My background, I’ve got a degree in Computer Science as well as mathematics. I’ve always been interested in technology, particularly bleeding edge technology, and so I’ve had the opportunity over the last couple of years starting back with getting involved in Big Data back in 2010, to take that and morph that into working with these other technology fronts, including IoT, AI, and Blockchain, and we’ll talk more about those I’m sure, as we move forward. But really that’s kind of been my background.
I’m working with both enterprise customers as well as start-ups around these new technologies, and really leveraging the Cloud as the infrastructure to go out and rapidly prototype or build out these solutions that they’re working on. So, that’s just a quick snapshot on a little bit of my background.
IoT is moving I guess from its childhood to adolescence. Share a little bit of your perspective about how you’ve seen the evolution of Connected Industry, what have we learned as large industrial companies have looked to move from this vision to get to production applications?
I think when we look at IoT and the metamorphosis of it; IoT has been around for a while if you look at in manufacturing plants there’s always been censored devices, everything from the lights in the building, to the heat, analyzing certain equipment, and other things that they measure and control. But the thing that’s really changing I think is looking at this information on a broader scale, on a broader perspective, and also sub-analyzing some of the stuff more locally, so at the Edge. Historically you might have as I’ve mentioned one of these manufacturing plants, they do stuff locally, what they may not be doing is comparing necessarily in the past data that’s happening in that manufacturing plant, let’s say that’s in Indiana, to a plant that may be running in China somewhere, or in India, or some other country.
So now through the creation and the analysis of Big Data, and using data weights, we’re able to store that information and look at it across a broader base, so that’s one point that’s changed. I think also the introduction of AI, so really starting to
So, I think these are some of the changes that we’re seeing, and the most important one and I’ll continue to mention that as we talk, is really leveraging these technologies together, that’s where the real power comes from.
That’s a great point this idea of combinatorial
If you look historically where we started, we had the original analysis which I’ll kind of label as descriptive, where we looked at things, what happened, how often did it happen, so we do some discovery, then we do some analysis of what the actual problem is. Then that elevated into really getting into more of the predictive, where we started to look at trends and modeling. From there we got into more of the prescriptive how can we achieve some of the best outcomes. But when you look at cognitive that really takes you to the next level which asks what is the next best course of action?
So, as an example, one of the clients we worked with had a dermatology application, and that application has infused AI into it specifically. They’re able to go in there in the doctor’s office and look at different treatments for patients and actually come back with a recommendation, and not just a recommendation but a competence level, so it may come that first recommendation is at 90 percent, the second one could be at 60, and the last one at 30, and then the doctor needs to ultimately decide because they’re responsible for the patient’s health, but now they have something they can use.
They may end up choosing the secondary solution because for that particular patient it’s a better fit, but it very quickly analyzes that data. What’s nice is, it’s not just looking at patient data for that particular patient, it was looking at a broader set of patient data, a broader set of documents, so maybe they downloaded information from the Mayo Clinic, or John Hopkins, or other places where you can take the PDFs, analyze that information, and really make sure you’re attacking it from the best types of treatments. But when we look at cognitive I think it’s important to understand that really what cognitive technology is, it’s really processing information more like a human than a computer; it’s understanding natural language, its generating hypothesis based on evidence and learning as it goes. So, these couple of aspect of understanding natural language, leaning as it goes, some machine learning, all these things are critical and cognitive.
But the other aspect is cognitive is really here to augment what we do as humans, and quite frankly this is in line with all technology; when I use my smartphone or my laptop I’m using that to do whatever it is I need to have done, it’s not like the smartphone is running my life, or my laptop is dictating what to do, I’m using these as tools so that’s an important thing to keep in mind.
That’s incredibly powerful technologies, and of
When I look at Blockchain, just to give folks a little bit of a background of what it is, as you’ve already mentioned it’s this concept of a distributed ledger, and in the old system obviously each person would have
You’re not able to change the records, so everything is immutable, it’s that type of object similar in object-oriented or functional programming, an immutable object is really one that’s unchangeable. So, you have that level of safety, and
So, as an example, if I were doing some type of auto-leasing, I could have an individual lease car, and basically eliminate having to go to a dealership and do a bunch of paperwork; all that could be done through smart contracts where people privy to it would be people like the leasing company, potentially the manufacturer because ultimately when you lease a car, it’s got to be built and come from the factory. The leasing company would be involved, there may be a local dealer where you may actually pick up the car depending on how that gets brokered, but you can actually simplify that process and make that fairly complete. I think that we will see this combination of Blockchain and other technologies as we move forward.
