In this special edition of Futurum Tech Podcast, we give a longer review of recent edge computing research and then we follow it up talking about recent trips to the Moon. We’re talking blockchain AI. We’re talking about Microsoft passing Apple. And we talk about are we getting too much recognition from our friends at Amazon? This and so much more on Futurum Tech Podcast.
Our Main Dive
Edge Computing: In this special ‘research’ edition we take a deep dive into the world of Edge Computing – what it is, why it’s so important, and how is it enabling the rise of technologies such as IoT and AI, and why it just might upend the market for cloud services!
Our Fast Five
We dig into this week’s interesting and noteworthy news:
- The rise and fall of Bitcoin and crypto currencies
- An update on HPE’s Discover event
- Amazon steps into the Blockchain
- Microsoft matches Apple’s valuation
- The latest on the Commercial Lunar Payload System (to the Moon!)
Marriott, and its generosity in sharing personal information on over 500 million guests over a four-year period.
Crystal Ball: Future-um Predictions and Guesses
Will we fix bias in AI, and will it take regulation to make it happen?
Fred McClimans: Welcome to today’s edition of FTP, the Futurum Tech Podcast. I’m your host today, Fred McClimans, joined, as always, with my colleagues Daniel Newman and Olivier Blanchard. Gentlemen, welcome to today’s edition of the Futurum Tech Podcast.
Daniel Newman: Hey. We’re all here.
Olivier Blanchard: Yeah. It’s hard to say, “Joined, as always, by.” It should be, “Joined, as always, by Olivier and occasionally by Daniel.”
Fred McClimans: Yeah. You are not far flung.
Olivier Blanchard: I want to apologize to everyone out there that this is me and those of you that prefer when I’m not here, because I’m back. But whichever it is you prefer, you’re either getting me because you’re happy about it or you’re getting me and that’s going to maybe ruin it for you. But let’s give it a shot today because I think we do have a great show. Right, Fred?
Fred McClimans: We do, indeed. We do, indeed. So today, we do have a really good show. We’re going to be taking a dive into the world of edge computing and talking about some recent research that we have published and providing some context on that. We’re also going to take a look at what’s going on with Bitcoin, which is taking a beating as of late. We’ll have a quick update on the HPE Discover event. We’ll talk a bit about AWS and their move into blockchain services finally. We’re also going to talk a bit about going back to the Moon, which should be very interesting. We’ll touch briefly on the Apple versus Microsoft valuation issue out there. In our Tech Bites segment, we’ll be taking a look at a data breach at Marriott.
Before we get into the show, I do want to remind everybody that while we will talk about companies that are publicly traded, and we will talk about their stock price and valuations occasionally, and earnings, the Futurum Teach Podcast is for entertainment and informational purposes only. We’re not providing any stock advice and you shouldn’t take anything that we say as a suggestion to invest one way or the other.
So, gentlemen, let’s kind of dig in here. Edge computing. We’ve been working in the edge computing area for quite a while. And, in fact, earlier this year… actually, Olivier, was it end of last year we published the Edge Computing Index? Is that correct?
Olivier Blanchard: Yeah
Fred McClimans: What was the date on that?
Olivier Blanchard: I can’t remember. It was about that.
Daniel Newman: It was May last year it was done.
Olivier Blanchard: Yeah.
Daniel Newman: We did that one with Cisco and with SaaS. So we worked with a partner on the software and hardware side. Kind of had a chance to do it again this year, Fred, but this time, we dove a little deeper.
Fred McClimans: We did. We did, indeed. We have been working on a research report which involves a deep-dive into primary research, taking a look at what the enterprises are actually doing out there, the challenges they’re facing, what they’re trying to achieve. And this was, thankfully, commissioned by Hewlett-Packard Enterprise, HPE, and Intel. The report itself, Edge Computing From the Edge to the Core to the Edge, was designed to take a look at the transformation opportunity that edge computing is presenting within the enterprise and how edge computing can actually hopefully deliver some level of improved business agility and business value.
So, guys, what I’d like to do is just kind of go through the report and some of the key findings, just touch on them briefly, and get some context and some insights from you.
Daniel Newman: Yeah. And maybe, Fred, just something that came to my mind as a quick jump-in since a lot of the time, we talk about broader issues and this time, we’re talking about research, we’re talking a pretty specific topic, is maybe just quickly share with everyone out there kind of how we’re defining the edge.
Because while our listeners have a variety of technical depth and we know there’s a lot of tech people out there, the edge is kind of a little bit of a foggy topic. In fact, sometimes, the edge is called the fog. So do you mind just kind of since you and I wrote this, but you really lead the research, give them a quick just taste of how you are viewing and finding the edge?
Fred McClimans: Yes. Well, defining the edge, it’s one of those things that not everybody can define it, but you know it when you see it. So in this case, just to kind of provide some background and context to the discussion here, at the end of the 20th century, we saw the rise of the internet. And the internet provided the ability to connect all these different islands of data and computing resources and users across this nice common fabric that wasn’t really the internet, it was a lot of smaller networks pulled together by different service providers. But that was the big push there. The ability to connect.
Then in the beginning of the 21st century, we saw the rise of cloud and the opportunity and ability to take all of the compute resources that we previously had within our enterprise and push them out into this flexible fabric that could be used and subscribed to and purchased on demand. You could spin data resources up. You could spin computing resources up. And you could load your applications into the cloud.
