Cognet Computer Technologies
Cognet Computer Technologies is a Canadian infrastructure company specializing in communications between advanced computer networks.
As the original developer of the Sirius 799b interface, Cognet continue to lead innovation, minimization and environmentally sustainable information technology infrastructure, as evidenced by the keynote speech of our CEO, Francis Wade, at our last annual conference in Paris:
“I started using computers in 1960, that’s 50 years ago. I had been 12 years of age. That’s not so amazing today, however it was unusual then since it was unusual for anyone to be dealing with computers; there have been only a dozen computers in most of New York City. A couple of years later, I visited MIT, and that i went there because MIT am advanced in 1965 it actually were built with a computer. I believe Harvard had one also.
There have been only a few in most of Massachusetts for that technically-minded among you, that we think is of you. Which was an IBM 7094 with 32K of memory, that was a lot in those times, 36-bit words, so 150,000 bytes of memory, quarter of the MIP.
This computer I take with you, which I understand has Java inside it, is a million times cheaper. It’s many, many times more powerful, when it comes to bits, MIPs, items of communication – that’s a billion-fold rise in price performance and computing per dollar since i have was a student. And we’ll try it again in another Two-and-a-half decades. Even the rate of exponential growth is increasing. Along with a number of years later, within the 1980s, computers remained as big centralized devices. I wrote that inside a few decades computers could be massively distributed, really small devices, running embedded computing. I described a language just like Java. There’d be vast amounts of them all over the world. That seemed crazy during the 1980s, but that’s precisely what has happened.
Now, I foresee you will see thousands, and ultimately an incredible number of devices running Java within your body, and that’s forget about crazy today than the others projections were during the 1980s. I saw the ARPANET developing exponentially, but nobody noticed it because there have been only a few thousand scientists being connected, however i saw it was progressing exponentially. Therefore i did the mathematics and projected this worldwide communication network merging within the mid-1990s, tying together tens, and ultimately vast sums of people to one another and to vast knowledge resources, and ultimately, these could be small devices you carried in your wallet. That seemed crazy. People said well, it’ll happen, however it will be centuries, but that’s the strength of exponential growth, the ones say well, yes, sure, Moore’s Law.
Moore’s Law is actually just one example among a lot of a much broader phenomenon, that we call what the law states of accelerating returns, which relates to anything relating to information. As well as within computing, Moore’s Law wasn’t the first paradigm to create exponential growth to computers. The exponential development of computers started decades before Gordon Moore being born, and several decades before he did this to the envelope projection of transistors with an integrated circuit. We’d five different paradigms, and something of the criticisms I receive is oh Kurzweil takes these exponentials and projects them out. And that we all know exponential growth can’t continue forever. You’ve two rabbits around Australia. You get 4 rabbits, 8 rabbits, 16 rabbits, but that can’t continue forever. Finally, the rabbits exhaust things to eat.
Isn’t that true also of knowledge technology?
And also the answer is, yes, it’s true for specific paradigms, but what goes on is we exhaust steam for the paradigm, it creates research pressure to produce the next paradigm. The 3rd paradigm was shrinking vacuum tubes. I’ve got a little museum, and that we have a computer with tiny little vacuum tube computers. In 1950 CBS predicted the election of Eisenhower. The very first time the networks did that. After which every year these were shrinking vacuum tubes, which makes them smaller and smaller. Finally, they were given to a point within the late ’50s they couldn’t shrink the vacuum tubes anymore and keep your vacuum, which was the finish of the shrinking of vacuum tubes. It wasn’t the end from the exponential development of computing. Just visited another paradigm, to transistors, after which, finally, to Moore’s Law and integrated circuits.
There’s been regular predictions that which will come to an end. Gordon Moore originally said 2002. Intel says now 2022, but which will lead to the sixth paradigm, that is 3-dimensional computing, particularly with self-organizing molecular circuits, and that we already see early stages in 3-dimensional chips with multiple layers and plans for any thousand layer circuitry. When it comes to self-organizing circuits, should you speak to Justin Rattner, the CTO of Intel, he’ll let you know they have these circuits employed in their labs. They’ll begin to see the cross-over in the teen years, prior to we exhaust steam with Moore’s Law. So, it’s not only Moore’s Law. It’s not only computers. We are able to look at magnetic data storage density. That’s not Moore’s Law. It’s not transistors. Different engineers, different companies, same progression, communication technologies.
