Podcast #11: The Rise of Quantum Computing

Hi there, this is Ed Maguire, Insights Partner with Momenta Partners. Welcome to the Momenta Intelligent Edge podcast series, where we feature leading practitioners and thinkers across connected industry, and the broader technology landscape.   

Today we have a special guest, Professor Ahmed Banafa who is a Professor at San Jose State. Ahmed is a prolific writer and thinker in the connected industry space, he’s done quite a lot of work in helping the industry in the ecosystem at large, reckon with and understanding the implications of emerging technologies, not just peer connected industry, but artificial intelligence and blockchain, and we’re going to hope to cover a lot of these topics in our conversations. 

So, Ahmed thanks so much for joining us. 

Thank you so much Ed, I’m really honored to be with you this morning. It’s a really interesting topic and it’s a timely one, we’re excited about what’s coming in the near future for IoT, including blockchain and AI. 

Absolutely. First of all, let’s get a bit of a level set, I’d love to hear a bit about your background, and what has helped shape your view of technology, and IoT specifically, since that’s our big focus here at Momenta. 

IoT is the way of looking at the big picture, we have many systems, they’re working perfectly by themselves now. You step back and look at the big picture, how that different system will communicate with each other, and create a bigger system here. IoT caught my attention something like six-years ago, I was doing a research about cloud computing, and then in the process of collecting and doing the research I heard some of the terms from Cisco, because Cisco is the one who coined the term ‘Internet of Everything’, that was the first time in 2000. Then they changed to ‘Internet of Things’, and that really triggered some kind of a different thought about what does that mean when you say Internet of Things. Most of the Sci-Fi movies are actually a glimpse into the future, away from the story of the movies, but they give you some kind of indication about what we would like to have in the future, and when you have everything around you alive, and I mean in reacting and responding that is the definition of IoT, and this is how I started doing the research and writing papers about IoT. 

Great. You’ve worked in academia, also providing quite a lot of thought leadership in the media. As you looked at IoT has there been any point of view or perspective that you feel has differentiated your thinking, from the way many others have been looking at the space? 

Well, the way I approached IoT is through three filters, the first one is technology, the second is business, the third is society. This is very calming when you try to make sense of new trends, so you look at it through the three filters. 

The first one is technology; do we have the technology to have this concept IoT?  

And then you move to the next filter if the answer is yes, which is the business, what’s in it for me as an investor or as a company that would like to use IoT or apply IoT.  

Now comes the third one which is the hard one, which is the society, society has two branches, the government, and the users or the citizens. Now, what will be the reaction of the government when you have a big system like this, what will be the reaction of the users, or the citizens when they see that their information is available everywhere, and all they’ll do is just talk to things, and they’re going to do whatever they need to do. 

So, once the trend and in this case its IoT, passes through the three filters now you’re talking about a new technology, you’re talking about a new trend that people are accepting. We still have some challenges, there is no question about this, and we still have a few obstacles we must overcome. 

How would you compare and contrast what we called IoT? You’ve been looking at it now around six-years ago, that was really when the term started to come into common usage. If you look back at prior technology ways, what in your mind is different that’s really distinguished what has been called Internet of Things, from some of the other trends earlier, like Enterprise Applications for instance? We kind of know a lot of what’s happening on the technology side with sensors getting cheaper, but are there some other fundamental business differences that have characterized this market or this space as its evolved. 

That’s a very good question, its dealing with the second filter which is the business. When you talk about IoT it depends on who you’re talking to, that’s one of the problems of explaining IoT to everybody. So, if you’re talking to a factory, IoT for them is considered the IIOT which is the Industrial IoT sensor productive or preventive maintenance, saving money, saving time on all the tasks and automating the tasks.  

If you talk to the consumer which is what everybody sees now, it’s exciting because you’re talking about how, ‘How can IoT change my life?’ I always give this example, and in my last speech I was giving a lecture or speech in Brazil and I explained that to them, IoT for me as a consumer is I wake up in the morning, I look in the mirror, and the mirror is a smart one, and the term ‘smart’ is the key thing here. The mirror will tell me, ‘You look tired’, ‘I’ve contacted your doctor’, ‘Uber is waiting outside to take you to the doctor’, ‘I moved your conference/meeting to tomorrow’. I go there and finish with the doctor and then a drone will bring that medication to me, and then once I receive it in that orange container, the pills I am taking are smart pills. So, if I take one of them, the doctor will know about that, so I’m not going to overdose on it, or ignore it.  