But now, in the last six, seven years, what we’ve seen is a big increase in the number of sensors. In particular, internet of things sensors. The devices that are all connected to the internet that are increasingly in everything from our cellphones to our cars to our refrigerators and, most importantly, in the industrial space, in all of our manufacturing and all of our transportation and all of our production systems out there. And gathering all the information from these systems is really important.
Now, when we think about the edge, I kind of take a really simplistic approach to this here. If it’s not in a data center, and I’ll include the cloud as a flexible global data center, if it’s not in a data center, it’s in the edge. Your mobile phone is a great example. Even when you’re in a data center, even when you’re visiting AWS, your mobile phone and the sensors in that are still in the edge. They’re not directly connected into the cloud fabric itself.
Now, for a lot of enterprises, a lot of businesses out there, they kind of will view the edge as anything that’s within their control that is not part of that centralized cloud data repository, the single source of record out here. So all of their production systems, the manufacturing, all of this stuff, everything that’s throwing off all this data, that’s all out there at the edge. It’s hands-on, actually doing stuff on a day-to-day basis.
Now, the challenge, and the rise of edge computing is coming about because while we’re generating a lot more data out at the edge, out in these production systems, in these operational systems that are 24/7. Everything from jet engines to Caterpillar construction equipment. All this data is being generated and the challenge we have is that that data’s been traditionally sent back to the centralized cloud system or to a data center or to a hybrid cloud data center architecture, and processed, and then, hopefully, pushed back out. But what we’re finding is that a lot of data that’s generated at the edge, it really has value at the edge. And if we can process that data, if we can apply some compute resources to it and actually do some data collection, do some data analytics, apply some machine learning, we can get some really fast insights back into those systems so that it’s not a one-way gathering information from all of these remote sensors, but we’re actually helping improve the performance of those sensors. And making better business decisions in a very short, real-time basis.
Daniel Newman: Jumping in. If we ask Fred if it’s raining, he’s actually going to tell you how clouds are formed.
Fred McClimans: Yes.
Daniel Newman: And that’s a perfect analogy from cloud and edge, right? But it was fun, I had a conversation with Dr. Tom Bradicich who’s the head of the intelligent edge business and IoT for manufacturing and industrial for HPE. And he was basically saying, “A really easy way to define it is if it’s not in the data center, it’s at the edge.” And as crazy simple as that actually is, that is a nice, simple way to discuss that. And then just because something’s in edge doesn’t make it intelligent. And we talk about if it doesn’t connect, doesn’t commute, and it can’t be controlled it means it’s not truly an intelligent edge.
So putting that all together, and, Fred, that was a great history, we’re seeing this pendulum swinging from distributed to centralized to distributed back to centralized. And now, we’re swinging hard back to the pendulum of distributed because smart cities, smart grids, retail environment, your Just Walk Out Amazon technology. All that stuff that’s happening requires a lot of the computing to happen very, very close to where the data is being created and that is what the edge is all about.
And so, I think that was a great background and sorry to jump in but I heard you fading. Literally, you were fading.
My son watches the movie Cars all the time and in the third edition of it is that part where Lightning McQueen is getting old and he’s aging and he’s falling behind and my son says, “Queen’s fading. Queen’s fading.” He’s talking about Lightning McQueen as he fades right before he crashes. He ended his career.
Fred McClimans: It’s funny, as soon as you mentioned Cars, that was not the first thing that came to mind. I was thinking more about that 1970s sci-fi flick where the car takes over and terrorizes the motors on the highway.
Daniel Newman: See, it’s a stage of life. I’ve got a little two-year-old, and you’ve got older kids, and you’re a lot older.
So all those things together, you’re thinking 70s movies. I love how we’ve gotten here. So back to the age of terminal-based computing.
Fred McClimans: Yes.
Daniel Newman: Why don’t we quickly give them a couple of the findings of the report so we can get everyone on to the rest of our show?
Fred McClimans: Yeah. There are five areas that we dove into and the first, we really wanted to assess what’s actually taking place with edge computing? What’s the adoption rate look like? The implementation rate out there. How many different enterprises, across a number of industries, are actually actively out there today not just thinking about the edge, but actually deploying the edge? For this particular survey, we went out, and we surveyed 512 executive and tech professionals across nine industries. And what we found was that when it comes to edge computing, and the journey of edge, it’s kind of interesting. 55% of the enterprises that we surveyed, they’re still in that evaluation, planning or perhaps the initial deployment stages with edge computing.
So you’ve got 45% that are solidly in there, and they’re expanding their existing deployment. That’s kind of an interesting takeaway here because that tells us there’s a lot of room to grow in the industry here where you’ve got 55% that are still in those very early stages moving forward. But the other interesting thing that we saw here with edge computing was that edge itself is being driven by the processes and applications that are out there at the edge of the network. It’s an operational function. And that’s very different than the way a lot of different technologies are implemented today in enterprises where it’s IT that takes that dominant position, finds the technology, and pushes it out to the masses. So a little bit different here.
And, Olivier, I’m curious, with the research that you did previously Edge Computing Index, how does that fit into what we’re seeing here in this particular situation?
Olivier Blanchard: Fred, I’m glad you ask because I was just thinking about that. So it’s really interesting. So let me take a step back a little bit and put this in the context of digital transformation as a whole. So one of the big findings in the last two years of research that we’ve done on digital transformation and technology adoption as a whole is that the rate of adoption, or the pace of adoption rather, varies from company to company. And we’ve identified the spectrum of adoption where you have digital leaders who are very far ahead of the curve.
