Category Archives: Platform 3.0

Do Androids Dream of Electric Sheep?

By Stuart Boardman, KPN

What does the apocalyptic vision of Blade Runner have to do with The Open Group’s Open Platform 3.0™ Forum?

Throughout history, from the ancient Greeks and the Talmud, through The Future Eve and Metropolis to I Robot and Terminator, we seem to have been both fascinated and appalled by the prospect of an autonomous “being” with its own consciousness and aspirations.

Hal-2001

But right now it’s not the machines that bother me. It’s how we try to do what we try to do with them. What we try to do is to address problems of increasingly critical economic, social and environmental importance. It bothers me because, like it or not, these problems can only be addressed by a partnership of man and (intelligent) machine and yet we seem to want to take the intelligence out of both partners.

Two recent posts that came my way via Twitter this week provoked me to write this blog. One is a GE Report that looks very thoroughly, if somewhat uncritically at what it calls the Industrial Internet. The other, by Forrester analyst Sarah Rotman Epps, appeared in Forbes under the title There Is No Internet of Things and laments the lack of interconnectedness in most “Smart” technologies.hammer

What disturbs me about both of those pieces is the suggestion that if we sort out some interoperability and throw masses of computing power and smart algorithms at a problem, everything will be dandy.

Actually it could just make things worse. Technically everything will work but the results will be a matter of chance. The problem lies in the validity of the models we use. And our ability to effectively model complex problems is at best unproven. If the model is faulty and the calculation perfect, the results will be wrong. In fact, when the systems we try to model are complex or chaotic, no deterministic model can deliver correct results other than by accident. But we like deterministic models, because they make us feel like we’re in control. I discussed this problem and its effects in more detail in my article on Ashby’s Law Of Requisite Variety. There’s also an important article by Joyce Hostyn, which explains how a simplistic view of objectivity leads to (at best) biased results. “Data does not lie. It just does not (always) mean what you think it does” (Claudia Perlich, Chief Scientist at Dstillery via CMSWire).

Now that doesn’t detract from the fact that developing a robot vacuum cleaner that actually “learns” the layout of a room is pretty impressive. That doesn’t mean that the robot is aware that it is a vacuum cleaner and that it has a (single) purpose in life. And just as well. It might get upset about us continually moving the furniture and decide to get revenge by crashing into our best antique glass cabinet.

With the Internet of Things (IoT) and Big Data in particular, we’re deploying machines to carry out analyses and take decisions that can be critical for the success of some human endeavor. If the models are wrong or only sometimes right, the consequences can be disastrous for health, the environment or the economy. In my Ashby piece I showed how unexpected events can result in an otherwise good model leading to fundamentally wrong reactions. In a world where IoT and Big Data combine with Mobility (multiple device types, locations and networks) and Cloud, the level of complexity is obviously high and there’s scope for a large number of unexpected events.
IoT Society

If we are to manage the volume of information coming our way and the speed with which it comes or with which we must react we need to harness the power of machine intelligence. In an intelligent manner. Which brings me to Cognitive Computing Systems.

On the IBM Research Cognitive Computing page I found this statement: “Far from replacing our thinking, cognitive systems will extend our cognition and free us to think more creatively.”  Cognitive Computing means allowing the computer to say “listen guys, I’m not really sure about this but here are the options”. Or even “I’ve actually never seen one of these before, so maybe you’d like to see what you can make of it”. And if the computer is really really not sure, maybe we’d better ride the storm for a while and figure out what this new thing is. Cognitive Computing means that we can, in a manner of speaking, discuss this with the computer.

It’s hard to say how far we are from commercially viable implementations of this technology. Watson has a few children but the family is still at the stage of applied research. But necessity is the mother of invention and, if the technologies we’re talking about in Platform 3.0 really do start collectively to take on the roles we have envisaged for them, that could just provide the necessary incentive to develop economically feasible solutions.

spacemenIn the meantime, we need to put ourselves more in the centre of things, to make the optimal use of the technologies we do have available to us but not shirk our responsibilities as intelligent human beings to use that intelligence and not seek easy answers to wicked problems.

 

 

I’ll leave you with 3 minutes and 12 seconds of genius:
marshalldavisjones
Marshall Davis Jones: “Touchscreen”


Stuart BoardmanStuart Boardman is a Senior Business Consultant with KPN where he co-leads the Enterprise Architecture practice as well as the Cloud Computing solutions group. He is co-lead of The Open Group Cloud Computing Work Group’s Security for the Cloud and SOA project and a founding member of both The Open Group Cloud Computing Work Group and The Open Group SOA Work Group. Stuart is the author of publications by the Information Security Platform (PvIB) in The Netherlands and of his previous employer, CGI. He is a frequent speaker at conferences on the topics of Cloud, SOA, and Identity.

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Filed under Cloud, Cloud/SOA, Open Platform 3.0, Platform 3.0

Leading Business Disruption Strategy with Enterprise Architecture

By Patty Donovan, The Open Group

On Wednesday, October 2nd, The Open Group and Enterprise Architects will host a tweet jam which discusses how organisations can lead business disruption with Enterprise Architecture (EA). Today, businesses are being forced to come to terms with their vulnerabilities and opportunities when it comes to disruptive innovation. Enterprise Architecture, by leveraging its emergent business architecture capabilities and its traditional technology and innovation focus, has the opportunity to fill a key void, aiding businesses to win in this new world.

In the recently published Hype Cycle for Enterprise Architecture 2013 Gartner places disruptive forces at the center of the emerging EA mandate:

“Enterprise Architecture (EA) is a discipline for proactively and holistically leading enterprise responses to disruptive forces by identifying and analyzing the execution of change toward desired business vision and outcomes.”

“EA practitioners have the opportunity to take a quantum leap toward not only becoming integral to the business, but also leading business change.”

Source: Hype Cycle for Enterprise Architecture 2013, Gartner 2013

Please join us on Wednesday, October 2nd at 12noon BST for our upcoming “Leading Disruption Strategy with EA” tweet jam where leading experts will discuss this evolving topic.

