Now, this is starting to happen in transistors.

Whole different paradigm transistors came out of the woodwork.

At this point in time, our processor is getting faster every generation because we're running our transistors faster, or instead because we have more transistors available for computation?

We went to the fourth paradigm, transistors, and finally integrated circuits.

Japan did not make transistors then and Emperors did not bow.

Now, in a few years time, by 2015, we will shrink transistors so much.

And these transistors are behaving essentially just like ion channels behave in the brain.

Polymeric transistors have been developed that can be used in rather simple integrated circuits.

A quadrillion transistors is almost the same as the number of neurons in your brain.

Transistors are getting smaller to allow this to happen, and technology has really benefitted from that.

The way that silicon behaves, the fact that you can build transistors, is a purely quantum phenomenon.

You can make both p and n type semiconductors, which means you can make transistors out of them.

Now, what's happening is that as transistors are getting smaller and smaller and smaller, they no longer behave like this.

And more than that, it's a confection of different ideas, the idea of plastic, the idea of a laser, the idea of transistors.

Moore's Law was just the last part of that, where we were shrinking transistors on an integrated circuit, but we had electro mechanical calculators, relay based computers that cracked the German Enigma Code, vacuum tubes in the 1950s predicted the election of Eisenhower, discreet transistors used in the first space flights and then Moore's Law.

And we take it for granted now, that each of these machines has billions of transistors, doing billions of cycles per second without failing.

But by the teen years, the features of transistors will be a few atoms in width, and we won't be able to shrink them any more.

So now the neurons are represented by little nodes or circuits on the chip, and the connections among the neurons are represented, actually modeled by transistors.

And a current integrated circuit might have in each one of these chips something like a billion transistors, all of which have to work perfectly every time.

They're faster, so you've got exponential growth in the speed of transistors, so the cost of a cycle of one transistor has been coming down with a halving rate of 1.1 years.

Fortunately, what motivates most significant advances in knowledge is not profit, but the pursuit of knowledge itself. This has been true of all of the transformative discoveries and innovations DNA, transistors, lasers, the Internet, and so on.

The most advanced transistors today are at 65 nanometers, and we've seen, and I've had the pleasure to invest in, companies that give me great confidence that we'll extend Moore's Law all the way down to roughly the 10 nanometer scale.

So without that curiosity driven understanding of the structure of atoms, which led to this rather esoteric theory, quantum mechanics, then we wouldn't have transistors, we wouldn't have silicon chips, we wouldn't have pretty much the basis of our modern economy.

So here's the specifications, just as if you were to make up a spec sheet for it 170 quadrillion transistors, 55 trillion links, emails running at two megahertz itself, 31 kilohertz text messaging, 246 exabyte storage. That's a big disk.

And one of the astonishing predictions of quantum mechanics, just by looking at the structure of atoms the same theory that describes transistors is that there can be no stars in the universe that have reached the end of their life that are bigger than, quite specifically, 1.4 times the mass of the Sun.

Both sides cite Moore s Law, named for Intel s co founder, Gordon Moore, who noticed that the density of transistors on a chip could be doubled every 18 months. The pessimists claim that this is becoming harder and more expensive the optimists hold that the law will remain valid, with chips moving to three dimensions.

Moore s law observes the increase in computer processing power over time specifically, that the number of transistors that can be placed cheaply on an integrated circuit doubles every 18 24 months. By contrast, Eroom s law charts the regress in new drug approvals, noting that the costs of developing a new medicine double roughly every nine years.

In another hybrid discipline, molecular computing, organic or artificial enzymes are programmed to conduct complex calculations faster than silicon chips. The field could provide an avenue, alongside 3D silicon chips, for maintaining or even accelerating the pace of Moore s Law, which states that the number of transistors on the integrated circuits used by computers doubles every two years.

The brain, the computer, and the economy all three are devices whose purpose is to solve fundamental information problems in coordinating the activities of individual units the neurons, the transistors, or individual people. As we improve our understanding of the problems that any one of these devices solves and how it overcomes obstacles in doing so we learn something valuable about all three.

The brain, the computer, and the economy all three are devices whose purpose is to solve fundamental information problems in coordinating the activities of individual units the neurons, the transistors, or individual people. As we improve our understanding of the problems that any one of these devices solves 160 and how it overcomes obstacles in doing so we learn something valuable about all three.

Yet it is likely that one day we will know much more about how economies work or fail to work by understanding better the physical structures that underlie brain functioning. Those structures networks of neurons that communicate with each other via axons and dendrites underlie the familiar analogy of the brain to a computer networks of transistors that communicate with each other via electric wires.