We have kind of a softer middle that’s following this rapid adoption, it’s just it’s a cluster of companies that are either slow to adopt or cautious or adopting different technologies at different rates. But they are keeping up with technology disruption and advancing in their digital transformation journey. And then towards the low end of the scale, you have companies that are either reluctant or have more difficulty than others in adopting technology. Or not just laggards, but actively rejecting the notion that they need to adapt.
And so you have these leaders, these adaptive companies, and then you have a bottom 25% or so, or 20% of companies that are really struggling. And typically, the more mature the technology, the more the spectrum leans more heavily towards heavy adoption and leadership in the market. Edge is one of those concepts that is rather more of a latecomer than cloud and mobile, for instance, which are typically much more mature. And so we haven’t really focused on edge in our research until recently, right? Two years ago, we weren’t really talking about it or it wasn’t really on our radar as a top technological investment priority. But what I find here is that generally, you have kind of… if you want to really simplify the scale, you have 25% of companies that are leaders, 50% of companies, so a very large middle, that’s somewhere in between, and then you have 25% that’s in the lower quadrant.
Edge, which is a relative new concept according to this data, is much farther along than I expected this quickly. So the way that you presented the data a few minutes ago, saying that there’s still a lot of room for growth, is absolutely correct. But when I look at the pie chart in the report that focuses on this, I see that all right, so 13% of companies are currently evaluating, right? So that would put them kind of in the laggard quadrant maybe or at least for edge. 19%, so just shy of 20, are planning deployment. So they’re not quite there yet. But then you have 25% of companies that are already in an initial phase of deployment and then a whopping 45%, which is the biggest of the four categories, already expanding deployment. So that’s, if my math is correct, that’s almost 70% of companies that are already working on edge investments and edge deployments. And two-thirds of those are already kind of in their second and third phases of edge investments.
That is not entirely surprising to me but it indicates to me that edge is much bigger than I thought it was. That also, companies, IT departments, and executives are much more aware of the value of edge than they were two years ago. And it’s a really good sign. I think this is the biggest change in 24 months for any technology investment that I’ve seen of any of the technologies that we follow. It’s extraordinary, I think.
Fred McClimans: Yeah. It’s interesting as well because when we talk about the adoption rate here, this is really, to a large extent, being driven by the just tremendous increase in IoT devices that are out there. Which also, to a large extent, includes all of these industrial sensors that have been out there for decades in systems, and those are now being upgraded, those are now being brought online and networked. The amount of data that we generate is huge out there. And finding a way to effectively process that is really significant. I mean, what was it? A terabyte of data comes off a jet engine in the course of a normal flight. Just something like that just kind of indicates just how much room there is.
But it is interesting because we did take a look at the enterprise in the survey base from two different perspectives. We grouped enterprises into industrial sectors and information sectors. In the industrial area, that’s primarily your industrials in manufacturing, energy and utilities, healthcare and pharma, retail consumer products, high-tech transportation, and then the public sector. On the information side, we have banking and finance, travel and hospitality, and media and publishing. Organizations that tend to be more information-focused, less physical hardware infrastructure for that. And what we did find there was that when it comes to the adoption rates here, it turns out that the information organizations are actually a little bit ahead. And perhaps that’s because they don’t have that legacy sensor hardware out there they’d need to kind of pull in play here.
I want to move onto the second area of research here. And, Dan, I’m going to throw this one over to you here in a second. When we looked at the classic model that we see in so many other technologies, IT-driven out here, we did not see that in edge computing. In fact, it turns out that it’s an operational function and operations, a line of business or an operational IT group or an operational technology team, that’s primarily the way edge computing is being injected into the systems. But interestingly, once it’s in, you start to see a little bit more responsibility on the part of IT to manage that. And, in fact, some of the stats that we had on that were fairly significant where the… oh, I think it was 72% of the initial implementation drivers within an enterprise come from an operational side, or the OT, operational technology side and not IT. But when you look at management, 69% of the time, centralized IT management or corporate IT ends up managing those systems.
Dan, I’d love to get your take on what that means for most enterprises.
Daniel Newman: Yeah. I think what you are basically showing there, Fred, is that the drivers of new technology adoption is coming more from the business use cases now. And we’re seeing that holistically. We talk a lot about shadow IT. How did Slack end up in the enterprise? How did these various external applications find their way, these gray IT? Edge is being driven by business units identifying problems and it’s much to the way OT always existed.
So when you look at that demark between OT and IT, OT was doing this and kind of doing the edge via smart sensors on pumps and manufacturing lines for a long time working with OT companies. PTC and Siemens and these companies. And the thing is, they had a certain way into this business and the reason hasn’t been as involved there is because they weren’t needed. The data stated in their own little data lakes. It was managed and locally taken care of. Well now, all this has to work together because of the amount of data. That jet engine isn’t just saying, “Yes,” and, “No,” any more. It’s giving lots and lots of data that requires tremendous amount of infrastructure which therefore requires IT to be able to support it.
And there’s coordination, right? Because this research wasn’t really just about edge. It was edge to cloud. So then you had that whole thing about how the edge and the cloud need to be orchestrated together. Well, if data’s being transported between the two and it’s masses of data, now it starts to matter which public cloud you’re using, which hybrid environments you’re using, what composable environments and software solutions that you have to support this. Your storage. Your memory. Your pipe. How fast can data go in between? Which workloads do we need to distribute to the edge versus workloads that can be handled if the data is sent to the cloud first? What’s real-time versus what has more capacity for latency?
