With today’s computer you are unlikely to reach with your hand inside your jacket, take out a roll and unroll it saying “Let me unroll my computer”.

The Plastic Logic Paper Tablet

We have seen, also discussed in this blog, a number of inventions of ways to use plastic, or plastic support, to design electronic circuits as well as foldable screens.

But now Plastic Logic is demonstrating a Paper Tablet, shown in the photo on the left.

They called it a PaperTab (short for Paper Tablet I guess) and they developed it in conjunction with the Human Media Lab at Queen’s University. The tablet is powered by a second generation Intel® CoreTM i5 Processor.

Interestingly, but not surprisingly since the Human Media Lab was involved, they are also proposing a new paradigm of interaction for this tablet that looks and feels like a sheet of paper. Rather than the usual screen with several applications on it that you select and run, here the idea is that every “sheet of paper” (every PaperTab) contains just one application. If you need to change application you get another sheet. May be one with a different colour.

Clearly you might end up with hundreds of sheet but on the other hand how many apps are you actually using most of the time. Just a few, and it might make sense to characterise each of them with a specific sheet!

Something that puzzles me is how thin it is, well like a sheet of paper, and the fact that to plug in a connector you need to have a bulge! But probably it will be just a matter of time and we will get rid of the connectors and of the bulge!

I have to confess that I am not really buying into the idea of one application – one sheet, but on the other hand it is interesting to think that form (media) can really change a paradigm we have been taking for granted for many years.

Ask the question to a person and he is very likely to tell you 2+2 makes 4. BUt you cannot be 100% sure he will tell you that. Ask a little kid and the probability he will come up with a different answer increases. Now ask a computer. It will keep telling you 4, over and ver (which is good, by the way). This observation points out the fact that computers don’t work like brains and although in certain areas computers do a better (and faster) job than brains in other it is quite the opposite.

As an example it is easier for us, humans, to recognize a face than it is for a computer, to recognize subtle emotion expressed by a voice or facial mimic, although they are catching up faster by leveraging the tremendous computational capacity of today’s chip.

Scientists have been working to create new processing architectures (the so called “non-von Neumann” architectures) that can provide capabilities similar to the brain. The first attempts tried to mimic the brain neural structure, and that resulted in neural networks computation.. Results have been interesting (for a while, progresses in voice recognition benefitted from these new processing approaches, although the neural networks were mostly simulated, running on von Neumann architectures).

Other approaches tried to merge silicon with bio substances, like neurons (but the problem here lies in the short time span of working and also on the very low capacity…).

Schematics of a reservoir computer

The advent of memristors has opened up a new path to non von Neumann architectures. Like neurons, memristors react based on the signal received AND on the remembrance of previous signals. Now a group of scientists is proposing a new architecture that has similar properties of memristors and they have called it “reservoir computing”.

An article on Technology Review Physics airXiv Blog presents the first demonstration of an opto-electronics reservoir computer. In a nutshell, it is a structure containing many reservoirs, single processing cells, connected in a random way through feedback loops. Feedback loops exist in nature and our processing is based on feedback loop, although we might not think about it. Every single action our brain activates is trimmed and finely tuned based on feedback the brain (and final cord centers) receives leading to a continuous adaptation. You grab a glass and your fingers put the exact pressure to hold it. This pressure depend on the texture of the glass surface (is it slippery?) on the weight of the glass and its content, on the position of your arm and body and so on.

Feedback loops lead to extremely complex behavior and in a way they also generate unpredictable behavior (you cannot predict the exact force that will be applied by your fingers when grabbing a glass). More than that, this behavior is adaptive, flexible.

Being able to create such processing capacity in a machine opens up the possibility to much more subtle reactions, actually to an interaction that is much more similar to ours.

We are going to see plenty of these new processing architectures in the future as we are transforming our ambient into something that is much more in synch with us.

There have been a number of talks about carrying around your data in a flash pen on the assumption that you can find a computer anywhere to process your data. Some companies have also developed flash pens embedding an Operating System to allow running a sort of virtual machine on a processor.

