Futurist Ray Kurzweil made a thought-provoking presentation at the recent MD&M in Anaheim, a trade show for medical-device companies. His presentation dealt with the accelerating rate of technical progress and predicting the future. While Kurzweil’s remarks were focused on the medical industry, he conveyed his most significant idea in his discovery of what he calls the Log of accelerating trends.
Although he made no comment on how the trend applied to the wind industry, he did provide its application to the solar industry, and perhaps from that we can make some predictions about the wind industry.
From the presentation
Technical developments form predictable trajectories, and those trajectories are exponential, said Kurzweil. Consider the progress of the computing industry. The accompanying graph starts with the 1890 American census and progresses to 1980. “The calculations possible per second versus year formed a remarkably smooth curve. It is doubly exponential. That is, the 1980 census was many times more the price/performance of the 1890 census. The progress went up through thick and thin, through war and peace,” said Kurzweil.
“These are some of the implications of what I call The log of accelerating trends. For medical designers, the technology is getting smaller and that’s another exponential trend. So, this computer here (raising his cell phone) is several billion times more powerful per dollar than the computer I used as an undergraduate at MIT. I went to MIT because it was so advanced that it actually had a computer in the late 60’s. It took up the floor of a building. Still, this cell phone is thousands of times more powerful, and one millionth the cost. That’s a several billion-fold increase in price-performance. The phone is also a tiny fraction of the 1960 computer’s size,” he said.
Both of those things (smaller and more powerful) will happen again over the next 25 years. This will produce products a hundred thousand times smaller, a billion times more powerful, and price-performance that gives some idea of what will be feasible.”
Both scales in the accompanying graph are logarithmic. “As you go up the Y axis, each labeled level is a hundred thousand times greater than the level below it. We’re not adding to what we’re measuring, we’re adding zeros, calculations per second per constant power. People look at this and say, ‘Ah, Moore’s Law,’ but Moore’s Law is just a part on the right. It was the fifth paradigm, and not the first to recognize the exponential growth of computing,” said Kurzweil.
For instance, vacuum tubes were shrinking in the 1950s. Every year in the 1950s, industry made the vacuum tubes smaller to keep this exponential growth going. That hit a wall in 1959. “We could not shrink the vacuum tubes anymore and keep the vacuum. That was their end, but it was not the end of the exponential growth of computing. We just went to the fourth paradigm, transistors, and then to microprocessors.”
Exponential growth started decades before Gordon Moore was even born. “It’s a doubly exponential curve because a straight line on a logarithmic scale is exponential growth. People have been saying for a long time, ‘Moore’s law is going to come to an end.’ It will in 2020 because its key features then will be five nanometers, which is the width of twenty carbon atoms, and we won’t be able to shrink them anymore,” he said.
However, enter the sixth paradigm, which is computing in three dimensions. “Our brains are organized in three dimensions which is really one key source of its power. Most interesting thing about this is: Where’s the slowdown in World War I, World War II, the Cold War, or the Great Depression? People say, well, it must have slowed down during the recent recession. I’m sure this group (the audience) realizes, that it’s not the case. It has a mind of its own. But it’s really the empirical evidence that’s the most persuasive. Just look at how clear a curve this is. I have data from 1980 projected out to 2050, we’re now at 2016, thirty-five years later, and it’s exactly where it should be. This aspect of the future is remarkably predictable.”
Time magazine published a cover story on Kurzweil’s Law of Accelerating Returns. “Its editors wanted to put my computer graph in the magazine along with a particular computer it had covered in the magazine as the last point. It’s the last point right on the curve, (referencing the accompanying curve) which I had laid out thirty years earlier. This aspect of the future is just amazingly predictable,” he said.
It’s not just Moore’s Law and it’s not just computing. It pertains to any information technology. (Editor’s note: SCADA or CMS in wind turbines) For instance, you could buy a transistor for $1 in 1968. Today, you can buy ten billion for a dollar, and they’re better because they’re smaller so electrons have less distance to travel, so they’re faster. The cost of a transistor cycle, which is a measure of price/performance of all of electronics, doubles every year. “You can get the same computation, communication, genetic sequencing you could last year, for half the price, this year,” said Kurzweil
Economists actually worry about deflation or falling prices, and the curve does represent a 50% deflation rate. “But it’s just for the part of the economy having to do with information. That part of the economy is gradually expanding.
He returned to the topic of deflation. “The world economy suffered from massive deflation during the Depression in the 1930s, along with the collapse of consumer confidence. But if you cut the price of something in half, most people will buy more of it. That’s economics 101. But what if I actually double my consumption year after year to keep up with this 50% deflation rate? If I don’t, the size of the economy will shrink … not in bits, bytes, or base pairs, but in terms of currency. For a number of good reasons, that would be a bad thing. The good news is: That’s actually not what happens.”