We welcome Open Group members and interested participants from all backgrounds to join the session and interact with our panel thought leaders, led by Hugh Evans, CEO of Enterprise Architects (@enterprisearchs). To access the discussion, please follow the #ogChat hashtag during the allotted discussion time.

Planned questions include:

  • Q1 What is #Disruption?
  • Q2 What is #Digitaldisruption?
  • Q3 What are good examples of disruptive #Bizmodels?
  • Q4 What is the role of #EntArch in driving and responding to #disruption?
  • Q5 Why is #EntArch well placed to respond to #Disruption?
  • Q6 Who are the key stakeholders #EntArch needs to engage when developing a #Disruption strategy?
  • Q7 What current gaps in #EntArch must be filled to effectively lead #Disruption strategy?

Additional appropriate hashtags:

  • #EntArch – Enterprise Architecture
  • #BizArch – Business Architecture
  • #Disruption – Disruption
  • #DigitalDisruption – Digital Disruption
  • #Bizmodels – Business Models
  • #ogArch – The Open Group Architecture Forum

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of this tweet jam is to share knowledge and answer questions on leading business disruption strategy with enterprise architecture. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat hashtag.
    • Sample: “Big Data presents a large business opportunity, but it is not yet being managed effectively internally – who owns the big data function? #ogchat”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rob Checkal (rob.checkal at hotwirepr.com). We anticipate a lively chat and hope you will be able to join!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Filed under Business Architecture, Enterprise Architecture, Future Technologies, Open Platform 3.0, Platform 3.0, Tweet Jam

IT Technology Trends – a Risky Business?

By Patty Donovan, The Open Group

On Wednesday, September 25, The Open Group will host a tweet jam looking at a multitude of emerging/converging technology trends and the risks they present to organizations who have already adopted or are looking to adopt them. Most of the technology concepts we’re talking about – Cloud, Big Data, BYOD/BYOS, the Internet of Things etc – are not new, but organizations are at differing stages of implementation and do not yet fully understand the longer term impact of adoption.

This tweet jam will allow us to explore some of these technologies in more detail and look at how organizations may better prepare against potential risks – whether this is in regards to security, access management, policies, privacy or ROI. As discussed in our previous Open Platform 3.0™ tweet jam, new technology trends present many opportunities but can also present business challenges if not managed effectively.

Please join us on Wednesday, September 25 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. BST for a tweet jam that will discuss and debate the issues around technology risks. A number of key areas will be addressed during the discussion including: Big Data, Cloud, Consumerization of IT, the Internet of Things and mobile and social computing with a focus on understanding the key risk priority areas organizations face and ways to mitigate them.

We welcome Open Group members and interested participants from all backgrounds to join the session and interact with our panel thought leaders led by David Lounsbury, CTO and Jim Hietala, VP of Security, from The Open Group. To access the discussion, please follow the #ogChat hashtag during the allotted discussion time.

  • Do you feel prepared for the emergence/convergence of IT trends? – Cloud, Big Data, BYOD/BYOS, Internet of things
  • Where do you see risks in these technologies? – Cloud, Big Data, BYOD/BYOS, Internet of things
  • How does your organization monitor for, measure and manage risks from these technologies?
  • Which policies are best at dealing with security risks from technologies? Which are less effective?
  • Many new technologies move data out of the enterprise to user devices or cloud services. Can we manage these new risks? How?
  • What role do standards, best practices and regulations play in keeping up with risks from these & future technologies?
  • Aside from risks caused by individual trends, what is the impact of multiple technology trends converging (Platform 3.0)?

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of this tweet jam is to share knowledge and answer questions on emerging/converging technology trends and the risks they present. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat hashtag.
    • Sample: “Big Data presents a large business opportunity, but it is not yet being managed effectively internally – who owns the big data function? #ogchat”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rob Checkal (rob.checkal at hotwirepr.com). We anticipate a lively chat and hope you will be able to join!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Filed under Cloud, Cloud/SOA, Data management, Future Technologies, Open Platform 3.0, Platform 3.0, Tweet Jam

Are You Ready for the Convergence of New, Disruptive Technologies?

By Chris Harding, The Open Group

The convergence of technical phenomena such as cloud, mobile and social computing, big data analysis, and the Internet of things that is being addressed by The Open Group’s Open Platform 3.0 Forum™ will transform the way that you use information technology. Are you ready? Take our survey at https://www.surveymonkey.com/s/convergent_tech

What the Technology Can Do

Mobile and social computing are leading the way. Recently, the launch of new iPhone models and the announcement of the Twitter stock flotation were headline news, reflecting the importance that these technologies now have for business. For example, banks use mobile text messaging to alert customers to security issues. Retailers use social media to understand their markets and communicate with potential customers.

Other technologies are close behind. In Formula One motor racing, sensors monitor vehicle operation and feed real-time information to the support teams, leading to improved design, greater safety, and lower costs. This approach could soon become routine for cars on the public roads too.

Many exciting new applications are being discussed. Stores could use sensors to capture customer behavior while browsing the goods on display, and give them targeted information and advice via their mobile devices. Medical professionals could monitor hospital patients and receive alerts of significant changes. Researchers could use shared cloud services and big data analysis to detect patterns in this information, and develop treatments, including for complex or uncommon conditions that are hard to understand using traditional methods. The potential is massive, and we are only just beginning to see it.

What the Analysts Say

Market analysts agree on the importance of the new technologies.

Gartner uses the term “Nexus of Forces” to describe the convergence and mutual reinforcement of social, mobility, cloud and information patterns that drive new business scenarios, and says that, although these forces are innovative and disruptive on their own, together they are revolutionizing business and society, disrupting old business models and creating new leaders.

IDC predicts that a combination of social cloud, mobile, and big data technologies will drive around 90% of all the growth in the IT market through 2020, and uses the term “third platform” to describe this combination.

