point and with the help of machines, because it’s very hard to  help those in that scale of commerce with that kind of information. These kinds of virtual agents can be  much more effective. And also think of  virtual agents. Imagine a virtual engineer bank where  you don’t have to travel to a branch just to inquire about the basic information. The way the JAN DHAN account holders are doing  today in India in remote areas.  So,  we actually can enable them and empower them to equip all kinds of information. They want this kind of  application which can run over an IVR system or the call center. So wide the numerous use cases possible and ultimately it will help a large set of people  to empower them to get much more or get much more confidence on the information about the entire thing, so that’s where I think  the change will happen in the coming days.

Rajesh: So, Tapan, why is it taking off now? So i think if we take the area of conversational AI. so what are the  building blocks which are helping conversational AI really rise onto the forefront  in this. And I also want to take up this element of we’ve talked about the conversation part and we also want to discuss in the AI part where does the AI come into the whole system? 

Tapan: Correct, so Rajesh  in conversation also we consider conversation in four different categories. It can be  human to machine  machine to machine machine to human and human to command, so these are four types of  conversation which happen. And what is AI? AI is basically,  you train a machine as a computer with  certain knowledge with certain data which actually can help a machine or system to  drive a conversation or drive  or drive certain instructions, that is called  artificial intelligence. Say for example, you are a call center agent and you are actually  talking to a customer. Now, imagine while you are talking to a customer you are getting  some sort of  guidance from the system itself but the system is telling you and going first you , you speak slowly . you are talking nonsense you should talk in the right way. So that kind of  instructions can come from the machines. when the machine is artificially intelligent with some pre – loaded data. Now how we get those data, actually we get from the users  uses the way we talk and  the way we communicate from all kinds of  user behavioral data is actually  we are using to train machines and we are using the best to train machines to train the worst at the bottom. So that’s how artificial intelligence works. Now why it is taking up now, because  there are so many  important things happening. First of all, I think the most important piece is , if you have to train a system we call it machine learning so you have to train your machine with more data. It requires lots of computers and earlier it was very very expensive. You see the share market price of the NVIDIA which is now  going up very much right so that itself proof that NVIDIA is a company  where they are doing pretty well and the devices that they are  producing which we use for this computation is actually available at some reasonable cost, so compute cost is available at reasonable price, that’s what is driving this a lot of  machine learning activities  across the world and in this domain not just the voice multiple activities are happening. So I would say the compute cost is lower and second is  now we are at a point where we are sitting with lot of data,  enough data which is like unused data so down now the enterprise and the companies or I would say the researchers the developers they are trying to  find out how much insights  and how much insights you can get from those data and what’s the best way to do that? And it to get next set of your customer, say for example flipkart ,one customers from tier 2 tier 3 repeatable customers not just the first time customer how it is possible ?Second, for example, I just  want to improve  customer service  or I just want to know my customer profile in a much better way than how it is possible! Third, for example, I live in a city where my nearest city scan  system or the facility available  is far away from 50 kilometers. Is it possible to get a city scan system or facility here in my town and since I don’t have a trained operator to maintain that? Can you use that with AI , so these kinds of requirements actually drive those factors  in this space.

Rajesh: So, Tapan, how did you get interested in this area? Tell us a little about your background and how did this whole conversational AI get to the forefront in your life?

Tapan: So about my background,  I come from a very , I would say  village. It is in tier three cities. I would say it’s very close to the Assam and Bangladesh border and my native is Rajbongshi , and the language I speak my native is Rajbongshi which is not even Bengali not in English and which is not even  part of this 22 scheduled language of India. But  there are three million people who speak in Rajbongshi. So for me I feel  language is ,speaking English is sort of a barrier for me. I’ve learned  how to speak English to get into my profession. So I also believe  if you don’t speak , if you don’t have the opportunity to speak your own native language you lack confidence. So that’s why, I was always interested to know  about how to solve this problem. Initially,  maybe  some  translator engine I’ll speak in  Bengali and get transferred to English it is relevant for multiple languages and. so backward wise.  I graduated  in computer science in 2006. I was working in a public sector company for two years and started my own company in 2008 but was doing  reselling business with the consulting business in the company. But I always  wanted to build this application  to solve this problem and finally  I got the opportunity in 2014. Where i got introduced to Sandipan at the city of Justdial who was having 10 years experience of building or working with the voice. And also thankfully people are binned. Finally we got into this  problem space and  started building those applications around the problem, so that’s how we got started and got attracted to this problem.

Rajesh: Fascinating story and I think this problem that you talked about breaking the language barrier for communication I think is very very critical especially in India, where we have so many so many different languages and even variations in those languages. I’m assuming one of the things that you have to do when you’re training the AI system is of course you need a lot of data but you also need to train it in the domain understanding. 

Tapan: Correct yes.

Rajesh:  And so in a car, so it’s not an open-ended problem ,and that is I think very important to where MIHUP plays a role right? 

