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Where is Technology Innovation Heading?

Today, in universities around the world, leading professors are looking for top notch PhD students and researchers to push the boundaries and explore areas that will enable tomorrow’s technology innovation. To have a preview of what the future could look like, we at Cisco asked 60 leading academic professors in Electrical Engineering (EE) and Computer Science (CS) in 25 top universities worldwide the following question: “What areas of research will you be focusing on going forward?”.

Here are 4 things, which we learned from their passionate and fascinating answers:

Moore Law

#1 – The Pending End of Moore’s Law 

The Interviewed Professors generally see Moore’s law coming to an end in the next 5-10 years (predictions of the end of the law are almost as old as the law itself…). It looks like smaller transistors can still be developed but at a high cost. Although not really about physical limits, but rather an economic issue, significant research is taking place to find alternative improvement mechanisms beyond reducing size. For example, replacing signal wires with optical signals, increasing energy efficiency, or using smarter data processing allocation between devices and the cloud.

#2: Research is Focusing on 4 Areas

The vast majority of research taking place at the top university institutions in Electrical Engineering (EE) and Computer Science (CS) falls into one of the following four areas:  

  1. Artificial intelligence: deep learning, mining of unstructured data, multi-agent communication, autonomous vehicles, robotics, human-computer interface, computer vision. 
  2. Process optimisation: software & systems engineering, processor improvements, power engineering, hardware improvement. 
  3. Cloud computing and networking: wireless communication, network engineering, software-defined networks, internet of things.
  4. Computer and information security: cryptography & encryption, network security, mobile security

#3 – Technology is Proliferating 

With the advent of the Internet of Things resulting in a growing number of connected devices impacting our life, technology is becoming increasingly embedded in society. Technologies such as big data and machine learning are in reality already playing a massive role (sometimes behind the scenes). Research will continue to drive improvements in Human-Computer Interfaces, creating new technologies that will increasingly co-exist with legacy, human controlled systems. As IT technology spills over into distant domains, it continuously expands the innovation boundaries of other industries such as healthcare and transportation.

#4 – Interdisciplinary Research is Key

Where is technology innovation heading?In many cases professors indicated that the key to unlocking the potential of technology applications is in combining research with other disciplines such as neuroscience, mechanical engineering, and social sciences. Professors also highlighted the difficulty in obtaining funding for such cross-disciplinary projects, because funding mechanisms usually expect proposed projects to fit into specific disciplines. 

In the following weeks, we will explore in more detail some of the themes that are emerging from this survey hopefully giving you out of the box ideas about the future they could potentially unlock.

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Back to the Future: Do Androids Dream of Electric Sheep?

As information consumers that depend so much on the Network or Cloud, we sometimes indulge in thinking what will happen when we really begin to feel the effects of Moore’s Law and Nielsen’s Law combined, at the edges: the amount of data and our ability to consume it (let alone stream it to the edge), is simply too much for our mind to process. We have already begun to experience this today: how much information can you consume on a daily basis from the collective of your so-called “smart” devices, your social networks or other networked services, and how much more data is left behind. Same for machines to machine: a jet engine produces terabytes of data about its performance in just a few minutes, it would be impossible to send this data to some remote computer or network and act on the engine locally.  We already know Big Data is not just growing, it is exploding!

The conclusion is simple: one day we will no longer be able to cope, unless the information is consumed differently, locally. Our brain may no longer be enough, we hope to get help, Artificial Intelligence comes to the rescue, M2M takes off, but the new system must be highly decentralized in order to stay robust, or else it will crash like some kind of dystopian event from H2G2. Is it any wonder that even today, a large portion if not the majority of the world Internet traffic is in fact already P2P and the majority of the world software downloaded is Open Source P2P? Just think of BitCoin and how it captures the imagination of the best or bravest developers and investors (and how ridiculous one of those categories could be, not realizing its potential current flaw, to the supreme delight of its developers, who will undoubtedly develop the fix — but that’s the subject of another blog).

Consequently, centralized high bandwidth style compute will break down at the bleeding edge, the cloud as we know it won’t scale and a new form of computing emerges: fog computing as a direct consequence of Moore’s and Nielsen’s Laws combined. Fighting this trend equates to fighting the laws of physics, I don’t think I can say it simpler than that.

Thus the compute model has already begun to shift: we will want our Big Data, analyzed, visualized, private, secure, ready when we are, and finally we begin to realize how vital it has become: can you live without your network, data, connection, friends or social network for more than a few minutes? Hours? Days? And when you rejoin it, how does it feel? And if you can’t, are you convinced that one day you must be in control of your own persona, your personal data, or else? Granted, while we shouldn’t worry too much about a Blade Runner dystopia or the H2G2 Krikkit story in Life, the Universe of Everything, there are some interesting things one could be doing, and more than just asking, as Philip K Dick once did, do androids dream of electric sheep?

To enable this new beginning, we started in Open Source, looking to incubate a project or two, first one in Eclipse M2M, among a dozen-or-so dots we’d like to connect in the days and months to come, we call it krikkit. The possibilities afforded by this new compute model are endless. One of those could be the ability to put us back in control of our own local and personal data, not some central place, service or bot currently sold as a matter of convenience, fashion or scale. I hope with the release of these new projects, we will begin to solve that together. What better way to collaborate, than open? Perhaps this is what the Internet of Everything and data in motion should be about.

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