The Open Group will identify the standards that will make Gartner’s Nexus of Forces and IDC’s Third Platform commercial realities. This will be the definition of Open Platform 3.0.

Disrupting Enterprise Use of IT

The new technologies are bringing new opportunities, but their use raises problems. In particular, end users find that working through IT departments in the traditional way is not satisfactory. The delays are too great for rapid, innovative development. They want to use the new technologies directly – “hands on”.

Increasingly, business departments are buying technology directly, by-passing their IT departments. Traditionally, the bulk of an enterprise’s IT budget was spent by the IT department and went on maintenance. A significant proportion is now spent by the business departments, on new technology.

Business and IT are not different worlds any more. Business analysts are increasingly using technical tools, and even doing application development, using exposed APIs. For example, marketing folk do search engine optimization, use business information tools, and analyze traffic on Twitter. Such operations require less IT skill than formerly because the new systems are easy to use. Also, users are becoming more IT-savvy. This is a revolution in business use of IT, comparable to the use of spreadsheets in the 1980s.

Also, business departments are hiring traditional application developers, who would once have only been found in IT departments.

Are You Ready?

These disruptive new technologies are changing, not just the IT architecture, but also the business architecture of the enterprises that use them. This is a sea change that affects us all.

The introduction of the PC had a dramatic impact on the way enterprises used IT, taking much of the technology out of the computer room and into the office. The new revolution is taking it out of the office and into the pocket. Cell phones and tablets give you windows into the world, not just your personal collection of applications and information. Through those windows you can see your friends, your best route home, what your customers like, how well your production processes are working, or whatever else you need to conduct your life and business.

This will change the way you work. You must learn how to tailor and combine the information and services available to you, to meet your personal objectives. If your role is to provide or help to provide IT services, you must learn how to support users working in this new way.

To negotiate this change successfully, and take advantage of it, each of us must understand what is happening, and how ready we are to deal with it.

The Open Group is conducting a survey of people’s reactions to the convergence of Cloud and other new technologies. Take the survey, to input your state of readiness, and get early sight of the results, to see how you compare with everyone else.

To take the survey, visit https://www.surveymonkey.com/s/convergent_tech

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing, and the Platform 3.0 Forum. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF® practitioner.

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Variety, Black Swans and Platform 3.0

By Stuart Boardman, KPN

Enterprises today are subject to and increasingly make use of a range of technological and business phenomena, that increase enormously the range of factors affecting the ability of an enterprise to carry out its business effectively and efficiently. Some examples of this (Cloud, Big Data, The Internet of Things, Social Media/Business and Mobility) are the focus of The Open Group’s Open Platform 3.0™ Forum. An enterprise participating in some way in this world (i.e. any enterprise unable to lock itself inside its own walls) will have to find ways of matching the variety these phenomena introduce. I’m using the term Variety here in the sense defined by W. Ross Ashby – most notably in his Law Of Requisite Variety (1952), which I’ve written more extensively about elsewhere.

Variety can be internal or external to a system (an enterprise is a system) but it’s the external variety that is increased so dramatically by these new phenomena, because they typically involve having some part of an enterprise’s business performed by another party – or a network of parties, not all of whom are necessarily directly known to that enterprise.

Ashby’s law says that the more Variety a system has to deal with, the more variety is needed in its responses. Variety must be matched by variety. You need at least to be able to monitor each factor and assess changes in its behavior, if you are to have any hope of responding..

There are three main elements involved in developing a strategy to match variety.

First we need to find ways of identifying relevant variety and of understanding what its effect on our enterprise might be. That’s going to tell us what meaningful options for response exist. We should not make the mistake of thinking that a deterministic response to any given type of variety is always possible. Ashby himself was very clear about this. Some factors (especially those involving people) don’t behave in a predictable manner. It’s therefore useful to classify each form of variety according to some schematic. I use Tom Graves’s SCAN framework.

image001

There are other frameworks – I just find Tom’s semantics rich but easy to follow.

Second we need to understand the level of risk that a particular form of variety might pose. How much damage might a particular event do to our business? In the “always on” world that Platform 3.0 encompasses, there’s a tendency to assume that being offline is a drama. But is that always true? The size and cost of a response mechanism needs to be in proportion with the risk involved.

image003Lastly we must decide what kind of response mechanism we actually want to implement – assuming  the level of risk and the available options indicate any need for response at all. The fact that we could put a control mechanism in place doesn’t necessarily mean that it’s a good idea, as Nassim Nicholas Taleb shows in his book Antifragile (of which more in a minute).

Here’s an example from the Internet of Things (IoT): “Smart Charging” for electric automobiles. Here we know that the number of parties involved is quite small (Distribution Network Operator, Charging Provider, Local Controller/Provider and Automobile/User) and that both functional and legal/commercial contracts image005between parties will apply. If we look at an individual device (sensor, monitor, controller…) and its relationship to someone else’s device, there’s a good chance we can describe the behaviour with some confidence. So we’re talking about a Simple situation that’s amenable to a rules based (“if A happens, do B”) response. But of course it’s not usually so straightforward. One can expect at least a one to many relationship between “our” device and the devices with which it exchanges information. So in reality we’re dealing with a Complicated situation. That doesn’t mean you can’t determine a reliable set of behaviours and responses but it will be a sizeable matrix and will require significant analysis effort.

So what’s the risk? Well that depends who you are. A car owner, a charging provider and a network operator have quite different perceptions of what constitutes an event of business significance. They all have a common interest in the efficient functioning of the system as a whole but quite different views on which events require a response and what sort of response. A sensor or controller problem could lead to a failure to detect a potential network overload. So could faulty data about weather or consumption patterns or poor (big) data analytics, all of which fall at best into the Ambiguous category. For a car owner this isn’t really a risk until something goes seriously wrong – and even then one can always work from home. For the network operator the significance is far greater, as they are legally responsible for providing sufficient capacity and additional infrastructure is expensive. On the other hand, if the network operator decides to play safe and reduce capacity allocated to the charging provider, that will at least lead to irritation for car owners due to incomplete or slow charging of their car. That is not usually a business critical event but the possibility exists. For the charging provider an isolated local event is not much more than an annoyance but a widespread effect can have direct financial or customer relationship consequences.