So, this is going to make our life much easier because somebody’s taking care of the things that is crowding, or jamming our schedule for things that can be done by an automated one. So, when you look at IoT from this perspective, for the industrial one it’s fantastic, it’s going to help, it’s going to save on the three important things for any business which is time, money and staff. From the consumer it’s going to make it so easy for them to give them their time. 

Yes, no doubt, and the transformation of business process of course is obviously a clear second order benefit, or implication of connecting technologies. You mentioned society, and I think this is really an interesting angle that we haven’t explored as much in some of our podcast conversations. I’d be interested in terms of how you apply a societal lens to Connected Industry, or IoT; what are some of the opportunities, threats, and potential risks, whether it be culture, whether it be the structure of governance, and our personal lives from having many devices that are connected? 

That’s a very good question, and it’s really a timely one, as we talk now, we know that Mark Zuckerberg is being grilled in the House, I was listening to it on the way to my office. I’ll give you a simple example to see how we can pass through the two lenses, or the two filters before technology and business, and how we stuck with the society. Google glasses, everybody would like to have something in front of their eyes, they can just move their finger and then do some kind of calculation, get some information. You think about the Terminator movie, you think about Tom Cruise movies which are fantastic. Now, that technology is there, Google did it, there are applications for something like that, and if there is no business then Google aren’t going to waste millions of dollars in that, stuck with the society, because I don’t want to sit with someone looking at me and then I tell him, or her, ‘No, I was sick last night’, and they look at my Facebook and my status says I was partying, or I was hiking, or something like that. So, that is the case of where the society can stop a product like that. That’s why Google went back and said, ‘Okay, it’s not for everybody, it’s just for certain people in society, like dentists, HR…’ people who need that information right away, available to them, fire-fighters, something like this which is going to be in front of their eyes. So, this is an example of how society can stop this one.  

Here's the other problem which is the government. The pillars of the user trust are three, so the user trust built in three pillars, and we call them SSP, Security, Safety, and Privacy. Now the government is worried about the invasion of privacy, safety, and the security, because you have breaches everywhere, regulation must be there to make sure that nobody is abusing this kind of data. The hearing we have today in the House is an example of how the government is worried about data, and the use of data to create actions, or to interfere with certain events in our life. This is how I look at it from the society. 

It’s quite timely, our conversation is occurring the day after the Mark Zuckerberg hearings were in the Senate, and the concerns I think people have about what happens with data certainly amplifies the concerns that many businesses have had. One of the conversations that we at Momenta have with the clients that we advise, and their clients in their industrial firms is, if you’re a farmer, who owns the data that gets collected from a harvesting machine, or a sensor when you buy a sensor from a vendor? This is an ongoing challenge, I’m wondering at least from your standpoint, have you seen any helpful regulation or frameworks evolving? I know we’ve got GDPR that’s set to take shape this year in Europe, but have you found any useful frameworks at least to help companies that are trying to think about this? 

The house is running a bill which is called the Honest Ad Act, which Twitter accepted, and Facebook support, this is just one way for them to make sure that our data is not abused, so they can use it, but they cannot abuse it. The problem with any kind of new technology, because IoT is basically the big framework of what we are dealing now. Facebook is just one of those engines that’s used in IoT, because I can get all the information about the consumer, so can for example, match his or her information with another website, and AI will make a decision about, ‘You should buy this/you should not buy this one’, all this information Facebook has, it’s like a story for this information.  

Eventually you’re going to see a lot of the hubs, and this is another topic we can talk about in the future, this race which I call an arms race between big names like Google, Amazon, Apple, to have their own digital assistance, you’re talking about the HomePod, and you’re talking about something like Google Assistant, and you’re talking about Alexa. You will see that they are in a furious stage of pushing this, this is the hub for the future, IoT devices. What you see now, they’re trying to establish a hub in your house, in your car, in your business where later-on when you go and buy any device, its compatible with Alexa, you just connect it, because one of the obstacles for us as a consumer is the set-up. If I buy a device then I’m going to go through the set-up, but if I’m in the eco-system of Amazon it’s connected automatically, and makes sure that it is really communicating. So, take this image about creating a hub and connecting all devices, Apple for example, and then where is the Facebook…that’s going to come. It’s going to help, seriously, it’s going to help Alexa to understand you, to understand your behavior or the way you act. 

So, this is where we see the data, this is where we see the protection from the government, to make sure that nobody is abusing this. The government has stood behind, because of the technical stuff – and it’s nothing anybody understands, and its growing fast, they need time to absorb this one, and to make sure that we’re not infringing on some of our constitutional rights. 