Tapan: Absolutely, I think  it is relevant. Say for example when you’re talking to a person and we talk in a particular topic or context and if you can follow that conversation, he hardly  remembers that 200 words in that entire conversation which was very very useful. So we also believe  since this is machine learning in AI and which gets improved with enough data and the more you use AI it will get you to improve, that’s how it works. So i think you always debate about the accuracy or  about the AI system or the other particular system. So we always said  it has to be accurate within the context, is it accurate enough for that particular context. The system needs to understand everything it is not even required. So that’s why i think, if we want to solve this problem so we have to pick the problem or the context and then we should try to attend or try to solve the problem rather than  solving the problem for anything it doesn’t make any sense for us so whenever you’re trying to our approach  to to build the solution of the platform is that, use case is the primary you focus with use case and what problem you are trying to solve with the help of this particular AI or the conventional thing and then you try to build the model accordingly then it will work perfectly for the use case. 

Rajesh: And like, if we go back to the TATA motors example  are you also confident that even if the languages spoken are different , you can handle those scenarios or is it limited to say only English or Hindi or  i’m assuming there’s a translation part of it which is also involved before we feed it to the AI engine.

Tapan: Correct, so  absolutely we are  confident so far. We have  rolled out four language. We support Hindi English  Tamil and Bengali, and we are also  rolling out another six language so we do have a plan to support in language by next year. And we are also doing not just only for TATA private vehicles but also for the commercial trucks where the user is not very sophisticated, if you can imagine that dialects and accent could be  hugely different. Now the way we have to  build the platform and that  the way we have trained it is capable to understand multiple dialect and accents  within that context and that’s why we don’t focus on on the takes output, otherwise we generally focus on meaning so we call it speech to meaning engine, where from the dialect itself can  get actual intent from that part. So that’s why I think. since we we focus on the speech to meaning part that’s why handling multiple language within the context  is not a challenge but again  as I said  AI can be improved with more learning and more data. That’s why we do have a  sort of feedback loop in the entire system where we collect those data through a mobile company, an app which goes to the cloud and  comes back with the improved version that’s how it works. But generally the entire system works in that, in the car or the trucks is without internet so you don’t need connectivity. 

Rajesh: Right, so in a way the power of this. Really is that  if we look ahead few years this whole human machine interface where we’ll be able to speak to the gadgets in our homes to the devices that we have to possibly  air conditioning units the tvs the washing machines the refrigerator house, so all of these devices which are becoming more and more complex because there’s a lot more digital elements which are coming into these devices and what’s also therefore changing is the way we communicate so rather than going through keypads and layers of interfaces we can just speak and get the  get the job done. 

Tapan: Absolutely, so entire  thing, the user interface will  get through a transformation and it will be like first device, so in the future there will be  sort of no key   recently  apple they have sort of launched a prototype of that kind of future device and where there is no keyboard it’s just a voice with siri so that  you can  operate the entire machine with the voice. So that kind of future we can expect from the domain, but i think  in India  i still believe  though the alexa  of course is  bringing new trends  they have created a new opportunity for a lot of  companies but for India alexa is still not relevant “i believe” because most of the Indians  they live in  700 square feet of house where alexa is much much more bigger. I think  from the Indian context and perspective we are still  left to install a lot of confidence to Indian, so that they can effectively use mobile phones at least in the proper way and they have to believe with the help of the tools which are very very powerful. Smartphones or maybe normal phones, you can do a lot of things. I think that’s where the confidence is not there because  I think  most of them think  this is something not for me. so that fear has to go first , so that they  should get connected to the digital ecosystem, which you’re building and that digital platform the health everything is connected to. So that’s why I think  that transformation has to happen in the mindset first in India and the devices for India, different kinds of devices are required, not the Alexa . 

Rajesh: Correct, so one question really on how marketers can leverage this sort of revolution that’s coming in conversational AI , how can marketers make use of this technology?

Tapan: Oh many multiple ways , marketers can  effectively use this particular application in several ways. I can give you a couple of examples where we have  sort of helped multiple companies  in our own way , say for example  we are working with the edutech company, they are trying to   onboard new students on their platform. Now they want to analyze the counselor performance, when the counselor is being counseled as students whether the counseling was appropriate or not? How effective was it? so because that’s happening in skill and humans can really  assess each of those counseling sessions. Now they are using AI platforms where we are analyzing all the counseling  every day and we are giving recommendations  to individuals to team or to the companies, where they need to improve so what’s the best practice? What’s the thumb rule? What are the best performers doing? How can we sort out which clone is best for the bottom? So this is one of the examples, you could also use . We’re all also working with  insurance companies, they are using this platform to improve their sales because they are saying look I do have two thousand callers every day, they are calling  customers  but my conversion is very very low. So how can we help me? So we are analyzing those in. The entire call and we are telling look  this 10 salesperson is your best and how they are because this is the pitch that’s how they’re talking to their customers and this script has to be used and we are using that script to train the system for the machine. And the machine generates feedback  for the rest of the agents.