As you start to put all these pieces together, you start to see well, why is the edge proliferating? Well, it’s massive data and it’s the fact that the BU’s themselves are the ones that know the problems. IT doesn’t really know the problems that the edge solved. The BU’s know the problems. So then this kind of all circles back to IT in partnership, in concert with the business units that are trying to identify a problem, they realize they have the opportunity to collect that data, analyze it, process it, and utilize it, and now the two have to work together. Has to start in the businesses and has to eventually be managed by IT.
And, God, I would love to talk about all the findings in this report hopefully. But we’re going to put it inside of the show notes so that people can download this report because if we try to go through the whole thing, this will be a seven-hour long podcast.
Fred McClimans: It will. It will. It’ll be a great one, but it’ll be a long one. So moving along here, just kind of touching on some of the key findings that we have here. And, Dan, you were talking about that aspect of edge really addressing specific operational needs in there but it turns out that edge computing itself isn’t just a solution to an issue or a problem, but it’s also an enabler of other technologies. So once you have the ability to process that data, there’s so much more that you can do. So many insights. So many different ways that you can rethink your business process.
And, in fact, it turns out that when we ask our enterprise clients, how important is edge computing to your digital transformation, to your IoT or your Industry 4.0 strategies? 56% came back and said it’s extremely important. In fact, they said it’s a focal point of those strategies. Another 37% said it was very important and it drives or helps drive that strategy. And surprisingly, I guess, maybe not surprisingly, there was 1% out that there simply said nah, it’s not important. It’s not part of our strategy at all. We’re not thinking about it. And you know who’s going to be falling by the wayside relatively quickly in those particular industries there.
But that was interesting that we found that it really is… edge computing is an enabler of additional transformational initiatives. And I think some of that comes down to the applications that are being used out there today or that are being targeted by edge computing. I mean, right now, not unexpectedly, it’s about data acquisition and pre-processing. That was the biggest initiative that people are targeting with edge computing. Security and monitoring, number two. In fact, when we asked people, “Do you believe that edge computing can increase your security profile across the board,” they said, “Absolutely.” So that was very interesting.
Today, some of the more advanced or emerging applications, more technical, AI and machine learning, video analytics, augmented virtual reality, they’re kind of at the bottom of the target list. But they are positioned to increase coming up moving forward here. So that’s kind of interesting there. Right now, a lot of edge computing is blocking, tackling basic business requirements. I think we’ll get to the fun stuff over the next couple years here.
Guys, there are a number of interesting findings and stats that we have in the research. We could spend about seven hours just kind of drilling all through it. There are a number of key things that are really interesting. Security, highly-valued but a lot of enterprises aren’t set up to actually handle that security. We see that shift in IT not necessarily initiating it, but being responsible for managing it. And there’s some interesting findings that we have here on budgets and collaboration between the OT and IT teams and things that we think are going to be very necessary to keep the momentum of edge computing going and, actually, have it continue to drive value for our clients.
What I’d like to say is there are three predictions that we do make. I do want to touch on those quickly and then we will be including a link in the show notes for the podcast here. Our listeners, they can download a copy of the research for free. If they have any questions, they can reach out to us and we’re always glad to get feedback and input on these things.
So three big predictions though, Dan, that we came out with in the report here. The first, edge computing growth. Assuming a 25% CAGR, or compounded annual growth rate, for data growth which is in line with IoT devices out there, we’re looking at a 1.56 increase in edge computing implementations by 2020 alone. And that’s a pretty significant growth trajectory here.
The second thing that we’re seeing is that within the next three to five years, we anticipate that more than 25% of all new IoT devices will feature some level of compute capability and really start to cross that boundary or herald the merger of IoT and edge computing technologies into one system.
And then the third thing that we’re looking at here, within the next five years, we really do expect that the volume of data that’s initially processed at the edge will be so significant that it will actually reshape the value proposition of cloud computing. Because cloud computing’s proposition is all about centralized resources and what we’re seeing here is that there’s a lot more value in keeping some of those data resources distributed and processed at the edge.
So with that, gentlemen, I’m going to kick off in here into our Fast Five. Olivier, you’ve got some interesting stuff going on this week with Bitcoin and crypto. What’s going on there?
Olivier Blanchard: I do. So I don’t want to beat up on Bitcoin. Bitcoin’s not having a very good year. But generally, what I want to say about Bitcoin and cryptocurrency as general is that it’s still a little bit of the Wild West out there. I caught an article on CNBC that kind of outlined the value of Bitcoin and just kind of created this hypothetical model where if you invested $1,000 in Bitcoin in a particular year, what your rate of return would be today.
So if you’d invested $1,000 in Bitcoin in 2011, you would now be looking at over $4 million in potential value. If you invested in Bitcoin in 2014, that $1,000 would now be worth about $5,000. If you invested in Bitcoin last year or any time in 2018, the average value of your $1,000 investment would now be in the red at $318. The value of Bitcoin relative to how early you invested in it keeps dropping. It’s not a steady decline, but it’s a troublesome one and it just highlights the fact to me, at least, and probably to a number of other analysts in various industries that Bitcoin and cryptocurrencies, while having a pretty tremendous potential for being disruptive and being useful, are still not anywhere near stable or properly regulated enough to be a viable, safe investment.