Now a UK company, Raspberry Pi, has developed a computer in a flash pen to bring processing capacity to other devices enabling them to process information, like a television.

It runs Ubuntu and Open Software in a package costing just 25$. It does not have any screen but a HDMI socket to connect to a television, with related 1080p30 H.264 decoder, a USB2.0 and an SD card slot.

Only a few years ago this package would have asked over 1,000 $. This is what amazes me most, and this is what is driving the ICT revolution.

A recent article on Technology Review presents a new technique, actually the merging of several techniques, to visualize brain structures in a way that singles out the way each neurons behaves and the way a certain function is performed, or, better, enhacted.

The resulting images are beautiful and made me think about complexity made simple, as well as how complexity can be completely masked by habits and interfaces.

A half millimeter square of a mouse brain. Blood vessels in red

Our world is tremendously complex, there is not a single area in modern world that is simple although most of the time we do not perceive the complexity and this mislead us to think that there is no complexity. Typically, when you are “expert” in a certain area you know the nooks and crannies and understand the hidden complexity. Since we are not expert in most areas we just see the simple face they present, be it an airport, a car, a department store. What could be easier than placing a box of candies on a shelf and have people picking up what they want. Well, there is a tremendous complexity hidden in that shelf (how the procurement is made, what is the delivery chain,…) and in that box (how it is packaged, how each single candy is made, what is the supply chain for sugar and flavor,…) not to mention all the regulations involved.

And the world is getting more complex by the day. As connectivity grows, something taking place here can influence something that at first sight looks completely unrelated. And still, everything seems so simple.

Same goes for our brain. There are so many levels of interconnected complexity, how were those neurons made in the fist time, how did they ended up where they are now, how are they connected, what is the global implication of something going on in that neuron, is it just connected to a function or does it subtly influence its surrounding and beyond?

These new techniques of looking inside they brain represent a step forward to understand how we understand. But they are, I feel and this is the reason why I decided to post it, a step towards a better understanding of our world and of understanding what we are actually doing in terms of global implication.

The techniques, particularly the mathematical analyses that is being developed, are likely to help us in a broader context because through connectivity we are making Gaia more and more similar to our brain.

Emotional Computing is a relatively new branch of computer science aiming at providing computer with a sense of emotion, not just understanding what one is saying but also interpreting the way it is being said to capture the hidden meaning, the emotion associated with it. Some interesting studies have been made at the Media Lab in the last few years.
Now, at the University of Cambridge, in the UK, a team of researchers is focussing on this topic.
Research on Emotional Computing

Interestingly, the researchers are cooperating with other researchers studying autisms since the understanding of the way to display emotions is crucial to program a computer to read emotion on our facial expressions and on the tone of our voice.

The aim of the research is not to have computers that can better “chat with us” rather to have systems that can spot problems once we interface with them. A car onboard system able to detect confusion in a driver can take appropriate steps and “interpret” the command given by the driver accordingly.

Escherichia Coli bacteria with an unexpected twist may become logic gates

Researchers at the UCSF (University of California at San Francisco) have announced they discovered a way to use Escherichia Coli bacteria as programmable computers. Each bacterium can be logic gate behaving like a silicon one.

Using genetic engineering the researchers have managed to build into the bacteria cell a molecular system that behaves as a logic gate and interact with other bacteria like logic gates connected by an electronic circuit. The idea is not to create a computer using bacteria rather than transistors, rather to be able to program bacteria in an easy and predictable way.

The possibility of programming cells means to be able to exploit 4 billion years of evolution. We are already using bacteria to help recovering from disasters like the oil spill in the Gulf of Mexico. To do that genetic engineers have manipulated their DNA to have them eat and process oil decomposing it into a harmless set of molecules.  The process is complex and this result at the UCSF may open the way to a much easier way of programming bacteria.

http://news.ucsf.edu/releases/ucsf-team-develops-logic-gates-to-program-bacteria-as-computers/

The implications may be enormous in many area, from health care to energy. As an example, in health care doctors might eventually be able to program the trillions of bacteria we host in our body to help us fighting cancer, in energy we re already looking for bacteria to generate biofuel from waste at an industrial rate.