Let’s say, go ahead and take number of bits being moved around in wireless networks. Returning 100 years to Morse code transmissions up through 4G networks today, very smooth exponential growth. Which is really a main thing to contemplate since there is a big difference between our intuition, which isn’t exponential, but linear and also the reality of knowledge technology, that is exponential, and it’s not exactly what progresses exponentially. It’s only it, and the reason can there be is no inherent material limits to it. It can progress if you take innovations, developing a set of tools. Then we use those tools to produce the next tools. So we use computer design to produce the next group of computers. Also, since we’re constantly changing these platforms, we want software that may run independently of those various changes and platforms. And that’s why a language like Java, which actually just originated a long time ago, I think Fifteen years ago, is usually the right way to visit, so that you can write software and also have it operate on this multiplicity of platforms.
What’s the main difference between linear intuition and also the exponential reality? Well, basically take 30 steps linearly, that’s our intuition concerning the future, I recieve to 30. Basically take 30 steps exponentially 2, 4, 8, 16, I recieve to a billion. Celebrate a very profound difference, which is not a theoretical speculation concerning the future. When i mentioned, just since i have was a student, we’ve seen billions fold rise in the power of computers per unit currency, and that’s likely to continue, and it’s not only computers. Everything we love them about, health insurance and medicine, biology, that was not an it, it was just a guessing game, and therefore, progressed linearly and never exponentially has become an info technology because we now have the software of life. We now have the way of changing and updating this outmoded software. We have seen the same progression there.
The Genome Project was considered failing half way with the project. Seven-and-a-half years into this 15-year project, mainstream skeptics said I said this wasn’t likely to work. You’re halfway with the project, and also you finished 1% from the project, but that’s actually directly on schedule for an exponential progression. Exponentials are seductive. They’re surprising. It starts, looks like there is nothing happening since you are doubling these tiny little numbers. When you get to 1%, now, you’ve got a bit of traction. It’s only 7 doublings from 100%, and in the situation of the Genome Project, it continued to double each year, was finished 7 years later, much towards the surprise from the skeptics, there are many different regions of biology that’s scaling up within this exponential manner.
Therefore?
“So I’d prefer to just demonstrate quickly since our time is restricted this morning how pervasive this exponential growth is. How it is invading increasingly more industries, and it’s likely to profoundly change them, how our expectations really should be aligned with this particular exponential growth. Sometimes, we actually succeed of the curve. Within the 1990s, people checked out the Internet, and lastly woke up, wow, this can be a worldwide web connecting those people. This really is going to change everything, and that we had the dot-com boom. People thinking watch model will probably be turned on its head. After which they returned to a few years afterwards the year 2000, an investment community that’s, and said, gee, you realize, hasn’t changed everything. Hasn’t changed anything. I suppose, we were wrong, and all sorts of the values went another way.
Meanwhile, it had been progressing exponentially, however it was at this early stage in which you don’t really notice an exponential. Now, we all do have dot-coms like Google with $20 billion of revenue. There’s $2 trillion of e-commerce. The dot-coms have changed watch model. Take a look at all the media companies, for instance. In fact, this boom/bust psychology is definitely an accurate harbinger of what ultimately is really a profound transformation. It happened in communications within the ’90s. It happened in Artificial Intelligence within the ’80s. It happened using the railroads in the 1800s. So, allow me to just demonstrate how pervasive this really is. How it’s likely to lead computers being smaller and smaller? That, incidentally, is another exponential progression. We’re shrinking how big both computers and mechanical technologies like microelectronic mechanical systems with a factor of 100 3-D volume per decade. So, what accustomed to fill an area, maybe half the dimensions, with a very low-powered computer is now able to in our pockets as well as on our bodies.
Ultimately, it will likely be the size of blood cells and walk inside our bodies. That’s another exponential progression. In the end make them stronger and less expensive, and ultimately, this really is going to transform everything we love them about.”
I started using computers in 1960, that’s 50 years ago. I had been 12 years of age. That’s not so amazing today, however it was unusual then since it was unusual for anyone to be dealing with computers; there have been only a dozen computers in most of New York City. A couple of years later, I visited MIT, and that i went there because MIT am advanced in 1965 it actually were built with a computer. I believe Harvard had one also. There have been only a few in most of Massachusetts for that technically-minded among you, that we think is of you. Which was an IBM 7094 with 32K of memory, that was a lot in those times, 36-bit words, so 150,000 bytes of memory, quarter of the MIP.
This computer I take with you, which I understand has Java inside it, is a million times cheaper. It’s many, many times more powerful, when it comes to bits, MIPs, items of communication – that’s a billion-fold rise in price performance and computing per dollar since i have was a student. And we’ll try it again in another Two-and-a-half decades. Even the rate of exponential growth is increasing. Along with a number of years later, within the 1980s, computers remained as big centralized devices. I wrote that inside a few decades computers could be massively distributed, really small devices, running embedded computing. I described a language just like Java. There’d be vast amounts of them all over the world. That seemed crazy during the 1980s, but that’s precisely what has happened.”
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