And to highlight that, I ran into this story earlier today about the CEO of a cryptocurrency platform, AriseBank, who was arrested by federal authorities for securities fraud. For essentially promising to investors that his company was FDIC-insured or would be and would be able to provide services that it was not authorized to provide.
And so I just want to really caution our listeners that while cryptocurrencies are great and we can have a separate discussion about the blockchain and blockchain technologies, to be very, very careful when they’re discussing cryptos, either personally as investments, or as a tool or a lever or a technology investment for their business. Get a little bit more… I guess it’s not so much get more educated in cryptocurrencies, but take a giant step back and really consider the risks with cryptocurrencies currently before you invest too many resources in them.
And I know that banks and other companies are looking pretty heavily into them and planning some deployments in the next 12 months. I would caution to maybe hold off on those a little bit.
Fred McClimans: Yeah. While Bitcoin and other cryptocurrencies can be disruptive, they are also so easily disrupted. And it doesn’t help that one of the great value propositions of Bitcoin is that it’s a decentralized system. But that decentralized system also means that there are different camps out there, different approaches, and they don’t always agree. And, in fact, in the last week, we saw a couple of major camps disagree and that created a lot of confusion there. So good advice on Bitcoin and cryptocurrencies.
Dan, you just spent the earlier part of this week at HPE Discover.
Daniel Newman: Yeah. I just got back from Madrid. You can probably hear the jet lag in my voice but it was a good event. I just thought I’d give a couple of interesting points. I think HPE’s been kind of a somewhat repressed company in the market. I think while they’ve been doing good things, they’ve just kind of steadily been chugging along and not necessarily getting the same notoriety as some of the other tech giants. Sister company, HPI, has gotten a little more because they’re the consumer, the sexier side and HPE’s the enterprise side.
And they’re actually doing a lot of really good things and I walked away with four sort of big takeaways from the even that I can try to surmise in just a few seconds here. But they’ve got a new composable cloud offering that it really does favor the hybrid IT space and the hybrid cloud space and bringing together public on-premises and making it easy for companies to handle. And then they’ve got a strong line of services to support any gaps that companies have. So that was one big takeaway.
Another really interesting takeaway was related to their edge IoT business with Aruba and the Intelligent Edge business that we talked a little bit more about in the report earlier. They have a really robust offering that’s really well prepared for the market and where things are going. And I think sometimes people forget Aruba is part of HPE, but Aruba’s got a really interesting offering related to the enterprise and workplace of the future.
We did just talk about the blockchain and that’s another area that I was pretty impressed with. They’ve got some interesting blockchain services for both on-premises and cloud that I think we’re going to start to hear quite a bit more about in the next few months. We hear a lot about IBM in the blockchain and IBM’s being doing a good job of marketing it and I’m fond of what they’re doing, but HPE’s also got some really interesting things and I think we’re going to see them there.
And Pointnext, which is HPE’s Enterprise Tech Services Group, has one of the most complete offerings for being able to take area storage. High-performance computing. Mainframe. Cloud. Hybrid cloud and all these things. And actually make those connections either through channel partner programs through the integrators or directly to market to be able to make these new technologies quickly digestible and deployable. And, really, seeing these head-on and having a chance to talk to these people made me realize that I think HPE’s a more dynamic competitor and they’re more prepared to help support the growth of all these various computing areas than people in the market are probably aware.
Fred McClimans: Excellent. And I would agree. What I’ve seen from HPE, yeah, they’re a little less repressed than they have been in the past. So but sticking with the blockchain theme there, my Fast Five today is AWS finally and formally entering the blockchain as a service market. They have two services or two components to this here. They have a managed blockchain service and they also announced the Quantum Ledger Database, or QLDB. And they both support Ethereum and the Hyperledger Fabric, Hyperledger being driven, to an extent, by IBM and their approach there.
What’s interesting in this here is putting aside the notion that I think services are really where the big value in blockchain is going to be, I do not expect many people to struggle through the implementations themselves or try to build something for their enterprise. There are just too many issues about public and private blockchains and performance and whatnot. Services are the way to go. So Amazon being here, that’s great.
But what was really interesting was AWS CEO, Andy Jassy, he explained their service offering by starting off with a very interesting line, “We don’t have a blockchain service or have not had one in the past because we just didn’t see any need. We didn’t know what it would be used for.” And it turns out what they’ve done is they spent the last year going out, and they have met with and spoken to every enterprise that they could get their hands on. And at the end of that process, they realized there is enough interest, there are enough applications, there are enough use cases that are proven and moving forward. Now’s the time.
So I think this is a big step for the industry. AWS has a lot of clout and them stepping up to the plate, I think, did a lot to legitimize blockchain as a service. And with that, Oliver, we’re going to back to you and you’re going to take to the Moon.
Olivier Blanchard: To the final. Okay, yeah. So space is not the final frontier as it turns out. It’s just the next frontier.
So in case you missed it, I don’t want to move too fast over the fact that we did land a vehicle on Mars this week, again, successfully. And it’s already sent images back, which is nothing trivial. And last week, as you recall, I think it was last week, we talked about the new network or the upcoming network of satellites, 12,000 satellites, that will create a net of wireless network capabilities for the entire planet. So we’re sending wireless to the entire planet through satellite technology. We’re putting landers on Mars. And the next step is we are going back to the Moon, which is super exciting because the Moon’s been sitting there for a while without a whole lot of interference from us.