When you look at Blockchain there’s a couple of different areas where we see this type of usage, and where it’s going. I should mention that the Blockchain industries to give you a perspective, and these are rough numbers that have come back from analysis and industry reports; the market is supposed to grow to 2.3 billion by 2021, that’s basically a compound growth rate of around 62 percent, so we’re starting to see a lot of build-up in that particular area. So, that’s what you’re going to see as far as the rapid growth, a lot of people are doing innovation now.
So, areas that are broad high level that are probably very immutable to this are everything from food safety, and I’ll talk about that in a moment, to obviously financial-types of transactions, that could be cross-currency payment, it could be bill of lading, it could be retail banking, public records, securities, digital property management, syndication of loans, supply chains. Two examples that I’ll call out, one is one we’ve done with Walmart, they had an issue in China where food was going from the farm to the store, in
Another example is internally in IBM we use from a global financing perspective, IBM global finance provides financing for our business partners as they go out and work with clients downstream. So, to that
But that’s just a quick couple of examples in a little more detail to help you understand what’s happening in that arena.
The use cases in global trade for instance and supply chain, seem to be really compelling to be able to reduce the amount of time that
What are some of the challenges in implementing
A couple of thoughts, there are a lot of companies working with this technology
But it’s also understanding as you get into this, it’s not just understanding the actual programming side, its understanding the business side as well. I think it’s very much similar if we look back to 2010 data science, that area had the same sort of aspect, it wasn’t just about, ‘Oh, I know how to program in R, so
The similar thing here with Blockchain, as you look to implement these things it really is beneficial to understand the business and how you’re implementing the use case and, have some level of that knowledge coupled with understanding the basic concepts of a distributed ledger, along with the programming aspects that we talked about. Some of the people now are doing programming in go as well for Blockchain, which is another alternative language to get involved in. So, I think there’s that learning curve, right now I would say is the first major improvement. The second one is getting the trust level built up if
So, it just takes time, it doesn’t happen overnight, but I think there’s enough endorsement around this technology that has got a real solid future, and
It certainly is extremely promising. I do think in technology,
That’s a great question, we had the same dilemma with Big Data where there were a lot of people trying to use it for everything, and early-on I talked about Big Data, particularly Hadoop and Spark was not a replacement for traditional
The other thing I should make mention of, I think at least from the beginning and maybe over time it will change, this technology is probably more apropos in enterprise-type businesses, or larger business versus the consumer market, I don’t necessarily know if somebody has a start-up that’s focused more on a consumer type of app, and when I say
It’s a great point that you made about big data Bruce, because the idea that Hadoop can handle every sort of analytic job, I think was floating around a few years ago when people were just getting into the technology. But even so, I think we have this incredibly diverse and rich array of techniques and tools for data analysis, but when we start to apply it to connected industry, or what we’ll call IoT, we’re still doing some very basic blocking and tackling.
If we circle back to some industries that are late adopters of Connected Industry, we could say certain types of manufacturing, transportation and connected spaces that are not necessarily working with brand new equipment, but are working with retrofits; how do you approach the challenges of applying the right tools to the problem, as your looking to start to take data from processes, and then start to apply this continuum of analytics, and then ultimately incorporate cognitive? I guess what I’m asking is, what would be a good beginner guide for cognitive or AI technologies in a connected context?
The first thing to look at is to really understand what I call the cognitive IoT marketplace, just to put
The other one that people don’t realize is, there’s a huge opportunity – the biggest area… actually that most people don’t know this, is if you ask them, ‘Where’s the biggest area for IoT today?’ ‘Where’s it being utilized the most?’ Particularly coupled with AI, and that is in the security area, so security surveillance, looking at people hacking into various IP addresses, any type of security, a lot of that’s being analyzed through
As far as getting started in this arena and what’s the best way to do it, I would probably look at a couple of things; you could look at IoT and start to immerse yourself in that, we have a thing called TJBot, it’s a little bot that you can get and put together, and it’s based off raspberry pie technology, it’s very small, it’s made out of cardboard. You could control it through your application that you develop on the Cloud. The little bot can move its arm up and down to wave to you, it can flash certain lights, it can do different things, you can talk to the bot etc. So, it’s a neat little thing to get started. To that end we do have what we call developer patterns, you can Google ‘developer patterns’, it’s out on the developer works website, or IBM code area, where you can go in and look. We have different areas broken out by the focus of the technology, so we have different patterns for Blockchain, for IoT, for AI, and it goes on from there, including things like container technology, other different areas too. So, you can take a look at that to get started.