Then there’s the third consideration. Just because we could set up a control, does that mean we really should do so? In Antifragile Taleb shows that many systems are fragile exactly because they try to control everything. Now in general this applies to social/economic systems, which in SCAN terms are Ambiguous or Not-known and therefore not really amenable to tight control anyway. But even mechanical systems can suffer from this problem. It’s not uncommon that a response to some stimulus has knock-on effects elsewhere in the system and if there’s a two way relationship between a source of variety and our response mechanism, all kinds of unexpected things could happen. So we need to be very sure about what we’re doing.

image007Moreover tightly controlled systems have great difficulty with black swan events (another Taleb book), because these by definition are not catered for in the rule book. An over-reaction or mistaken reaction can have disastrous consequences. No reaction may sometimes be a better tactic. All of which brings me to another example.

The example is based on the (in)famous Amazon outage of a couple of years back and is in no way intended to knock Amazon. I’ve written about this in detail in another blog but the central point is that when there is a significant outage we (the customer) are in the Not-known territory. We have no direct ability to respond to the variety that caused the problem, so we need a different way of responding – something that we can decide for ourselves but which can’t possibly be based on a rules driven approach. I described a response that involved creating a separate back-up/recovery strategy – potentially with multiple options. But of course that comes at a price, so our risk assessment needs to be well thought through.

This example has another interesting aspect to it. The scale of the problem arose from a failure of a control structure that could manage expected events but which actually made things worse in the face of something in the order of a black swan event. And of course this isn’t just about machines – there were people involved too. The control structure was intended to be robust but was in fact fragile. But in the end how much damage was done? As far as I know no-one went bust. Amazon learned from the experience and continued to do so – and so did everyone else. So actually the whole system proved to be anti-fragile. It got better as a result of a few knocks. I don’t know exactly how Amazon do it now but I hope they’ve given up trying to control everything with a rule book.

You could say that the mission of the Open Platform 3.0 Forum is to help enterprises gain the benefits they seek from all those phenomena. So here’s a great opportunity for the Forum to take a lead in an area that too often gets shoved off into the non-sexy world of “non-functional requirements”. I hope we can describe ways for enterprises to deal with variety in an intelligent and adequate manner – to reliably manage what can be managed without driving themselves crazy trying to manage the unmanageable.

Stuart BoardmanStuart Boardman is a Senior Business Consultant with KPN where he co-leads the Enterprise Architecture practice as well as the Cloud Computing solutions group. He is co-lead of The Open Group Cloud Computing Work Group’s Security for the Cloud and SOA project and a founding member of both The Open Group Cloud Computing Work Group and The Open Group SOA Work Group. Stuart is the author of publications by the Information Security Platform (PvIB) in The Netherlands and of his previous employer, CGI. He is a frequent speaker at conferences on the topics of Cloud, SOA, and Identity.

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As Platform 3.0 ripens, expect agile access and distribution of actionable intelligence across enterprises, says The Open Group panel

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here

This latest BriefingsDirect discussion, leading into the The Open Group Conference on July 15 in Philadelphia, brings together a panel of experts to explore the business implications of the current shift to so-called Platform 3.0.

Known as the new model through which big data, cloud, and mobile and social — in combination — allow for advanced intelligence and automation in business, Platform 3.0 has so far lacked standards or even clear definitions.

The Open Group and its community are poised to change that, and we’re here now to learn more how to leverage Platform 3.0 as more than a IT shift — and as a business game-changer. It will be a big topic at next week’s conference.

The panel: Dave Lounsbury, Chief Technical Officer at The Open Group; Chris Harding, Director of Interoperability at The Open Group, and Mark Skilton, Global Director in the Strategy Office at Capgemini. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference, which is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL. [Disclosure: The Open Group is a sponsor of this and other BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: A lot of people are still wrapping their minds around this notion of Platform 3.0, something that is a whole greater than the sum of the parts. Why is this more than an IT conversation or a shift in how things are delivered? Why are the business implications momentous?

Lounsbury: Well, Dana, there are lot of IT changes or technical changes going on that are bringing together a lot of factors. They’re turning into this sort of super-saturated solution of ideas and possibilities and this emerging idea that this represents a new platform. I think it’s a pretty fundamental change.

Lounsbury

If you look at history, not just the history of IT, but all of human history, you see that step changes in societies and organizations are frequently driven by communication or connectedness. Think about the evolution of speech or the invention of the alphabet or movable-type printing. These technical innovations that we’re seeing are bringing together these vast sources of data about the world around us and doing it in real time.

Further, we’re starting to see a lot of rapid evolution in how you turn data into information and presenting the information in a way such that people can make decisions on it. Given all that we’re starting to realize, we’re on the cusp of another step of connectedness and awareness.

Fundamental changes

This really is going to drive some fundamental changes in the way we organize ourselves. Part of what The Open Group is doing, trying to bring Platform 3.0 together, is to try to get ahead of this and make sure that we understand not just what technical standards are needed, but how businesses will need to adapt and evolve what business processes they need to put in place in order to take maximum advantage of this to see change in the way that we look at the information.

Harding: Enterprises have to keep up with the way that things are moving in order to keep their positions in their industries. Enterprises can’t afford to be working with yesterday’s technology. It’s a case of being able to understand the information that they’re presented, and make the best decisions.

Harding

We’ve always talked about computers being about input, process, and output. Years ago, the input might have been through a teletype, the processing on a computer in the back office, and the output on print-out paper.

Now, we’re talking about the input being through a range of sensors and social media, the processing is done on the cloud, and the output goes to your mobile device, so you have it wherever you are when you need it. Enterprises that stick in the past are probably going to suffer.