So this week, NASA announced that nine companies, including Lockheed Martin, but also smaller, more specialized companies like Moon Express, I love the name, Deep Space Systems, Draper, Firefly Aerospace, and OrbitBeyond were selected to participate in NASA’s newly-minted commercial, I’m sorry, commercial lunar payload services, or CLPS. And that’s fairly soon, as early as 2019. So next year, some of these companies will be sending automated robotic landers on the Moon. So we’re not sending people back yet. No astronauts. No moonwalkers. But we are sending robots and landers to the Moon as a first phase for those types of human-led missions. So that’s very exciting, I think. We’re colonizing the solar system and it’s actually happening.
Fred McClimans: One moon at a time. No, actually, I agree. I think that’s pretty significant there. And people tend to forget, there are a lot of natural resources on the Moon.
Olivier Blanchard: Yeah. Yeah.
Fred McClimans: And, of course, while that’s good, it also gives one a little bit of concern perhaps about the future of what we actually do on the Moon. But putting the Moon behind us, Dan, when we talk about moonshots, we talk about companies that go into orbit. Apple recently went into Orbit. It was the first trillion dollar company. But something happened along the way. What’s going on there?
Daniel Newman: Well, their Mars rover took a shot back to the Moon and now it’s taking a shot back to Earth as Apple’s fall from grace. And, I guess, I find a little joy in it. Anyone that’s listening to me long enough knows I’m first in line to give criticism. But I think it’s more of a compliment to Satya Nadella and Microsoft who we’ve been quite bullish on. And I believe in our show covering the trillion dollar valuation, myself and Oliver and, probably to a lesser extent, you all agreed that Microsoft had a really strong chance of being the next trillion dollar company. Not necessarily surpassing Apple at any point. But this week, that flipped. And for a moment in time on Monday, Microsoft by about $33 million became the highest market cap company on the planet.
Throughout the course of the week, while people thought that was just going to be a passing moment, Microsoft actually continued to gain. So as of this last 10 minutes when I looked at the ticket, $845 billion is the market cap for Microsoft which just a few years ago was considered the dinosaur of tech before Satya Nadella took on. And with Apple on just an absolute rocket ship of ascent, they fell to 842. So you’re seeing a $3 billion difference in valuation and a lot of it comes down the leadership, the bets Satya has made, their continued partnerships, they’re all-in on cloud. And the fact that they really do have products and services for the enterprise, which is still a big area of spending. So kudos to Microsoft. I think Apple was overvalued anyway so I think it’s more reasonable. I certainly believe Apple could come back and surpass them again, and they most likely will. But Microsoft is a great company doing great things and it hasn’t been talked about as much as it probably should be.
And so this moment in time is something to really keep our eyes on and say, “Hey. Maybe they’re doing a lot of the right things.” And even in consumer hardware, Microsoft has come a long, long way and they have a shot to be on top for a long time if they keep doing things the way they’re doing.
Fred McClimans: Yeah. They do, indeed. And not to take anything away from Steve Ballmer but, yeah, the company is a different company than it was a decade ago, certainly. And by the way-
Daniel Newman: I’ll take that away from him. He was awful. I mean, he was great for the shareholders but in terms of innovation.
Olivier Blanchard: I wasn’t a fan either. Yeah. This is much better.
Fred McClimans: Yeah. I’m being polite here. So, hey, and by the way, we can’t forget Amazon, which is sitting there at a market cap of $825 billion. And we’ll talk about Amazon here in a moment here, but that wraps our Fast Five. So our Tech Bites segment today. Those things in technology that simply bite. This week it is Marriott. Marriott Hotels that, I don’t know of an easy way to put this, but they took Yahoo’s beer and then some with a data breach. 500 million guests had their records purloined, hacked by somebody that they don’t know who it is yet but they believe that they’ve actually been in Marriott’s system or in the Starwood Preferred Guest database since 2014.
And the amazing thing here is when you look at what they believe is stolen, so you have a half-billion people with their information stolen, for 327 million of those guests, the stolen information includes some combination of their name. Mailing address. Phone number. Email address. Their Starwood Preferred Guest account. Their date-of-birth. Gender. Arrival and departure dates. Reservation dates. Communication preference. Oh, and, by the way, passport numbers.
Olivier Blanchard: That’s stupid.
Fred McClimans: So the more we see about this, the uglier it gets. And I have a feeling that this particular story is going to get a lot uglier here as we move forward. And it puts a really interesting question out there. When you’re looking at brands, when you’re looking at companies, whether it’s from a consumption perspective or an investment perspective or, “Hey. I want to use this company’s technology,” we may think they’re totally safe. And they may be saying all the right things. But data security, data privacy, it’s a losing proposition in many situations. And I think three, four years from now, we’ll find out that, yeah, probably just about everybody else, like the Marriott, has also had some type of a breach that they didn’t realize at the time.
Dan, I know… in fact, Dan and Olivier both, you guys have been big advocates of privacy rights. Dan, do you think this damages Marriott? Do people look at Marriott differently moving forward? Or do they just simply say, “Yeah, it happens to everybody now?”