We have more than doubled our consumption of computer memory. “There has been 18% growth in constant currency in every information technology each year for the last 50 years despite the fact you can get twice as much of it each year for the same price. What’s the reason for that? It’s what you’re all involved in: Innovation. Creating new capabilities as the price/performance makes new capabilities feasible.” (Editor’s note: If the price of electric power drops, would we not use more of it?)
Consider: Why were there no social networks ten years ago? Was it because Mark Zuckerberg was still a junior in high school? No. The reason: It was not feasible. The price/performance wasn’t there. “There were attempts to do it, and then arguments such as: ‘Can we afford to let our users download a picture?’ It just couldn’t be done. Six or seven years ago it became cost effective and took off.”
In the early ’80s Kurzweil says he noticed that the ARPANET (the Advanced Research Projects Agency Network), created by the Department of Defense, connected a thousand scientists. The number of users doubled every year. “I did the math and thought, ‘Whoa, this is going to be a worldwide web connecting hundreds of millions of people to each other and to vast knowledge resources by the late ’90s.’ Others thought that was ridiculous because the Department of Defense could only tie together one or two thousand scientists in a year. But the impact of exponential growth took over and it did happen.”
Kurzweil said he saw a need for search engines because you couldn’t find anything. The computational and communication resources to create an effective search engine would be in place by the late 1990s. “Now what I could not predict, was that among the 50 different projects to create an effective search engine in the late ’90s would be a couple of kids in a Stanford dorm who would take over the world of search. But the fact that search engines would be needed and would be feasible, was predictable.”
The internet keeps data traffic doubling every year. On the right (referring to a slide), that’s the number of bits we move around wirelessly in the world. Over the last century starting with Morse code, through AM radio, and today it’s 4G networks. It has been a trillion-fold increase but again, look at how predictable a phenomenon that is. Here’s that graph of the ARPANET in the early ’80s, and shows the exponential growth. That’s a logarithmic graph representing a billion-fold increase since the early ’80s. On the right is the same data, but on a linear scale which is how we experience it. To the casual observer, it looked like the worldwide web was a new thing. But in the late 1990s, but you could see it coming.
The application to solar energy
Nanotechnology is a whole different application but is a form of information technology: Using computers to predict the functions and properties of materials. We’re applying that to solar panels and energy storage. The costs have been coming down rapidly for solar energy for example. Google founder Larry Page and I were asked four years ago by the National Academy of Engineering to study the emerging energy technologies. We selected solar because it’s growing exponentially and has been for over twenty-five years, doubling every two years.
In 2012, solar panels were producing 0.5% of the world’s energy supply. Some people dismissed it, say, “It’s a nice thing to do, but a half percent, it’s a fringe player. That’s not going to solve the problem.” They were ignoring the exponential growth just as they ignored the exponential growth of the Internet and with genome project. Half a percent is only eight doublings away from 100%. Now it is four years later, has doubled twice again. Now solar panels product 2% of the world’s energy, right on schedule. People dismiss it, 2%. Nice, but a fringe player. That ignores the exponential growth which means it is only six doublings or six years from 100%.
Two years ago Kurzweil presented this to the Prime Minister of Israel, who had been to my class at the MIT Sloan School in the 1970s. He said, “Ray, do we have enough sunlight to do this with a doubling seven more times?” I said, “Yes. After we double seven more times, and meeting 100% of the world’s energy needs, we’ll still be using only one part in 10,000 of the sunlight that we have.” It’s not true we’re running out of energy. We’re only running out of resources if we stick with 19th century technologies.
Caption: Kurzweil’s predictions refer mostly to information technology. However, energy storage technology is of interest to the wind industry. If an 8% improvement in power density per year is correct for EV batteries, the next doubling will come in 9 years. So, for example, by 2024 (and possibly sooner) the Chevy Bolt, which now has an advertised range of 200 miles will be capable of 400. The success of EVs will demand more electric power, and that will be good for the wind industry.
A connection to cloud computers
Our brains are already connected to the cloud… indirectly. “I’ve got to use my fingers, my eyes, and ears for this device, but it really is a brain extender. A kid in Africa can access all of human knowledge with a few keystrokes. They’re making us more productive and more intelligent. This will go directly to our brain in the 2030s. It won’t just be a direct connection to search engines in the cloud. We’ll literally expand the scope and capability of our brain,” he said.