Yes, no doubt. It’s funny, what’s also topical is, I don’t know if you were watching the HBO series, Silicon Valley? The current episode had a funny vignette about a company making smart refrigerators that had been compromised by the Pied Piper team at the end of the last season, to deliver some decentralized storage. But they do a teardown of the code, and they find out that the company itself has been collecting all its customers conversations. It was one of these situations where they apparently hadn’t been intending to do this but, you have all these devices that are now collecting information and expose people to a lot of vulnerabilities.  

It would be interesting to see how you think the awareness of not just the security vulnerabilities, but as you go back to say about a year and a half ago when we had the Mirai Botnet, and the first wave of these hijacked IoT devices, that essentially became vessels for… well at first I guess they were just gamers who were trying to get advantages over others. But the idea that we have all these devices that we plug into the Internet, but there may not be any inherent security, or the security ends up being an afterthought and we don’t change our passwords, and there isn’t really reliability for the manufacturer, it’s certainly a cost structure.  

I’d love to get your perspective on the security aspect of data, and some of the implications going forward of having so many data sources that track personalized and business as well. 

Security is a big issue, it’s a challenge, and it’s an evolving challenge. If you’re smart, there’s somebody else smarter than you who will outsmart you, and get access to the devices. My belief is that the weakest link in security is the human, and it’s also the strongest link if you think about it. If we train them and if we allocate them, because the user allocation is a big thing. The Mirai attack which happened in 2016, I remember that, it was Friday 26th October, around 500 million devices all over the world was being attacked at the same time, the reason for that one is if not all of them, most of them, they kept their default password and never changed it, and this is something humans can do at this level. Now, if we can take that one piece of the shield and make it strong, which is the allocation of the user to understand that they have to take some responsibility, and change the password in their busy schedule, the same for businesses, the same for factories, that will cover that, that a lot of the hackers they can get in and get into the systems. That is one thing. 

The other thing is, the problem of security created by technology, and it’s going to be solved by technology too, so, we have the option of using new techniques like blockchain for example. Blockchain is a very good example of how you can secure certain transactions, certain parts where you are worried about people or hackers, you don’t want anyone to see that, and you can just use the underlying technology used in bitcoin, use it for IoT security.  

The third part is AI, and how they can use AI to help the users understand the risk, and to help the users make the right decisions. So, when I give a speech about IoT, I always compare IoT for example an eagle; the two wings of the eagle, one of them is AI, the other one is blockchain. So, once you are smart and secure you can fly. That’s the example of it. 

I want to get to those topics in a little bit, because I think that really hits some of the most consequential innovations ahead of us, no doubt. I’d be curious at least in your perspective since you’ve been following this space, how would you characterize any events, people, or companies, let’s say since IoT started, to become a thing? Are there any pivotal developments that have had the most impact on your views, in terms of changing your shaping, how you’ve viewed the potential of what Connected Industry can accomplish? 

There are names, there are big names because for you to deal with IoT as a whole trend, you have to have a lot of money. This month Microsoft announced they are investing five billion dollars in IoT, and part of the investment is going to go to something called fog computing or edge computing, which is an interesting concept, but we can talk about it later. Then you talk about IBM and you talk about Cisco as the first company that created that name, or mentioned that name, and SAP is also big in IoT. So, the big names are there, and Google have their own system. 

That takes me back to we must distinguish between the two types of IoT, the industry of, and the consumer IoT. When you’re talking about the consumer IoT you’re talking about all the different concepts here for the consumers, it is the hubs that we talk about, so that’s like the series etc. When we talk about the industrial part, now you’re talking about a big investment, the big oil and gas companies; I was giving a speech in one of the conferences and that was the key thing for them, because they lose hundreds of millions of dollars because they have no clue when the next pipe, or when the next problem is going to happen in their infrastructure.  

So, for us as a consumer, we can see the big consumer companies, and we can understand it for the industry IoT, you can talk about huge names dealing with it in that field. Now, it’s worth mentioning that between the United States and Europe there are big differences about looking at IoT, and I say this because I gave a speech in Spain, and I’m going to give one in Italy, and one in the UK, the University College of London; they look at IoT in Europe as the industrial, as the IoT, they’re really more on the big project, the smart cities, smart streets. If you move to the United States, we focus more on the consumer part of it, and this is what is visible for so many people, IoT means a sensor that you have for babies, when they start to move, they will alert their parents, smart mirrors and so on. So, the focus here is different between the two continents. 

How does Asia come into play in terms of the way that companies are thinking about harnessing disruptive technologies, compared to the US and Europe? 