Daniel Newman: Well, I think the answer’s yes and no. I think there’s a short-term definite dip that’ll take place and Marriott will get some serious negative publicity. I think it’s also a shot to the bowel for its consumers because it’s a reminder of our own exposure. The risk that we’re at. The requirements that we need to do better to take care of ourselves. But it’s really disappointing because even when we’re doing a great job of ourselves managing our passwords and such, the companies that we entrust our stuff with, the companies that we use frequently, and if you’re a frequent traveler that uses one hotel or one airline, you give them a lot of data. Because when you’re booking all the time, it just makes life so much easier.
But this is an argument for the blockchain. This is an argument for automation. This is an argument that we need other ways for data to be accessible and to improve customer experience without necessarily having to give all our data. We need more encryption requirements. We need more oversight. As to cyber policies, we need greater investment in cybersecurity. I think a lot of research I’ve read and a lot of the reports I’ve read have primarily shown that it’s still a reactive area. Few companies are truly doing proactive. Most companies look at breaches as an inevitable and they budget. And, actually, the way it’s often budgeted is what is the cost of the breach versus how much do they need to spend to prevent these breaches? And they will allow a breach up to the point where the economics are foreseen as more positive to let the breach happen than to spend the money to properly secure your network.
Fred McClimans: Yeah. That’s one of the ugly sides of cyber-insurance that’s out there. I see a number of enterprises increasingly relying upon insurance as a way to kind of soften the blow. And it becomes almost an actuarial table.
Here’s the data we have. Here’s the potential risk. Here’s the insurance coverage. What’s the calculation look like. But at least in this case, while the breach began, they believe, back in 2014, Marriott seems to be, at least right now, doing all the proactive things here. Olivier, what do you think the chances are that this devolves into another Yahoo situation where every two weeks, more details start making their way out that just make the breach worse and worse?
Olivier Blanchard: Yeah. I think we’re sort of getting callous to this. It used to be huge news, now it’s not so much. So first of all, there’s other news that takes up most of the news attention that we already get. So it kind of obscures it and it falls behind. But also, it’s happened so many times to so many different companies that we just kind of lose track.
I think my reaction to the story, its kind of illustrates maybe a little bit how we prioritize our reaction to data breaches. The fact that our names and phone numbers and emails have been hacked, it’s not that shocking to us anymore. At this point, we kind of almost expect that all of this stuff is out there already. What shocked me is when you mentioned passport numbers, for instance, because there’s some security issues involved with that. And passport numbers can also be part of a more secure way of identifying people or confirming IDs.
It’s kind of the nature of the type of information that gets breached and hacked, not so much that it did. So it’s just it’s one more, there’ll be 20 more by the end of the year. Some big. Some small. Everything that Dan said, and his analysis, I think, is correct, I think at first, it’ll make you think twice about pushing that button and choosing Marriott as a place to stay. But at the same time, people are invested in it. They might have the best rates. They might have the best availability. The best location. Long-term past the next three weeks, I don’t think it matters.
Fred McClimans: Right. Well, it’s interesting because there’s an aspect here perhaps of the inevitable quest for regulation and actual regulation with teeth in it that maybe makes that equation a little bit more in favor of companies actually not just reactively trying to secure information, but making those decisions up front that the technologies that they use. The way they use the technologies. The business decisions they make start to be made more from a… or, I guess, the way to say it is less from a we’ve built it, now how do we secure it? And more from a we can do this, but can we secure it? And if we can’t, let’s not do it perspective. But I definitely think the trend here is moving towards increased regulation of some type. And, hey, maybe if we’re lucky we’ll get a GDPR out of it.
Although, I think that’s unlikely at this point.
But that’s a good lead-in to our Crystal Ball segment where we are going to put our Carnac the Magnificent hats on and take a cut at something that also potentially involves regulation. So Crystal Ball, guys, this week, Amazon, we talked about them earlier, Amazon has been served with a letter from seven House Democrats requesting details about Amazon’s Rekognition, facial recognition platform. That’s Rekognition with a K. Now, the interesting thing here is Rekognition is a facial recognition app that is being pushed by Amazon to law enforcement. And there is a lot of issues that people have just around that in general. Should we be putting facial recognition onto cameras that are pretty much ubiquitous at this point? Are there issues of First Amendment rights? Are there privacy issues out there?
But in this particular case, it turns out that they believe the facial recognition software, based on an initial pilot, might have a bit of racial bias injected into the system. And, Olivier, this is something that you have and I have talked about in the past here. Bias in AI. Bias in technologies.
Olivier Blanchard: We’re writing a book about that right now, in fact.
Fred McClimans: Yes. It’s an increasing issue for us here. So, gentlemen, just your take on this. If you look out in three to five years, do you believe that we will have fixed these bias issues in technology so that we don’t have these particular issues here? And if you do think we’ve fixed it, do you believe there’s regulation involved in that? So, Olivier?
Olivier Blanchard: This could be a topic for the main topic for our show. It’s a big enough topic. My short answer is going to be no. No. It’s not going to be fixed. No. Regulation will not be in place. I think that the problem of AI bias, or the challenge rather of AI bias and correcting it is not something that we’re going to be able to solve even in the next decade. I think that the best way to address it right now is to understand that bias always exists in any algorithm and to try to steer biases towards the outcomes that we want. And so it’s not so much the having the ability or mandating the ability to eliminate bias, racial bias, economic bias, ethnic bias, whatever type of bias from an AI algorithm and computer vision, for instance, which may include facial recognition. The impetus should be on trying to identify those biases and mitigate them any way that we can. And that may be to artificially inject these systems with counter-biases that are worked into the algorithms and into the technology that end up equalizing the equation a little bit.