“What’s more, we’re going to do it again by connecting the top of our neocortical hierarchy to the cloud. We will add a sophisticated synthetic neocortex in the cloud. I believe we understand how these modules work.” For predictions, Kurzweil suggested that we’ll create more beautiful music and create a language that will have more insight into science, it will be funnier, and so on.
A computer gets the joke
Here’s an application to language. “This example comes from IBM. Watson (IBM’s more advanced version of Apple’s Siri) recently won a Jeopardy (a TV game show) tournament against the best two players in the world. Watson got this query correct in the rhyme category: The answer: “A long, tiresome speech delivered by a frothy pie topping.” Watson quickly responded with the question: “What is a meringue harangue?” That’s pretty good. The two human contestants didn’t get that. In fact, Watson got a higher score than the two of them combined. What’s not widely appreciated was Watson got his knowledge not by being programmed by the engineers but actually by having read Wikipedia and other encyclopedias: 200 hundred million pages of natural-language documents.
A more complete presentation that Kurzweil gave to the audience of medical designers appears here: http://goo.gl/RwmiK1
We have to grasp at the implications of Kurzweil predictions for the wind industry. Consider turbine maintenance. My guess is that if a virtual wind technician with the smarts of IBM’s Watson were available to each wind farm, it will do the trouble shooting while human wind techs will provide the corrective action. GE and others have suggested approaches to wind-farm operations from the perspective that the entire wind farm is the plant. The ideas of big data and the Internet of Things are still new but offer similar promise. Their implementations may lead to greater efficiency and lower cost power.
In a couple decades, should a wind technician select a neocortical implant for a direct connection to cloud computers, that person won’t need a Watson, but then the tech may be too valuable to climb towers.
For OEMs, the implications in the near term are much smarter controls. It is difficult to imagine designing turbines smaller yet producing the same or more power, but such events are not limited by my imagination.
If you’ve read this far, you might also be interested in this article from Kevin Kelley: Was Moore’s Law inevitable? In the article, he recalls in the 1950s, after recognizing accelerating trends in aerospace and early electronics, trying to grasp their implications, and how early predictions fell far short of what actually transpired.
Filed Under: Innovators & influencers, News, O&M
It’s called the Law of Accelerating Returns, not log of accelerating trends. Though to be fair, most of his data is usually presented in logarithmic graphs, and showcases trends. A close paraphrase, but not “what he calls” it. Otherwise well written and well researched.
Brad Arnold says
Let me add that the modern illiteracy is the inability to learn, unlearn, and relearn, given new evidence. Please quit your infatuation with wind and solar. Do you understand with the about of energy that “quantum fusion” could provide we could feasibly remove the excess carbon from the air and water? That is just the beginning of the engineering marvels that this technology would enable if you would just accept the scientific evidence that cold fusion is a reality.
Brad Arnold says
I laugh at the binary solar vs wind fear. Oh no, solar will beat out wind! Let me set you straight: there is a new energy technology that gives a power density of 10 to the 5th over burning fossil fuel. That is because it is nuclear, but doesn’t produce either radiation or radioactive waste, and uses common material as fuel. The fomula was just published open source by the MFMP (Martin Fleischmann Memorial Project). Obvious, once scientists give up their irrational prejudice against cold fusion (otherwise known as LENR or quantum fusion), this will beat both solar and wind hands down.
And here’s the recipe in short form, as published by MFMP on February 24, 2016. For further details, please visit Quantumheat.org:
Prepare thoroughly (Ni + LiAlH4 + Li)
1. Bake Ni
2. Reduce Ni
3. Hydrogenate Ni
4. Mix: Ni + LiAlH4 + Li
5. Bake and vac reactor, add Mix, vac warm, add H2, Vac
6. Heat to above Mössbauer determined Ni Debye (say 135C), pressure regulated to approx 1bar abs.
7. Hold, pressure regulated to approx 1bar abs.
8. Heat slowly to as close to Ni Curie as comfortable (Say 340C), pressure regulated to approx 1bar abs.
9. Hold, pressure regulated to approx 1bar abs.
10. Slowly lower temp to above highest known Ni Debye (Say 220C), pressure regulated to approx 1bar abs.
11. Hold, pressure regulated to approx 1bar abs.
12. Go as fast as possible through Ni Curie
13. Hold, pressure regulated to approx 0.5bar abs.
14. Cycle through 500C internal, pressure regulated to approx 0.5bar abs.
15. Hold, pressure regulated to approx 0.5bar abs.
16. Raise internal temperature to over 1200, pressure regulated to approx 0.5bar abs.
17. Drop to around 1000C and hold, pressure regulated to approx 0.5bar abs.
18. Raise internal temperature to near boiling point of Lithium
Some of the above steps may in time be redundant.