On the pure AI side, you could look at particular areas depending on what interests you, so maybe its machine learning, maybe its natural language type of work. We even have things where we have services that can
That’s great insight
I think a couple of disconnects, I’ll first talk about one that gets back similar to Blockchain or some of these other technologies, that AI is the answer to everything, it’s going to solve the world’s problems. As we see, as in the evolution of history, one problem gets solved and then there’s another one that gets created that has to be solved, it’s a never-ending set of problems that we’re dealing with. At one point it was polio was a problem, then we had a vaccination for that. Now, believe it or
Number two, you talked about fear of the technology, and that gets into probably a little bit more on the AI robotics side
I think it’s a little bit of a cop-out to say, ‘The machine told me to do ABC and D’, I don’t think that’s really where we want to go, I think the machine is here to help. Now, having said that, there may be cases that are very benign and it’s a very finite set, as an example, I go into a department store and I work with a
Getting to things like medicine or areas like that, that’s a little bit
Yes, it’s funny because I think there’s this debate about whether autonomous systems can have
I just wanted to turn the conversation back to Blockchain and ask you the same question that I’ve asked about AI and Big Data, which is
A couple of things, I would recommend reading up on Blockchain as much as you can, there are a lot of good blogs out there to get you started. I also run a Blockchain area out on LinkedIn, it’s called Blockchain for Business, and I also run one for AI IoT, and I run one for Big Data and analytics as well. So, you can see in there, we talk about things like use cases, about the technology, you can also attend local meet-ups, I highly recommend that because those will go more in-depth on that. If you’re a developer, from there you can take it into going to different workshops that we offer, and then going out to as I mentioned our IBM code site, where you can get involved and download information that you can leverage. We’ve developed code-patterns that have code out on GitHub, that you can download to augment what you’re
So, there’s a lot of different
I would say there’s almost a universe of interesting content, and amazing insights and innovation, really in all of these areas in Connected Industry, in AI and in Blockchain.
Bruce, it’s been really
Some of the resources I talked about or things I just mentioned in the last dialogue, in terms of attending meet-ups, if you go to meetup.com you can go in there, put in your city, your location, and find out what technology meet-ups there are. Definitely go out to the IBM Developer works website, you can Google IBM code, and there there’s a lot of rich resources. But in addition to that, as far as from a book standpoint, what I like to do is to talk about two areas, or two books which I would recommend, they’re not technology-related, so I like to recommend different books to people based on the kind of books that I’ve read or have been interested in, which I think have value or give you a different perspective.
The first one I would talk about is, Leonardo DaVinci by Walter Isaacson. I think it’s really an interesting book because it gives you a perspective on how De Vinci analyzed and looked at things. I think what’s fascinating, and it’s hard to flashback to that time period because in today’s society, at least for most of us, it’s really a very-very
So, I think it’s a constant analyzing how do things work, why do they work, how can I make them better. What we now focus on is innovation, and innovation I don’t think happens in a vacuum, it’s really analyzing and understand other concepts and base information, and that’s how you start to innovate. That would be one book I would recommend.
The other one is just general books on leadership. I think leadership is something we don’t see enough of, I should say good leadership is obviously leaders, whether they’re good or not is another question. So, I tend to read a lot of books like, ‘Extreme Ownership, How US Navy SEALs Lead and Win’ by Jacko Willink, I look at the military because I think the military does understand leadership at its core, and I think if you’ve ever witnessed like did, during Hurricane Andrew in Florida, the military came in and very quickly organized food and housing for people, cleaned up streets, cleared streets, got things in order, there was a lot of
That doesn’t happen without leadership, obviously the other key thread there is supply chain management, so that would be another thing you can learn from that as well, but those are what I would put out there as two books.
That’s great Bruce, those are terrific examples, and I think we can all learn a lot from the examples and the amazing ability to execute from the military side, and also the greatest polymath of all time, DaVinci is always an inspiration to us, and for generations to follow.
It’s been a great conversation Bruce, we’ve covered a lot of ground. I just want to thank you again for taking the time to be a guest on the Momenta Edge Insights Podcast, and I want to thank everybody for listening. Hope to see you again sometime soon Bruce.
Thank you very much
Great point, thanks so much.