Of course, one has to wonder what would be the effect of hackers hijacking bacteria ….

Computers work by moving electrons through their circuits and electrons are (relatively speaking) slow. Actually the electromagnetic field generated is lightning fast but the circuitry works on the actual movement of electrons (currents). It would be good if one can get rid of electrons and just based the computation on the electromagnetic field. Unfortunately one is related to the other.
However, light (that is photons) is an electromagnetic field and if we can use it as the bases for information computation in a chip it would lead to a tremendous leap forward in performance. Compare the difference in performance that we have been able to have moving from the ADSL (that is based on electrons) to the fibre (that is based on photons).

In the last few years we have seen some enabling technology bringing photons on silicon, that is on chip. By mixing gallium erbium with silicon (not an easy feat to marry these substances because of their different physical characteristics) we have been able to develop laser and photodetector on a silicon chip. But that is not enough. What is needed is the capability of processing light without converting it first into electrons.

It is such a complex area that it has been given its own name: nanophotonic on a chip.

Today we have reached petaflop processing capacity (one million billion instructions per second) by clustering thousands of processing chips performing parallel computation. The bottleneck is in their interconnection and in the fact that not everything can be processed in parallel, hence the need for communications among the chips.

This week IBM researchers have announced a breakthrough: a way to use waveguides instead of wires (copper connection at micro scale) within a chip.

http://domino.research.ibm.com/comm/research_projects.nsf/pages/photonics.index.html

IBM CMOS Integrated Silicon Nanophotonics Technology

This kind of chips will not just be faster, they will also consume much less power since photons do not generate heat (at the same level of electrons).

According to IBM researchers this technology can leapfrog present day processing capacity by a thousand fold bringing us into the exascale era (a billion billion instructions per second). How far are we from that? 8 years, according to IBM. And a 1000 folds in 8 years is faster than the Moore’s law (it would be 50 folds only at the Moore’s law pace)!

By the way, an exascale computer, according to estimate of Ray Kurzweil, would be running at 100 times faster than our brain (however speed is not everything!), whose processors numbers in the 100 billions and connections in the 1000 trillions.

As it is difficult to imagine the breath of thoughts it is difficult to imagine what such processing power would enable.

But there is more. Processing, storage and transmission are tightly meshed and the different proportion of each of them has deep effect on communications and on communication infrastructures. It would be naive to believe that Next Generation Networks will be unaffected by these changes in those basic technologies performances. A full optical communications extending within the chip itself shrinks the Earth to a ball whose points are never farther apart than 0.07 seconds. Add to this unlimited storage and you can start imagining a world where switching may no longer be needed since every place on the Earth may potentially share the global information space and meaning is no longer the result of information processing rather the state of information being used.

A really strange architecture to imagine. Luckily enough we are already studying this kind of architecture in neuroscience: our brain.

I remember when I was young the awe of lay people when confronted with computers. A machine that could calculate with blazing fast precision was something out of this world. We used to call them, at least in Italian, Electronic Brains. And some scientists were forecasting a time when this electronic brains indeed would match our reasoning capabilities and even surpass them. Some are seeing this as happening right now and most agree that in the next decade we will have computers passing the Turing test, becoming indistinguishable from humans in terms of reasoning.

But now there is an unexpected twist to this vision of an electronic brain.

Brain electrode to interface neurons with a computer

http://www.technovelgy.com/ct/Science-Fiction-News.asp?NewsNum=3025

MIT’s Technology Review picks up the discussion on brain coprocessors, computers that can be associated with our brain to increase its performances and provides arguments for its feasibility and the need for some standard architecture that can foster this goal.

The progress in bioengineering is making it possible to probe the brain with a resolution of a few neurons and it is expected we will be able to interact with a single neuron. Even if this will not be viable in a short time, the plasticity of our brain can provide turn-around to this lack of resolution and make it possible to intercept signals coming from external probes and process them. Couple this with the increasing capability to analyze what is going inside our skull and you get a human computer interface at the processing level.