I have to be a big critic for Asia, and I have a lot of contacts in Taiwan, in China, in Malaysia, and other countries, not to forget India and the rest. They are willing to take the risk, and this is one thing I have learnt with my friends there, they will jump at the first mention of a new technology. When blockchain came to the picture before the craze of bitcoin, I remember three years ago I had contact from Hong Kong and they wanted me to come and talk about it, nobody even knew what blockchain was, nobody understood what blockchain was, but they are willing to open their mind, understand, and open their wallets for this.  

Look at Alibaba, a huge company, and how they think about expanding and using AI, using blockchain, using IoT, in different aspect. Asia is always at the front when it comes to, ‘Let’s try this’, ‘Let’s try this and see if this is going to work or not’, they are ahead when it comes to a few fields like AI, they’re trying so hard to be the leader in AI. Anybody who gets into AI, and master, and perfect AI will lead the world, because you’re talking about creating something called digital twin, which is you’re creating another seven billion just virtually, because they think like you, they act like you, and they will be under your control. 

The digital twin concept is super-powerful in the ability to anticipate where things are headed. I just want to continue a bit more on the Connected Industry side, before we dive into some of the more cutting-edge technologies. As you’ve seen certain industries start to transform through Connected Industry, it would be interesting to hear where you found the consequential impact, and secondly, what industries in your experience have been most effective in embracing newer technologies, and conversely are there some that are laggards, that may not really appreciate the risks that are coming at them? 

The first thing that comes to my mind is the Fantac, you’re talking about the financial services. The financial services have the money, and they can try different things. The Fantac is ahead of so many, an example of that, when they use the blockchain to count you there. The second one, you’re talking about healthcare, the wearable devices we talk about. If you listen to Tomko when they talk about Apple’s future, they talk about wearables that’s part of monitoring your health, and they talk about education, he was talking this field last week in Chicago. But the main thing is healthcare, because healthcare there’s a lot of money there, and the impact is immediate. If you can save lives, if I can sense that this watch, or this device which is connected, or this jacket I’m wearing which is a smart jacket, can monitor what I’m doing, can monitor and send it to the doctor, and that will predict or save me from a future disease, then that by itself will help propagate, or open the door of every house and save my life, you can use that one. 

So, we’re talking to the financial, talking to the healthcare. Now some of the government, and I’m not talking about any specific state here in the United States, but there are governments outside, Dubai government for example, and in South Africa, in certain parts of the world, and Asia of course definitely, they embrace this kind of destructive technology, they’re open to that, and they’re willing to try it because they want to save money on the process, and make it easy for people to conduct business with them. 

Yes, that’s right. It’s been a real challenge I think if you compare smart cities in some of the more developed countries, we’re particularly familiar with some of the challenges here in the US where there may be a will, but of course… how shall we say it! There are organizational interests, and lots of challenges of coordinating many different constituencies to knit together solutions. Many times, just like developing countries that jumped over wireline communications into wireless, its sometimes not having that legacy back, that legacy of technology ends up being a real advantage, it can be a real burden! 

What are some technology hurdles or even enabling technologies that you think maybe are under-appreciated in the market? We swim in an environment where there are hype cycles, and there’s certainly a lot of new bright shiny objects all the time, but I’d be curious to get your take on where there may be some misperceptions in the market. 

It all goes down to the three elements, that’s security, safety, and privacy, which are the building-blocks for the user or the consumer trust. That’s a problem, because why am I’m not using this device, a smart mirror? I’m not using it because it’s going to collect my data or something like that, and the ignorance about the benefits is really a big obstacle that’s keeping people from trying new things, and the business model, that all goes back to the three lenses we talk about, three filters. I’m going to pay $300 or $400 dollars for a smart watch just to monitor my heartbeat, I mean how is that going to benefit me? So, we’re talking about these kinds of obstacles which are not encouraging people to try it, and the market, the mass production will start when there is an appreciation from the consumers, and the consumer is asking for that. It should not be something that distinguishes me from others, it should be part of the norm. 

Samsung is doing great things, and you mentioned something about refrigerators, the smart fridge and the smart dishwashers, if they’re connected then it’s going to make my life easier. But we go back to very important obstacles, I wrote an article for Social Development magazine which should be published in May, and I listed all these obstacles;  

Number one is standardization. Standardization is a problem here Ed, standardization means you’re asking Google, you’re asking Apple, you’re asking IBM to agree on certain protocols which are, if I have my device, I don’t have to worry which other device I’m going to use to connect with it.  That is killing the market, they want to keep their customers and their ecosystem. Unless there are unprofitable organizations like IEEE will push for that kind of protocol, as they did with the communication TCPIP for the Internet, or the government who require them to have a common protocol which is the last think you want to do, because my personal belief is that regulations cripple growth and innovation, the more regulations we have the slower will be the two actions here. 