Gardner: Mark Skilton, the ability to manage data at greater speed and scale, the whole three Vs — velocity, volume, and value — on its own could perhaps be a game changing shift in the market. The drive of mobile devices into lives of both consumers and workers is also a very big deal.

Of course, cloud has been an ongoing evolution of emphasis towards agility and efficiency in how workloads are supported. But is there something about the combination of how these are coming together at this particular time that, in your opinion, substantiates The Open Group’s emphasis on this as a literal platform shift?

Skilton: It is exactly that in terms of the workloads. The world we’re now into is the multi-workload environment, where you have mobile workloads, storage and compute workloads, and social networking workloads. There are many different types of data and traffic today in different cloud platforms and devices.

Skilton

It has to do with not just one solution, not one subscription model — because we’re now into this subscription-model era … the subscription economy, as one group tends to describe it. Now, we’re looking for not only just providing the security, the infrastructure, to deliver this kind of capability to a mobile device, as Chris was saying. The question is, how can you do this horizontally across other platforms? How can you integrate these things? This is something that is critical to the new order.

So Platform 3.0 addressing this point by bringing this together. Just look at the numbers. Look at the scale that we’re dealing with — 1.7 billion mobile devices sold in 2012, and 6.8 billion subscriptions estimated according to the International Telecommunications Union (ITU) equivalent to 96 percent of the world population.

Massive growth

We had massive growth in scale of mobile data traffic and internet data expansion. Mobile data is increasing 18 percent fold from 2011 to 2016 reaching 130 exabytes annually.  We passed 1 zettabyte of global online data storage back in 2010 and IP data traffic predicted to pass 1.3 zettabytes by 2016, with internet video accounting for 61 percent of total internet data according to Cisco studies.

These studies also predict data center traffic combining network and internet based storage will reach 6.6 zettabytes annually, and nearly two thirds of this will be cloud based by 2016.  This is only going to grow as social networking is reaching nearly one in four people around the world with 1.7 billion using at least one form of social networking in 2013, rising to one in three people with 2.55 billion global audience by 2017 as another extraordinary figure from an eMarketing.com study.

It is not surprising that many industry analysts are seeing growth in technologies of mobility, social computing, big data and cloud convergence at 30 to 40 percent and the shift to B2C commerce passing $1 trillion in 2012 is just the start of a wider digital transformation.

These numbers speak volumes in terms of the integration, interoperability, and connection of the new types of business and social realities that we have today.

Gardner: Why should IT be thinking about this as a fundamental shift, rather than a modest change?

Lounsbury: A lot depends on how you define your IT organization. It’s useful to separate the plumbing from the water. If we think of the water as the information that’s flowing, it’s how we make sure that the water is pure and getting to the places where you need to have the taps, where you need to have the water, etc.

But the plumbing also has to be up to the job. It needs to have the capacity. It needs to have new tools to filter out the impurities from the water. There’s no point giving someone data if it’s not been properly managed or if there’s incorrect information.

What’s going to happen in IT is not only do we have to focus on the mechanics of the plumbing, where we see things like the big database that we’ve seen in the open-source  role and things like that nature, but there’s the analytics and the data stewardship aspects of it.

We need to bring in mechanisms, so the data is valid and kept up to date. We need to indicate its freshness to the decision makers. Furthermore, IT is going to be called upon, whether as part of the enterprise IP or where end users will drive the selection of what they’re going to do with analytic tools and recommendation tools to take the data and turn it into information. One of the things you can’t do with business decision makers is overwhelm them with big rafts of data and expect them to figure it out.

You really need to present the information in a way that they can use to quickly make business decisions. That is an addition to the role of IT that may not have been there traditionally — how you think about the data and the role of what, in the beginning, was called data scientist and things of that nature.

Shift in constituency

Skilton: I’d just like to add to Dave’s excellent points about, the shape of data has changed, but also about why should IT get involved. We’re seeing that there’s a shift in the constituency of who is using this data.

We have the Chief Marketing Officer and the Chief Procurement Officer and other key line of business managers taking more direct control over the uses of information technology that enable their channels and interactions through mobile, social and data analytics. We’ve got processes that were previously managed just by IT and are now being consumed by significant stakeholders and investors in the organization.

We have to recognize in IT that we are the masters of our own destiny. The information needs to be sorted into new types of mobile devices, new types of data intelligence, and ways of delivering this kind of service.

I read recently in MIT Sloan Management Review an article that asked what is the role of the CIO. There is still the critical role of managing the security, compliance, and performance of these systems. But there’s also a socialization of IT, and this is where  the  positioning architectures which are cross platform is key to  delivering real value to the business users in the IT community.

Gardner: How do we prevent this from going off the rails?

Harding: This a very important point. And to add to the difficulties, it’s not only that a whole set of different people are getting involved with different kinds of information, but there’s also a step change in the speed with which all this is delivered. It’s no longer the case, that you can say, “Oh well, we need some kind of information system to manage this information. We’ll procure it and get a program written” that a year later that would be in place in delivering reports to it.

Now, people are looking to make sense of this information on the fly if possible. It’s really a case of having the platforms be the standard technology platform and also the systems for using it, the business processes, understood and in place.

Then, you can do all these things quickly and build on learning from what people have gone in the past, and not go out into all sorts of new experimental things that might not lead anywhere. It’s a case of building up the standard platform in the industry best practice. This is where The Open Group can really help things along by being a recipient and a reflector of best practice and standard.

Skilton: Capgemini has been doing work in this area. I break it down into four levels of scalability. It’s the platform scalability of understanding what you can do with your current legacy systems in introducing cloud computing or big data, and the infrastructure that gives you this, what we call multiplexing of resources. We’re very much seeing this idea of introducing scalable platform resource management, and you see that a lot with the heritage of virtualization.

Going into networking and the network scalability, a lot of the customers have who inherited their old telecommunications networks are looking to introduce new MPLS type scalable networks. The reason for this is that it’s all about connectivity in the field. I meet a number of clients who are saying, “We’ve got this cloud service,” or “This service is in a certain area of my country. If I move to another parts of the country or I’m traveling, I can’t get connectivity.” That’s the big issue of scaling.