Rajesh: All the other agents excellent  

Tapan: That’s how marketers are getting  benefits out of this product for the system 

Rajesh: So, looking at the broader  impact of this on society Tapan, what do you see as the impact if you look ahead? What’s the impact of conversational AI really on society in general?

Tapan: Yeah, i strongly believe as I mentioned  in the change in the mindset  I think i can give you a lot of examples  still  in our society especially in India we consider any computer or the devices the machines is an evil factor and because of  lack of  education of the literacy a literacy of  i think that about multiple things, we still consider  is not great to be in the social media platform because that is something not allowed in our society in some areas. And as I said we still fear the machines. We have  a lot of people who don’t know how to use atm machines still today . So I think fear of machines is  something that is the biggest factor which is  driving a lack of confidence in us. I think  if we want to transform or change your society the entire citizen has to be empowered and we’ll have to install a lot of confidence and that does the entire citizen has to become smart enough,  so that they can make better and informed decisions. And that is only possible when you empower them with a tool which is very easy to use and with that tool they can actually  access to anything and that’s where boys can play a very very effective role.

Rajesh: And and I presume it would be Mihup’s vision also! 

Tapan: Absolutely,  we just want to be the trusted factor  like  as i said talby,  MIHUP we want to be the one of the trusted factor for everyone and they should think of MIHUP while they’re using  voice to access anything  any machines or the applications or anything that’s what our aspiration is.

Rajesh: I think, it’s a great view into the future I think basically if I were to summarize two or three of the key points that you’re saying is that we are going to see the rise of conversational interfaces, where we will be able to communicate  just by speaking onto devices. The human and machine interface will keep improving the more the data. That is there the better the interface can be and even in the example that you gave in call centers or in conversations you can actually now remove the inefficiencies and the differences which are there between sales. People you can learn from the best and the others can be trained and even guided possibly in real time in conversations that are taking place.

Tapan: Yeah

Rajesh: So I think we are opening up a whole new fascinating world of conversational AI.  So that was a wonderful  introduction to the area of Tapan and we will come to the last part, the fun part, the five ones so quick sort of short answers. One future tech trend that excites you and other than of course conversational AI? 

Tapan: Okay, so I think  other than thinking of  conventional AI  today  i am fond of two things and i’m truly excited  about the potential. One is of course  the way we are leveraging internet for the education and  so MIHUP is working with a  with multiple edutech companies and i can see  today from a place where probably there is no   good teacher may be available good in the sense of   in this in the context of getting better  indicating the foundation. I can think of  accessing a teacher based out of the UK for the education of my child. I think  that is something  fascinating  and it’s going to happen crazy. I think  it’s good for the company, for the country and the society. And second fascinating thing  I think on the health care side  I think  the way we are  thinking of transforming the entire  treatment.  I follow Siddhartha Mukherjee and he talks about   re-engineering cells,  how we can re-engineer the genes and cells,  instead of using pills  that kind of , I think innovation is truly fascinating and really   changes the way we are thinking about the treatment in the future.

Rajesh: Great insights, one tech or trend that has disappointed you? 

Tapan: I would say the way we today  use social media platforms to influence decisions of individuals, I think that is not correct  . Recently if you have seen the advertisement of the whitehead junior  the way they are  sort of an advertising if you learn this code you’ll get a job in Google  ,that kind of advertisement influencing is very bad and that trend has to be stopped.. 

Rajesh: Very good point.  One good book recommendation? 

Tapan: So, I think  the great book is “Zero To One” by Peter Thiel.  I have learned a lot  from that book  and  yeah so  i’d recommend everyone who is  thinking of starting a company. 

Rajesh: And one good person  podcast to follow?

Tapan:  I would actually suggest  two people probably again. I follow Elon Musk  very closely , because he talks about impossible things and makes them possible  that are truly inspiring, and again the Siddhartha Mukherjee  , the way of   innovating the entire health care. I would say the thinking at least. 

Rajesh: Absolutely. I think both have amazing visionaries. And  final question.  one key driving belief in your life?

Tapan: I always believed in one quote from Swami Vivekanand , that was a gift from my mother when i was  in class five, the book is the power capsules, and there is a quote which says  “the success is equal to  purity plus passions plus perseverance”.  I truly believe in that  and I have seen a lot of people in my family and my colleagues and everything. If you truly stand for those three things  it will be successful. And in life success is something the changing post it’s nothing fixed so those three cons factors have to be there for any  sort of achievement here. 

Rajesh: Great great suggestions. 

Tapan: Thank you very much, it was a wonderful conversation with you. I wish you a good future for the world of conversational AI. I think we’re just seeing the starting point of  the power of the internet and AI and technology with the following costs of computing storage. All of that is now coming together to really open up new opportunities going forward especially in the human and machine interface  thank you very much, for the great chat with you Tapan.

Tapan: Thank you so much thank you. 

Rajesh: Thank you everyone, for watching and listening. I will be back with another edition of martech brain next week.