The government can say, ‘Okay, we know the famous standards ISO 9000, where you have to have to be certified so you can do business with the government, they might require something like that, and it would be the standard. The other one which is a very important thing is, skills, how many jobs can you fill with somebody who knows about blockchain, or about IoT? How can you define it for them?  

The universities are not giving us enough graduates that will cover the needs in the market. I’m working with the university in creating a blockchain class, I’m going to teach the same thing with IoT, I’m giving another class on IoT, and I have to build it myself, I have to gather all the resources, and I have to convince a trail of committees that this is the future, Purdue University have it, University of Southern California have it, MIT have it, Harvard have it. So, that’s another obstacle we see, when it comes to skills, when it comes to standardization, that’s a big problem there. 

You touched on a topic that I hadn’t thought or hadn’t prepared to ask you about, but since you are working in education, what are some of the challenges? As technology is changing so quickly, education had been designed in a much more static culture, and this ability to create skills, and up-skill and be able to adapt to changing conditions, and changing technologies, it doesn’t really fit easily in the confines of say a traditional four-year degree, or two-year degree. How are you thinking about the changes that we’re going to need, to have the skills that will help match promising students with job opportunities, and allow companies to find the employees, and the collaborators, that will help them realize their visions and move forward? 

That’s an excellent question, and it is a problem as you’ve said. Now, you have to understand that the four year programs, or five years in some schools, they built the foundation first, the general education, you have to know Math, you have to know Physics if you’re an engineer, and then you have to know the basics of for example electrical engineering, you have to know all the courses about digital designs, signal processing. How we contact, how we deal with something like this is, it’s done in multiple tracks, and I’m going to talk about my situation because every professor, every person has their own style.  

Number one is, I bring leaders from the industry to talk to the students in a series of speeches, so next week I’m going to have someone from Intel, before I’ve had someone from Nvidia. Those are really at a high level; 1) They’re hiring, they’re looking for people to hire, 2) they have up-to-date information about what their company is doing and what the market is looking for.  

The second one is, in any university when the school is confused about a topic, or they don’t want to deal with it, they throw it under something called ‘special topics’, and special topics means its up-to-date, we’re not sure that this is something clear to us. So, here in the classes I’m talking about them, which is blockchain and IoT, under special topics. So, the students who are interested in these kinds of topics, because they are aware about the needs in the market, they will take that class. You open it, and this is how you update them. 

The third track is the senior projects. The senior project is not as I tell my students, it’s not a Lego project, where you just get some blocks and you create it, and you’re done. You have to have something that when you sit in front of the recruiter, or you’re doing that kind of interview, you’re proud of it, you tell them, you explain to them exactly what you did, and that’s all in the last year of their study. So, this will minimize or reduce the gap between what we are doing at universities, or academies, and what is the market, because we must keep in touch with the market.  

I have friends in Google, I have friends in Facebook, I have friends in LinkedIn, I talk to them all the time, I invite them, I have some projects with them, or I bring some of my students to work with them, and this is how you keep yourself as an educator, up-to-date, and not buried in editions and books from 2000, 2002, 2007, and you’re talking about old technology. 

Yes, no doubt, and I think that’s one of the reasons why you’ve had initiatives like singularity University tried to emerge and address that gap. It’s been a real challenge for a lot of organizations. You’ve addressed both cultural challenges and structural challenges too in terms of the way these organizations are set-up. But I think what you’re doing again by evangelizing and articulating the greatest promise ahead, I think maybe the best thing we can do is help people learn, and treat learning as a lifelong process, rather than just something that you do for four years, or in-between sleeping through your classes! 

You cover a lot of interesting technologies, and let’s talk about AI a bit because I know you’ve done quite a bit of thinking about why AI and machine learning is so important, and would love to get your perspective on how you see AI being able to impact IoT and connected industry. I know you referred to it essentially as one of the wings on the bird, on the eagle as it were, but would love to get a bit of nuance on how your views have evolved as well. 

AI is not new, and you know this, and I’m old enough to talk about it, in the eighties everyone was talking about AI and how AI was really going to change the world, and then it died. And what happened is, now we have the tools, now we have the band-width, now we have the programming skills that we can use for AI in this case. AI is a big word that covered multiple disciplines, and many times people confuse AI with machine learning, and with deep learning. If you’ll give me a few seconds, then I can explain the difference between the terms here. So, this is how I explain it to anyone, AI is the big term, now inside AI you have two things, the first is machine learning, and inside machine learning you have the deep learning, an example of this is the following; 

For machine learning, if I would like the computer to recognize smiling faces out of 100 pictures, I would scan those pictures, I have an algorithm and I will define that algorithm that the lips go in a certain direction, that’s a smile, if the eyes are going in one direction, that’s a smile. So, the computer will recognize this and give me for example five pictures. That’s a set of pictures of people smiling, and that is machine learning. 