Another one is application programming interfaces (APIs). What we’re seeing now is an explosion of integration and application services using API connectivity, and these are creating huge opportunities of what Chris Anderson of Wired used to call the “long tail effect.” It is now a reality in terms of building that kind of social connectivity and data exchange that Dave was talking about.

Finally, there are the marketplaces. Companies needs to think about what online marketplaces they need for digital branding, social branding, social networks, and awareness of your customers, suppliers, and employees. Customers can see that these four levels are where they need to start thinking about for IT strategy, and Platform 3.0 is right on this target of trying to work out what are the strategies of each of these new levels of scalability.

Gardner: We’re coming up on The Open Group Conference in Philadelphia very shortly. What should we expect from that? What is The Open Group doing vis-à-vis Platform 3.0, and how can organizations benefit from seeing a more methodological or standardized approach to some way of rationalizing all of this complexity? [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Lounsbury: We’re still in the formational stages of  “third platform” or Platform 3.0 for The Open Group as an industry. To some extent, we’re starting pretty much at the ground floor with that in the Platform 3.0 forum. We’re leveraging a lot of the components that have been done previously by the work of the members of The Open Group in cloud, services-oriented architecture (SOA), and some of the work on the Internet of things.

First step

Our first step is to bring those things together to make sure that we’ve got a foundation to depart from. The next thing is that, through our Platform 3.0 Forum and the Steering Committee, we can ask people to talk about what their scenarios are for adoption of Platform 3.0?

That can range from things like the technological aspects of it and what standards are needed, but also to take a clue from our previous cloud working group. What are the best business practices in order to understand and then adopt some of these Platform 3.0 concepts to get your business using them?

What we’re really working toward in Philadelphia is to set up an exchange of ideas among the people who can, from the buy side, bring in their use cases from the supply side, bring in their ideas about what the technology possibilities are, and bring those together and start to shape a set of tracks where we can create business and technical artifacts that will help businesses adopt the Platform 3.0 concept.

Harding: We certainly also need to understand the business environment within which Platform 3.0 will be used. We’ve heard already about new players, new roles of various kinds that are appearing, and the fact that the technology is there and the business is adapting to this to use technology in new ways.

For example, we’ve heard about the data scientist. The data scientist is a new kind of role, a new kind of person, that is playing a particular part in all this within enterprises. We’re also hearing about marketplaces for services, new ways in which services are being made available and combined.

We really need to understand the actors in this new kind of business scenario. What are the pain points that people are having? What are the problems that need to be resolved in order to understand what kind of shape the new platform will have? That is one of the key things that the Platform 3.0 Forum members will be getting their teeth into.

Gardner: Looking to the future, when we think about the ability of the data to be so powerful when processed properly, when recommendations can be delivered to the right place at the right time, but we also recognize that there are limits to a manual or even human level approach to that, scientist by scientist, analysis by analysis.

When we think about the implications of automation, it seems like there were already some early examples of where bringing cloud, data, social, mobile, interactions, granularity of interactions together, that we’ve begun to see that how a recommendation engine could be brought to bear. I’m thinking about the Siri capability at Apple and even some of the examples of the Watson Technology at IBM.

So to our panel, are there unknown unknowns about where this will lead in terms of having extraordinary intelligence, a super computer or data center of super computers, brought to bear almost any problem instantly and then the result delivered directly to a center, a smart phone, any number of end points?

It seems that the potential here is mind boggling. Mark Skilton, any thoughts?

Skilton: What we’re talking about is the next generation of the Internet.  The advent of IPv6 and the explosion in multimedia services, will start to drive the next generation of the Internet.

I think that in the future, we’ll be talking about a multiplicity of information that is not just about services at your location or your personal lifestyle or your working preferences. We’ll see a convergence of information and services across multiple devices and new types of “co-presence services” that interact with your needs and social networks to provide predictive augmented information value.

When you start to get much more information about the context of where you are, the insight into what’s happening, and the predictive nature of these, it becomes something that becomes much more embedding into everyday life and in real time in context of what you are doing.

I expect to see much more intelligent applications coming forward on mobile devices in the next 5 to 10 years driven by this interconnected explosion of real time processing data, traffic, devices and social networking we describe in the scope of platform 3.0. This will add augmented intelligence and is something that’s really exciting and a complete game changer. I would call it the next killer app.

First-mover benefits

Gardner: There’s this notion of intelligence brought to bear rapidly in context, at a manageable cost. This seems to me a big change for businesses. We could, of course, go into the social implications as well, but just for businesses, that alone to me would be an incentive to get thinking and acting on this. So any thoughts about where businesses that do this well would be able to have significant advantage and first mover benefits?

Harding: Businesses always are taking stock. They understand their environments. They understand how the world that they live in is changing and they understand what part they play in it. It will be down to individual businesses to look at this new technical possibility and say, “So now this is where we could make a change to our business.” It’s the vision moment where you see a combination of technical possibility and business advantage that will work for your organization.

It’s going to be different for every business, and I’m very happy to say this, it’s something that computers aren’t going to be able to do for a very long time yet. It’s going to really be down to business people to do this as they have been doing for centuries and millennia, to understand how they can take advantage of these things.

So it’s a very exciting time, and we’ll see businesses understanding and developing their individual business visions as the starting point for a cycle of business transformation, which is what we’ll be very much talking about in Philadelphia. So yes, there will be businesses that gain advantage, but I wouldn’t point to any particular business, or any particular sector and say, “It’s going to be them” or “It’s going to be them.”

Gardner: Dave Lounsbury, a last word to you. In terms of some of the future implications and vision, where could this could lead in the not too distant future?

Lounsbury: I’d disagree a bit with my colleagues on this, and this could probably be a podcast on its own, Dana. You mentioned Siri, and I believe IBM just announced the commercial version of its Watson recommendation and analysis engine for use in some customer-facing applications.

