Internet of Thinking – Tech Vision 2018 Trend

Internet of Thinking – Tech Vision 2018 Trend


AI, robotics, immersive reality, connected
devices – all of them undoubtedly huge technological boons but at the same time they’re collectively
putting a strain on the infrastructure that founded upon. So, as we’re becoming more demanding about
data we’re asking, is it time to rethink how and where our data is handled. I’m talking to Paul Daugherty, Marc Carrel-Billiard,
Michael Biltz and Elise Cornille. The Internet of Thinking it’s a very curious
turn of phrase. What does it mean? The Internet of Thinking is one of my favourite
areas that we’re talking about in the Vision this year because it’s an interesting term,
but it also really captures what’s happening as intelligent enterprises move forward. And it’s talking about the fact that intelligence
is something that needs to be embedded in many different parts of the organization,
in many different parts of your operations. The Internet of Thinking is about how you
tie all these different intelligent components together in the right way to accomplish what
you’re doing from a business perspective. If you’re in a consumer industry, it might
be the device in the consumer’s living room or that they’re wearing on the wrist. If you’re in a manufacturing company it might
be on your trucks or out in your manufacturing operations. As we’re applying more intelligence, it’s
not just all one centralized big-brain system that’s doing this for organizations, it’s
intelligence at the edge in many cases, it’s off board, off-line intelligence combined
with different, more centralized means. And that’s what we mean when we talk about
the Internet of Thinking, it’s how do you assemble the right enterprise capabilities
out of this very distributed set of capabilities that you need to build around your organization. We’ve become accustomed to the cloud being
such a great servant for us in terms of being able to cope with all our demands over the
last 10 years, companies just offloading everything to the cloud. But, what kind of trends are we seeing today. A good question. I think what we see now, is that we see that
the processing of the data is not staying in the cloud, but now is going to towards
where the action is. We call that the edge. And that’s why we see like IoT, edge IoT and
all the things coming back… …to the device itself? That’s right. And so I think that’s going to be very important. If you look at where the technology is going
with the driverless car, with more sensors everywhere like in the fabs, the manufacturing… …in our homes, on our person… Everything. So it’s going to be really at the edge. And what it means is two things; it means
that we need to increase the potential of the semiconductor chips that are built. The second thing that we need to think about
is, ‘okay well this is the, the computing power needed at this level’ and we need
to figure out exactly what is absolutely needed and what is not because we’ll have to make
priorities in the algorithm of what needs to be at the edge and what needs to remain
in the cloud. So, there’s going to be a lot of rethinking
about architecture, leveraging microservices and some other stuff like that. So, we’re talking about reconstituting the
architecture, if you like, of all systems, but it’s not to say that the cloud’s going
away. What’s going to be the dynamic between on-board
and, if you like, the farther use case of the cloud. Yeah, I mean what’s happened is that we’re
actually now starting to personalize and customize every solution. So, the hardware to the software, to the cloud,
depending on what exactly it is that you’re doing. You know, you use an example of something
like NeuroPace. And, essentially, what they’ve created is
a small little device, it’s surgically implanted and what it’s going to do is – on the device
itself, it’s self-contained – it’s going to monitor, look for signs of seizure happening
and then when it does it sends out pulses to help control them. And they’re reducing things by 40, I think
44 percent, which are amazing results. But, that’s also not where they’re going to
be doing and figuring these algorithms out. They’re figuring these things out by periodically
uploading the data back to a database that’s going to take not one individual, but every
single person using this and using the signals, the data, they’re getting off of it in order
to refine, to create better algorithms that then go down back to the device itself in
order to make it better through every iteration. We’ve been hearing about the shifting, if
you like, in the balance of power between the cloud and back to the edge, device-level
processing. What’s driving that? Really, it’s about consumer expectations. As things have evolved we are looking for
the objects around us to become more and more intelligent and give us instant feedback,
and instant gratification which we talk about. But, in order to do that we need much more
advanced compute power at the edge with these devices and then to communicate back with
your enterprise, make sense of the data that’s being used, and use that to develop new products
and services and meet those consumer expectations. So it’s not a one size fits all, really is
it? It’s going to be some decisions are going
to be made at the edge. Some are going to be made at the network level. How do you decide as a company what goes where,
do you need different capabilities inside companies to think about these kinds of things? Yeah, I think a lot of companies are having
to take a hard look at hardware. You know, for years that’s been something
we’ve kind of taken for granted on the consumer level – there will always be upgrades, right? There’ll always be more compute power. But, we’re reaching the limits of some of
that. So, companies are needing to reinvest in their
infrastructure and look at having software accelerators that will help them reach that
next level of hardware compute processing. And then also being able to provide that instant
intelligence that not only customers are demanding, but that a lot of different devices will demand
even if you think about autonomous driving cars, or extended reality headsets and more. And does it, I suppose, mean a whole new level
of thinking about partnerships with some companies that are providing these kind of compute power? Absolutely. I think the semiconductor industry is poised
to form new partnerships and really advance this because, simply put, most organizations
won’t be able to invest very quickly in their own hardware and infrastructure. They’ll be looking for ways to partner with
others to not only improve that, but also team with them to give them more capabilities,
more ability to expand their own infrastructure to serve different kinds of customers. So, there are plenty of examples on how we
would demand this kind of real-time interaction with the devices for good reason. There are. I think a great example is some of the public
safety applications of the Internet of Thinking that are really advancing the way that we
are protected in different environments. For example, there’s a lot of video analytics
that are used to monitor train stations and different public spaces to ensure that they
can quickly, instantaneously, spot an adverse event, or perhaps just an abnormal exception
event, and quickly flag that and have the right human intervention – even machine intervention
– whether it be automatically closing doors when there could be a fire, for example, or
deploying public safety officials in a situation that looks like it may be threatening people
around them. So, we’ve heard about technology driving a
move both to the edge and also more centralized management. What is the big takeaway here for business
and how they need to respond to this? I think it’s bringing about a new need for
more sophisticated engineering experience across many domains. It’ll all depend on the base of the company
and the industry, but it’s certainly not just about the back-office IT anymore (and it hasn’t
been for a while), it’s about being able to engineer across all these different devices
and platforms and that brings a different kind of need for a different kind of talent. And, as you as you look at that, it also brings
a need for different partnerships because no organization can do all that on their own. So, the ability to form the right partnerships
with other technology and service providers to provide those end-to-end solutions could
be very critical.

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