Deep learning is going through the next step which is why they are smiling. This is a real smile, this is some kind of a smirk, this is that somebody has a gun to the head of that person to smile, this is a smile of fear, that is deep learning.  

Now you add the two, the machine learning and the deep learning, that is artificial intelligence. The depth of how good your algorithm in both deep learning and machine learning, this reflects on your artificial intelligence. 

So that’s a simple definition for machine learning, and deep learning. 

Now, we move to artificial intelligence. Artificial intelligence I name it as the catalyst for IoT, there are many areas that AI can help Internet of Things. In one of my articles, I have six of them, and they’re more about the main six areas, they can help in data preparation; if you are a data scientist you understand, and you know by heart that 80 percent of your time is spent on cleaning the data. You have millions of points given to you, millions of data given to you, and you’re trying to clean it by saying there’s no redundancy, there is no point of this one, so the data preparation can be cleaned by using an algorithm with artificial intelligence. 

Then you move to the second one which is data discovery. Now, you have that clean data, or clean set of data, you’re likely to discover the pattern there, repetitions. A simple example of this one, you go to Safeway, and you buy the same thing again and again, your WorldCard will have the single points, so that will be preparing that you will always buy that, at a certain time, in a certain quantity.  

The third part, AI can help IoT in visualization of streaming data. This is important for the business filter, or the business lens, nothing will make a business person happy more than seeing a real-time visualization of the performance of data. For example, the number of the sales, the number of activities, the number of trades, all these things.  

The fourth one is something which had the technical term is something called, Time Serious Accuracy of Data, in English its simple, it’s how can you describe data? Any data in the world can be described using the center of the data, the variation of the data, the time of the data, the outliers, and the distribution of the data. We have to make sure that it is a good data; garbage in, garbage out. If the data itself is wrong then the result will be wrong, it doesn’t matter what kind of AI you are using in the middle. 

The fifth one is productive and advanced analytics, this is good for industrial IoT, this is good for the business. So, I want to be proactive, I want to know what the customer is going to buy so I can have the inventory, this will help me with the supply chain movements, so I can have the trucks on time and I don’t have any kind of shortage, or gap in my inventory. 

The last one is the real-time, or the location. This is the one we are talking about when you go to a place like Macy’s, you suddenly look at your phone and you receive an offer, ‘Today is 10 percent’, because they recognize that you are in that place, and you have an agreement with Macy’s that they will give you 10 percent through that app. So, you can see it is really helping the IoT data to be specific, it’s helping the IoT data analytics when we use AI, because data is the fuel, data is the gold, data is basically the new gold. So, if you don’t use it you lose it. And Facebook is in trouble because of data, it’s not because of anything else. 

Yes, no doubt. Of course, the curation and governance around that data is certainly not a trivial matter in any sense of the imagination. But how do you think more broadly as we look at the application of predictive analytics to essentially, I would say turbo-charge… the way that I’ve always looked at what analytics do is that they can either increase sales, improve operational efficiencies, or minimize risk. Most of the value falls into those three buckets in a very generalized sense. 

But with AI and machine learning, there is this potential to completely disintermediate certain types of processes. I know there’s a lot of talk about AI destroying jobs, but it’s my view that it’s not quite that simple, it’s not necessarily as there is some gain. What happens is, we think about refactoring processes and tasks in certain types of jobs. As we introduce these technologies into connected industry, how do you see some of the downstream implications of applied machine learning, and deep learning of course, and other techniques, into traditional connected industry; how that will change the roles and responsibilities of people who previously had completely manual jobs? 

This is one of the things, and I’m really happy that you talk about this, because this is what I call the myth about AI, that it’s going to destroy jobs. It’s going to replace jobs but it’s going to bring more. Gartner has a study about that and says 2.3 million jobs will be created by 2020, and 1.8 will be lost, so, the net here is positive. The point about it is, the more we are automating stuff, the more we’re using machines, smart machines for this one, people are going to lose their jobs, and this is unfortunate there is no question about this. We have said the same thing about every new technology you’ve interacted with, ‘This technology will replace this’, ‘People are going to lose jobs’. For example, the Internet, ‘Internet will replace the newspaper, so people are not going to read information’, well, the Internet created so many jobs for people on the other side, where there are many other skills that have to be learnt or have to be retrained to get that. 