I definitely see these as the thin end of the wedge on filling that gap between the growth of data and the analysis of data. I can imagine in not in the next couple of years, but in the next couple of technology cycles, that we’ll see the concept of recommendations and analysis as a service, to bring it full circle to cloud. And keep in mind that all of case law is data and all of the medical textbooks ever written are data. Pick your industry, and there is huge amount of knowledge base that humans must currently keep on top of.

This approach and these advances in the recommendation engines driven by the availability of big data are going to produce profound changes in the way knowledge workers produce their job. That’s something that businesses, including their IT functions, absolutely need to stay in front of to remain competitive in the next decade or so.

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Three laws of the next Internet of Things – the new platforming evolution in computing

By Mark Skilton, Global Director at Capgemini

There is a wave of new devices and services that are growing in strength extending the boundary of what is possible in today’s internet driven economy and lifestyle.   A striking feature is the link between apps that are on smart phones and tablets and the ability to connect to not just websites but also to data collection sensors and intelligence analytical analysis of that information.   A key driver of this has also been the improvement in the cost-performance curve of information technology not just in CPU and storage but also the easy availability and affordability of highly powerful computing and mass storage in mobile devices coupled with access to complex sensors, advanced optics and screen displays results in a potentially truly immersive experience.  This is a long way from the early days of radio frequency identity tags which are the forerunner of this evolution.   Digitization of information and its interpretation of meaning is everywhere, moving into a range of industries and augmented services that create new possibilities and value. A key challenge in how to understand this growth of devices, sensors, content and services across the myriad of platforms and permutations this can bring.

·         Energy conservation

o   Through home and building energy management

·         Lifestyle activity

o   Motion sensor Accelerometers, ambient light sensors, moisture sensors, gyroscopes, proximity sensors.

·          Lifestyle health

o   Heart rate, blood oxygen levels, respiratory rate, heart rate variability, for cardiorespiratory monitoring are some of the potential
that connecting Devices

·         Medical Health

o   Biomedical sensing for patient care and elderly care management,  heart, lung, kidney dialysis,  medial value and organ implants, orthopaedic implants and brain-image scanning.   Examples of devices can monitoring elderly physical activity, blood pressure and other factors unobtrusively and proactively.  These aim to drive improvements in prevention, testing, early detection, surgery and treatment helping improve quality of life and address rising medical costs and society impact of aging population.

·         Transport

o   Precision global positioning, local real time image perception interpretation  sensing, dynamic electromechanical control systems.

·         Materials science engineering and manufacturing

o   Strain gauges, stress sensors, precision lasers, micro and nanoparticle engineering,  cellular manipulation, gene splicing,
3D printing has the potential to revolutionize automated manufacturing but through distributed services over the internet, manufacturing can potentially be accessed by anyone.

·         Physical Safety and security

o   Examples include Controlling children’s access to their mobile phone via your pc is an example of parental protection of children using web based applications to monitory and control mobile and computing access.  Or Keyless entry using your  phone.  Wiki, Bluetooth and internet network app and device to automate locking of physical; door and entry remotely or in proximity.

·         Remote activity and swarming robotics

o   The developing of autonomous robotics to respond and support exploration and services in harsh or inaccessible environments. Disabled support through robotic prosthetics and communication synthesis.   Swarming robots that fly or mimic group behavior.  Swarming robots that mimic nature and decision making.

These are just the tip of want is possible; the early commercial ventures that are starting to drive new ways to think about information technology and application services.

A key feature I noticed in all these devices are that they augment previous layers of technology by sitting on top of them and adding extra value.   While often the long shadow of the first generation giants of the public internet Apple, Google, Amazon give the impression that to succeed means a controlled platform and investment of millions; these new technologies use existing infrastructure and operate across a federated distributed architecture that represents a new kind of platforming paradigm of multiple systems.

Perhaps a paradigm of new technology cycles is that as the new tech arrives it will cannibalize older technologies. Clearly nothing is immune to this trend, even the cloud,   I’ll call it even the evolution of a  kind a technology laws ( a feature  I saw in by Charles Fine clock speed book http://www.businessforum.com/clockspeed.html  but adapted here as a function of compound cannibalization and augmentation).  I think Big Data is an example of such a shift in this direction as augmented informatics enables major next generation power pays for added value services.

These devices and sensors can work with existing infrastructure services and resources but they also create a new kind of computing architecture that involves many technologies, standards and systems. What was in early times called “system of systems” Integration (Examples seen in the defence sector  http://www.bctmod.army.mil/SoSI/sosi.html  and digital ecosystems in the government sector  http://www.eurativ.com/specialreport-skills/kroes-europe-needs-digital-ecosy-interview-517996 )

While a sensor device can replace the existing thermostat in your house or the lighting or the access locks to your doors, they are offering a new kind of augmented experience that provides information and insight that enabled better control of the wider environment or the actions and decisions within a context.

This leads to a second feature of these device, the ability to learn and adapt from the inputs and environment.  This is probably an even larger impact than the first to use infrastructure in that it’s the ability to change the outcomes is a revolution in information.  The previous idea of static information and human sense making of this data is being replaced by the active pursuit of automated intelligence from the machines we build.   Earlier design paradigms that needed to define declarative services, what IT call CRUD (Create, Read, Update, Delete) as predefined and managed transactions are being replaced by machine learning algorithms that seek to build a second generation of intelligent services  that alter the results and services with the passage of time and usage characteristics.

This leads me to a third effect that became apparent in the discussion of lifestyle services versus medical and active device management.  In the case of lifestyle devices a key feature is the ability to blend in with the personal activity to enable new insight in behavior and lifestyle choices, to passively and actively monitor or tack action, not always to affect they behavior itself. That is to provide unobtrusive, ubiquitous presence.   But moving this idea further it is also about the way the devices could merge in a become integrated within the context of the user or environmental setting.  The example of biomedical devices to augment patient care and wellbeing is one such example that can have real and substantive impact of quality of life as well as efficiency in cost of care programs with an aging population to support.