This is what scientists have start to address as a brain coprocessor, a computer connected to our brain that can augment its processing capabilities. Clearly this would open up science fiction scenarios, such as the ones depicted by Douglas Hofstadter in “The Minds’ I” (a must read book on the philosophy of mind).

We are not there yet, or are we?

In fact, and this is what the authors discuss in the paper, if we just relax the requirement to have a physical interconnection between a physical brain and a computer we are already getting very close to this “brain coprocessor”. IT evolution can get us even closer in just a few years.

The capabilities to appreciate the context by a computer and to process information about a person, his experiences, make possible to have sophisticated interactions.

In reality we are getting to the point that these interactions become part of our decision process and effectively we act as if we have a brain coprocessor plugged in. Actually, I feel easier with this sort of loose connectivity than thinking of having a hard connection between my brain and a computer.

I guess that as long as the brain coprocessor lives in a shade and I do not feel like I am basing my decision on that I would feel ok. This, by the way, is already happening for airplane pilots that land a plane on a foggy runway using computer eyes to tale decisions. This happens seamlessly and most pilots would tell you that they are landing the plane without perceiving any intrusion from the computer(s). It will happen soon to us, driving cars with computer assisted driving and enhanced vision (projecting obstacles on the windshield).

On the other hand, the more transparent this brain coprocessor is going to be the more issues will emerge. Who’s going to take responsibility if something goes wrong? Can we tell “not my fault, it was my brain coprocessor that went awry!”?

I am sure we are moving in this direction as we are transforming our ambient into an aware entity and as a consequence we will adapt subtly our behavior to this new dimension. It is a new world with unexpected twists awaiting for us.

I want to mention an interesting sort of computer made with pipes embedded in plastic I saw at the recent ICT 2010 in Brussels.

As it is visible in the photo I took it is made by two sheets of plastic engraved to form pipes, cisterns and to lodge micro pumps.

The plastic - pipes based computer

This device, a prototype at this time but almost ready to go in operation, has been designed as a chemical processing lab. It has some reservoirs for the reagents and one input to insert the blood of a patient. Depending on the type of analyses the blood is pushed by the pumps in the cisterns to be mixed with the appropriate reagents and at the right time it is moved forward for the subsequent step. At the end it reaches the detection spot where light from a laser is diffracted onto a set of diodes. These are not part of the device but reside in the external interface of a normal computer that will derive the result of the analyses.

The chemical processing lab is designed to be very cheap, few euro max, and it is thrown away once the analyses is completed thus avoiding any contamination risk and danger to the environment.

I was at a panel on road-mapping the future of Digital Society in Brussel at ICT2010,

http://ec.europa.eu/information_society/events/ict/2010/

and I had the pleasure of listening to a fantastic presentation given by Henry Markram, a neuroscientist from the Ecole Politechnique of Lausanne, making parallels between the (our) brain and ICT.

One of the point that was raised is that by 2020 we could have computers with the power to simulate a  brain (in 2005 we had the power to simulate a single neuron, today we can simulate hundred millions  neurons). With 2007 technology that 2020 computer would require 3GW of power to work. IBM, Cray and SGI are working to develop computation technologies that can achieve that processing power at just 20 MW. That is impressive, a decrease of 150 times in energy consumption. But according to the presentation I heard our brain only needs some 30W to crunch information. That is 100 million less times energy than today’s technology and almost a million less energy than those promised by technologies we are studying today.

An interesting observation made by Henry in the presentation is that the evolution of ICT is leading to performances similar to the brain  following an almost linear progression. However, if we can manage to really mimic the brain that would lead to a revolutionary progress. In particular there are some characteristics of the brain workings that are not present in today’s ICT, although they are getting more an more desirable and important, such as resilience (a brain can lose up to 50% of its neurons and you hardly notice it), imaginery (the brain sees what it is processing and therefore can make smart decision on what and how to process), storage (the brain stores fragment and reuses what it has already stored, thus both saves and makes information much more robust), processing (the brain computation is a state change and as such it remembers and builds on all previous computation, it learns).