Now that is exactly the same thing, we talk about with those three lenses, when we talk about society how the government can help this in this process, and how the users or the citizen can help themselves by updating their skills, so they can deal with the new changes. I tell my students, I don’t care what’s your major, industrial engineering, mechanical engineering, chemical engineering, you should know how to code, you should know how to program. I’m telling them, and I have a big poster in my office saying, ‘There are three skills I want you to learn by yourselves, don’t wait for the school; Python, Java, and the database SQL’, because any job you go to, any company you go to, if you have those three skills it’s going to make you very valuable to them. Even if you’re in mechanical, even if you’re in chemical, even if you deal with data, you need to know how to program it, how to deal with it. So, yes, jobs will be lost but more jobs will be created, and now we have to deal with the resistance from the traditional normal manual jobs there. 

Yes, it’s obvious a debate that has people certainly concerned and not without reason, I think there’s quite a bit of fud out there, but I tend to fall into the camp that ultimately new jobs can get created. Who would have thought that 15 years ago there would be such a thing as a social media marketing manager, or…? 

That’s right.  

Which leads us into the last topic I’d like to talk about, which is blockchain, which is certainly near and dear to me. You’ve been doing quite a bit of work around it, and I’d love to get your perspective on the relevance of blockchain, not so much as power for crypto currencies, or ICOs, that’s getting a lot of coverage; but the practical enterprise uses, and how we might see implications of this technology change business processes, and create real value? 

I’ve been asked that question from many business leaders, or business owners here in the Silicon Valley, and my answer is simple, you need security you think about watching, if you need to secure certain parts of your transactions, certain process, then think about blockchain. Blockchain is still evolving, we have some problems that we have to overcome, like scalability, storage, and the biggest problem is skilled talents, we don’t have enough talents that will handle the blockchain. Yesterday one of my students came to my office, she told me she’d received an offer from Intuit one of the biggest companies in the Valley here, they sent her a code and she showed me that code, it is talking about using blockchain in transactions. She said, ‘I’ve never heard of blockchain’, I told her, ‘Okay, you go home, you read, you practice, you’ll find codes on GitHub about blockchain, and then you answer them. Because you’re a programmer, you’re a software engineer, you already have the foundation to understand the different structures of the program. So, what you do is, you have to educate yourself’, and I told her, ‘I don’t want to hear again from you saying that you’ve never heard about blockchain, because that tells me you are really living under a rock in the Silicon Valley, blockchain is everywhere’. 

So, this is just an example. In the hiring process they are looking for people who understand the terminology of blockchain, so for using blockchain in the business process, anybody who will take the initiative now and understand it, or upgrade their skills of their existing engineers – and this is what companies are doing like Google and the other companies, big names here, they look around and find people who have the foundation, and then they train them to be blockchain engineers, and use their skills. Use it in the business and you will be ahead of the curve, that’s what I tell people about it. 

What about the shortcomings of blockchain tech? Clearly there’s a lot of concern that if you’re a solidity developer, CryptoKitties will use up 25 percent of the compute capacity of the network! So, if you have a real hit on your hands this concept of a virtual computer is certainly an issue. Then there are many other blockchains at this point, public and permissioned, as well as some of the graphs or the DAGs and other technologies that are addressing scalability issues, but what do you see are the major shortcomings, and, are there signs that give you confidence that will get these resolved in a reasonable time? 

We need more companies, the companies which are pure blockchain companies. For example, Ethereum, and this is not an endorsement, but I’m talking about somebody who will give me their notes, so I can use it as for example the blockchain platform. I dream of blockchain as a service, that’s one of the concepts I’d like to see soon from big companies like IBM, hopefully Microsoft, and Google if they want to catch up with that trend, where I can use their services like I’m using the AWS now. I know that they have a private for example blockchain, or the public one we talk about which is the bitcoin. I have my own private one with certain known that will verify the transactions, and I’m happy with this, and somebody can build that private blockchain for me, that’s a company that will make a lot of money.  

We have the public one like Ethereum, and Bitcoin and the rest, where I can rent it, I can say, ‘Listen guys, I need 10,000 nodes that can verify my transactions’, and they will provide me this kind of information, we don’t have many. It goes back to the same problem which is, it’s a new technology that many companies want to take the rest of their still unknown, so many factors, and you’re right about it, it’s software. If somebody is writing a software, somebody will hack that software, so this is a new earth shatters water for us, we’re trying to go there and see. But we have seen the benefits of that because of the whole idea of decentralization, the whole idea of being public for the nodes in that blockchain. The secure feature of the hash-function where if you tamper off one, you can tamper one, but you cannot change the mind of another 5,000 nodes to change the values there. 