An interesting side effect of these trends is the cultural dilemma these devices and sensors bring in the intrusion of personal data and privacy. Yet once the meaning and value of if this telemetry on safety , health or material value factors is perceived for the good of the individual and community, the adoption of such services may become more pronounced and reinforced. A virtuous circle of accelerated adoption seen as a key characteristic of successful growth and a kind of conditioning feedback that creates positive reinforcement.     While a key feature that is underpinning these is the ability of the device and sensor to have an unobtrusive, ubiquitous presence this overall effect is central to the idea of effective system of systems integration and borderless information flow TM (The Open Group)

These trends I see as three laws of the next Internet of things describing a next generation platforming strategy and evolution.

Its clear that sensors and devices are merging together in a way that will see cross cutting from one industry to another.  Motion and temperature sensors in one will see application in another industry.   Services from one industry may connect with other industries as combinations of these services, lifestyles and affects.

Iofthings1.jpg

Formal and informal communities both physical and virtual will be connected through sensors and devices that pervade the social, technological and commercial environments. This will drive further growth in the mass of data and digitized information with the gradual semantic representation of this information into meaningful context.  Apps services will develop increasing intelligence and awareness of the multiplicity of data, its content and metadata adding new insight and services to the infrastructure fabric.  This is a new platforming paradigm that may be constructed from one or many systems and architectures from the macro to micro, nano level systems technologies.

The three laws as I describe may be recast in a lighter tongue-in-cheek way comparing them to the famous Isaac Asimov three laws of robotics.   This is just an illustration but in some way implies that the sequence of laws is in some fashion protecting the users, resources and environment by some altruistic motive.  This may be the case in some system feedback loops that are seeking this goal but often commercial micro economic considerations may be more the driver. However I can’t help thinking that this does hint to what maybe the first stepping stone to the eventuality of such laws.

Three laws of the next generation of The Internet of Things – a new platforming architecture

Law 1. A device, sensor or service may operate in an environment if it can augment infrastructure

Law 2.  A device, sensor or service must be able  to learn and adapt its response to the environment as long as  it’s not in conflict with the First law

Law 3. A device, sensor or service  must have unobtrusive ubiquitous presence such that it does not conflict with the First or Second laws

References

 ·       Energy conservation

o   The example of  Nest  http://www.nest.com Learning thermostat, founded by Tony Fadell, ex ipod hardware designer and  Head of iPod and iPhone division, Apple.   The device monitors and learns about energy usage in a building and adapts and controls the use of energy for improved carbon and cost efficiency.

·         Lifestyle activity

o   Motion sensor Accelerometers, ambient light sensors, moisture sensors, gyroscopes, proximity sensors.  Example such as UP Jawbone  https://jawbone/up and Fitbit  http://www.fitbit.com .

·          Lifestyle health

o   Heart rate, blood oxygen levels, respiratory rate, heart rate variability, for cardiorespiratory monitoring are some of the potential that connecting Devices such as Zensorium  http://www.zensorium.com

·         Medical Health

o   Biomedical sensing for patient care and elderly care management,  heart, lung, kidney dialysis,  medial value and organ implants, orthopaedic implants and brain-image scanning.   Examples of devices can monitoring elderly physical activity, blood pressure and other factors unobtrusively and proactively.  http://www.nytimes.com/2010/07/29/garden/29parents.html?pagewanted-all  These aim to drive improvements in prevention, testing, early detection, surgery and treatment helping improve quality of life and address rising medical costs and society impact of aging population.

·         Transport

o   Precision global positioning, local real time image perception interpretation  sensing, dynamic electromechanical control systems. Examples include Toyota  advanced IT systems that will help drivers avoid road accidents.  Http://www.toyota.com/safety/ Google driverless car  http://www.forbes.com/sites/chenkamul/2013/01/22/fasten-your-seatbelts-googles-driverless-car-is-worth-trillions/

·         Materials science engineering and manufacturing

o   Strain gauges, stress sensors, precision lasers, micro and nanoparticle engineering,  cellular manipulation, gene splicing,
3D printing has the potential to revolutionize automated manufacturing but through distributed services over the internet, manufacturing can potentially be accessed by anyone.

·         Physical Safety and security

o   Alpha Blue http://www.alphablue.co.uk Controlling children’s access to their mobile phone via your pc is an example of parental protection of children using web based applications to monitory and control mobile and computing access.

o   Keyless entry using your  phone.  Wiki, Bluetooth and internet network app and device to automate locking of physical; door and entry remotely or in proximity. Examples such as Lockitron  https://www.lockitron.com.

·         Remote activity and swarming robotics

o   The developing of autonomous robotics to respond and support exploration and services in  harsh or inaccessible environments. Examples include the NASA Mars curiosity rover that has active control programs to determine remote actions on the red planet that has a signal delay time round trip (13 minutes, 48 seconds EDL) approximately 30 minutes to detect perhaps react to an event remotely from Earth.  http://blogs.eas.int/mex/2012/08/05/time-delay-betrween-mars-and-earth/  http://www.nasa.gov/mission_pages/mars/main/imdex.html .  Disabled support through robotic prosthetics and communication synthesis.     http://disabilitynews.com/technology/prosthetic-robotic-arm-can-feel/.  Swarming robotc that fly or mimic group behavior.    University of Pennsylvania, http://www.reuters.com/video/2012/03/20/flying-robot-swarms-the-future-of-search?videoId-232001151 Swarming robots ,   Natural Robotics Lab , The University of Sheffield , UK   http://www.sheffield.ac.uk/news/nr/sheffield-centre-robotic-gross-natural-robotics-lab-1.265434

 Mark Skilton is Global Director for Capgemini, Strategy CTO Group, Global Infrastructure Services. His role includes strategy development, competitive technology planning including Cloud Computing and on-demand services, global delivery readiness and creation of Centers of Excellence. He is currently author of the Capgemini University Cloud Computing Course and is responsible for Group Interoperability strategy.

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