The other aspect of this is it demonstrates the extent to which humans are still very much necessary in the process to validate decisions and analysis from AIs and AI-related technologies. If anything should be stressed about that, it’s that humans ultimately have to make the decisions. We cannot leave the decisions to machines. No matter how intelligent. No matter how advanced. Not yet.
Fred McClimans: I agree. Dan, your take on this?
Daniel Newman: Yeah. The question really is just because we can doesn’t mean we should. And with the facial recognition technology, we now can and the law enforcement who have a difficult task at hand of trying to identify criminals, trying to identify criminal activity, trying to solve the crimes, they’re looking for every leg up they have.
Because, obviously, just like cyber criminals, they have all the advantages and it’s always chasing. So they want to be able to utilize it. And there’s a lot of potential value in the data.
The problem is it is a complete invasion of privacy and society has this challenge right now that we have to understand we’re in a surveillance economy. We are constantly being surveilled. Everywhere we are. Everything we do. There’s video. There’s people watching us. There’s people that can see us. There’s no such thing as privacy. It’s like what happens in Vegas ends up on the internet. Well, that’s everything now. Everything you do. If you break a rule, you may not get caught by law enforcement today but suddenly, what happens is it becomes like Minority Report. Pre-cog. It’s like they see what you’re doing and they’re assuming what you’re going to do and in the attempt to try to stop you before you do it, they’re going to try to stop you. But actually haven’t done anything.
So now, we’re saying that the system is able to measure human intention more accurately than the human itself.
Could the person be heading to the bank to rob it and on the way there, they get a crisis of consciousness or they win the lottery and they change their mind and they turn around and they’re going to walk away, but instead, they get arrested on the walk just based on a series of recognition of behavior of activities? So the problem is we have no way to police it. And when the police want to use this data, there needs to be a number of checks and balances in place that before they’re able to utilize this data as part of their processing the due process, they have to have a number of checks to make sure that they used it properly, collected it properly, followed the rules of the due process. Because otherwise, what’s going to happen is there’s going to be no such semblance of privacy left.
Problem is as well, what I just suggested is a really nice idea. Deep down, I’m very, very skeptical that it will ever take place because I just think all semblance of privacy is more or less gone. So long as you create data, you’re vulnerable and not to knock on Facebook, but it’s kind of like the thing with people’s random messages showing back up five months, two years, four years later. Which is a whole another Tech Bites topic. If only Facebook didn’t give us the best topic every week for what bites in technology.
Fred McClimans: Well, it’s a battle between Zuckerberg and Musk.
Daniel Newman: Yeah. It’s like, “Hey. Hold my beer.” Right? But the short finale on this topic is that even when we think we’ve erased data from our past or you’ve gotten away with doing something that maybe isn’t even illegal, but just unethical, you don’t know when the data’s going to come back. So nowadays, we are basically forced to live like saints or know that at any given time, our private decisions of imperfection could come back and haunt us a week, a month, a decade afterwards because we have no control over how this data is created, managed, policed, and utilized.
Olivier Blanchard: And I just want to point out really quick that from a legislative standpoint, legislators are always several years behind the technology. They cannot keep up. And so we have technologies like what Congress is suddenly interested in with Amazon, facial recognition, and they want to hold these emergency hearings that are kind of contentious. When what they probably should be doing is just finding out what the technology is and what it can do without necessarily treating it like some kind of emergency investigation. If we can get better at aligning the technology advancements that could help us or threaten us, whichever way we use them, with the legislator’s ability to process, understand, and contextualize technology, I think that we’ll find a more effective way of addressing it.
Fred McClimans: Yeah. Well, I think all the technology, all the data that is causing a lot of these issues here and the lack of privacy, that can also be used to help us collaborate.
Olivier Blanchard: Absolutely.
Fred McClimans: And communicate and share and be more open. I don’t see an easy resolution for this type of issue here. I mean, removing bias from technology systems. As long as there’s bias in the developers, and that doesn’t mean it’s bad bias, it’s just sometimes it’s a lack of context or a lack of available information in other areas or a lack of diversity. Or just it happens.
Olivier Blanchard: It’s a work in progress.
Fred McClimans: And we need to find a way to move past that. And it’s a challenge with facial recognition and even the technology that we have out there, every time we automate something, every time we reduce an action to data and put it into a system and let that be interpreted in some way, that also drives the actions that we take. And one unfortunate side effect of some of the great advances in technology is that we’re losing agency. We’re losing free will. And Dan, in the case that you pointed out with Minority Report, to an extent, we’re losing that free will proactively. People saying, “Well, yes, this is going to happen here.” And that’s a Minority Report that I suffered through Tom Cruise in that film once, I don’t want to go through Minority Report ever again with that.
So, gentlemen, that wraps today’s edition of the Futurum Tech Podcast. I thank you both for your insights here. We went a bit long but good stuff. And I want to remind our listeners here that the Edge Computing Report, From the Edge to the Core to the Edge, is available on the Futurum Research website. We will have the link in the show notes here for you to take a look. It’s a free download. And we encourage you, if you have questions, comments, send them back to us. And since you’re listening to the podcast, go ahead and hit that subscribe button. Give us a like. Share it with your friends. The more people, the merrier I guess is the way to look at it.
So with that, Dan, Olivier, thank you. And to our listeners, thank you very much. We will see you next week for another exciting and potentially shorter edition of the Futurum Tech Podcast.
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