That gives us hope. So, we’re approaching that, and a lot of companies are working on this and seeing the benefit of this. Government are using it, government are using this one for their business, I’ll give you an example; MIT, the issue to the of degrees or certificates, it’s basically that piece of paper, you take it home with you and you have it on the wall. They have one which is run by blockchain, which is a verified one, so, I have one on my phone, it’s an icon I click or touch it, and I show it to the employer, that’s a verification I have my degree from MIT. That employer is part of a network run by MIT, so they know this icon and that this one is verified, they understand this, they have a certain barcode, they scan it and its verified in MIT, then comes back to say this is a valid degree. 

There are companies that are trying to do the same thing for payments, so they can verify that. I’m talking about payment for example employees, and you can scale this one or apply it to any kind of transactions. The problem with it is scalability, and storage, and processing power, and talents, which is problems we have, every one of them is an opportunity for a bunch of companies to make money, because if you sold the storage, the problem with blockchain, ah, that’s not a great thing, you’re going to be number one in the market. If you sold the processing problem, it’s the same thing. All these things are open markets for us, so if any start-ups are thinking about going somewhere with their ideas, this is something they should at least entertain or study. 

Absolutely. It’s incredible how much opportunity is ahead of us. As we look forward, how do you look at the next five or ten years? I know Connected Industry, AI, and blockchain are all evolving at a rapid rate, but as we look forward, I would ask what would a successful future look like to you? 

Okay! I’m going to give you the funny answer, and the real answer here. I will consider ourselves in the future when I can download my food, the hot chicken, I can download it, I don’t have to worry about driving, that for me is the future, so I can download whatever food I want. I download it, it’s there, its fresh and everything. That’s going to be way in the future. 

But the real answer is, it’s actually in quantum computing. If we can get the factor of quantum computing in all of what we’re talking about here, that’s going to solve a lot of problems, for example the processing and the power used by the blockchain, the information exchange between the different sensors. Quantum computing is a big player, and a lot of big companies know that, we’re talking about IBM, Google, Microsoft, they are spending tons of money on trying to be the first in the market that will deliver a quantum computer. I’m not talking about the one that will fill this office, I’m talking about something I can buy from Best Buy, something I can buy from eBay, and it’s going to run with huge power, save time, saving energy, all these things will be part of that.  

So, when we master, which is the next step of quantum computing, most of the problems we are facing now will be solved and it’s going to make it easier for us to use all the destructive technology we talk about. 

Wow, that’s a fascinating insight. I’ve seen one of the quantum computers out in California that IBM had been running, I know we’ve got some way to go before it gets mainstream, but we’re on the way. I think that’s a terrific insight. 

Ahmed it’s been fantastic walking through this whole range of topics here. One of the questions I always like to ask of guests is, if you could recommend a good book or a friendly resource, anything you’d like to share that we can share in the show notes? 

My advice to everybody who is really concerned or would like to know about the new technology, read all the publications that deal with technology, don’t limit yourself. For example, the Internet has a lot of those resources, subscribe to that, if you have Facebook, subscribe, if you have LinkedIn, subscribe. You will receive a lot of up-to-date information. 

The issue of a book is, whatever book we recommend, within two-hours it’s going to be outdated, and this is what I discovered with the new technology. So, in my classes I don’t give any text books, I tell them it’s going to be PowerPoint articles, that’s what you read, if you really want to be up-to-date, because the book, after you buy it, it’s gone. 

Also, follow certain people on LinkedIn and interact with them, join the groups because that’s going to be very helpful in that case, because you’ll find yourself knowing about not just the knowledge, or information or the articles, you’re going to know about the events. You’re going to know about some of the service of what you do Ed, and I commend you for that, which is exploring and explaining things to people in a different format, sound, video, writing.  

So, that’s my advice for anybody who wants to be up-to-date. 

I think this podcast will help anybody who likes to listen, to learn quite a bit about these new technologies. That’s terrific and we’ll definitely include your LinkedIn link in the show notes, so that people can follow you. 

Again, Ahmed thank you again for sharing your time and your insights. This has really covered an enormous range of topic. 

I’m Ed Maguire, Insights Partner from Momenta Partners, and we thank you for participating in, and being an active listener in our Edge podcasts. Any comments please send them to edge@moment.partners and we’re happy to respond to any questions, suggestions, or input.