A number of current but disappointing trends may be in the ‘short run’.
The continuation of the solar cell and battery cost curves are pretty darn impressive. Costs halving about once a decade, for several decades, is pretty darn impressive. One more decade until solar is cheaper than coal is today, and then it gets cheaper (vast areas of equatorial desert could produce thousands of times current electricity production and export in the form of computation, the products of electricity-intensive manufacturing, high-voltage lines, electrolysis to make hydrogen and hydrocarbons, etc). These trends may end before that, but the outside view looks good.
There have also been continued incremental improvements in robotics and machine learning that are worth mentioning, and look like they can continue for a while longer. Vision, voice recognition, language translation, and the like have been doing well.
Even Africa, while the population size is exploding, is growing economically—perhaps thanks to universally available cheap cellphones.
A very large chunk of this is directly or indirectly increased resource prices, especially driven by China.
If the latter, if the AI is not run at the exact instant that there is enough processing power available, ever more computing power in excess of what is needed (by definition) builds up.
If the improvement in cost-performance of computation slows dramatically in the next decade or so, this could be a small effect. Kurzweil predicts that silicon CMOS will end and be replaced by something that improves at least as rapidly, generalizing from past transitions (vacuum tubes to transistors, etc), but there are fewer data points to support that claim, and we are much closer to physical limits, with less room for miniaturization. There are new materials with plausibly better properties than silicon, room for new designs (memristors, unreliable computing, wacky new cooling systems), clever 3-D innovations, and so forth. However, a grab bag of such innovations seems less reliable than miniaturization, which automatically improves many dimensions of performance at once.
The continuation of the solar cell and battery cost curves are pretty darn impressive. Costs halving about once a decade, for several decades, is pretty darn impressive. One more decade until solar is cheaper than coal is today,
Do you have a cost curve for the price of watts delivered to the grid, instead of solar cell costs?
Solar panels are currently selling for as low as US$0.70c a watt (7-April-2012) in industrial quantities, but the balance of system costs put the systems closer to $4 a watt.
So even if the panels were free, it’s still $3.30 per watt to actually make it happen.
BOS costs have so far kept rough pace with cell costs, and the DOE has fairly credible roadmaps and prototypes for further reductions, as with cells. Part of these are regulatory costs (pointless permitting demands and the like) which can be relaxed, and have been in places like Germany.
The continuation of the solar cell and battery cost curves are pretty darn impressive. Costs halving about once a decade, for several decades, is pretty darn impressive. One more decade until solar is cheaper than coal is today, and then it gets cheaper (vast areas of equatorial desert could produce thousands of times current electricity production and export in the form of computation, the products of electricity-intensive manufacturing, high-voltage lines, electrolysis to make hydrogen and hydrocarbons, etc). These trends may end before that, but the outside view looks good.
That sounds promising for us (Australia). We have almost as much desert as we do coal!
A huge amount surely, at least for many problems. There’s no guarantee that any particular problem will be subject to vast further software improvements, though.
Can you expand on this? I suspect this is true for some classes of problems, but I’m sufficiently uncertain that I’m intrigued by your claim about this being “surely” going to happen.
A lot of existing improvement trends would have to suddenly stop, along with the general empirical trend of continued software progress. On many applications we are well short of the performance of biological systems, and those biological systems show large internal variation (e.g. the human IQ distribution) without an abrupt “wall” visible, indicating that machines could go further (as they already have on many problems).
I’m not quite sure software is well short of the performance of biological systems in terms of what software can do with given number of operations per second. Consider the cat image recognition: Google’s system has miniscule computing power comparing to human visual cortex, and performs accordingly (badly).
What I suspect though, is that the greatest advances in speeding up technological progress, would come from better algorithm that works on well defined problems like making better transistors—something where even the humans make breakthroughs not by verbally doing some i think therefore i am philosophy in their heads but by either throwing science at the wall and seeing what sticks, or by imagining it in their heads, visually, trying to imitate the non-intelligent simulator. Likewise for the automated software development; so much of the thought that human does to do such tasks is, really, unrelated to this human capacity to see meaning and purpose to life, or the symbol grounding or anything of this kind that makes us fearsome, dangerous, survival machines—things you don’t need to make for automated programming software.
Why would you expect the opposite? Tight lower bounds have not been proven for most problems, much less algorithms produced which reach such bounds, and even in the rare cases where they have been, then the constant factors could well be substantially improved. And then there are hardware improvements like ASICs, which are no joking matter. I collected just a few possibilities (since it’s not a main area of interest for me as it seems so obvious that there are many improvements left) in http://www.gwern.net/Aria%27s%20past,%20present,%20and%20future#fn3
I’m not sure really. The conjectured limits in some cases are strong. Computational complexity is unfortunately an area where we have a vast difference between what we suspect and what we can prove. And the point about improvements in constant factors is very well taken- it is an area that’s often underappreciated.
But at the same time, these are reasons to suspect that improvements will exist. Carl’s comment was about improvement “surely” occurring which seems like a much stronger claim. Moreover, in this context, while hardware improvements are likely to happen, they aren’t relevant to the claim in question which is about software. But overall, this may be a language issue, and I may simply be interpreting “surely” as a stronger statement than it is intended.
Given the sheer economic value of improvements, is there any reason at all to expect optimization/research to just stop, short of a global disaster? (And even then, depending on the disaster...)
No, not particularly that I can think of. The only examples where people stop working on optimizing a problem is when the problem has become so easy that it simply doesn’t matter to optimize further, but such examples are rare, and even in those sorts, further optimization does occur just at a slower place.
One of the ways we can kill ourselves is global warming. Replacing coal power with solar power will reduce one of the causes of global warming—namely, the greenhouse gases emitted from coal plants.
How likely is it for global warming to be an existential risk threat? This seems unlikely. It may well be that global warming will contribute to existential risk in a marginal fashion if it forces less resources to be spent on existential risk issues or makes war more likely, but that seems like a much more roundabout issue, and by that logic many other technologies would fall into the same category.
It depends what you mean by an existential threat.
I think there’s a reasonable chance that global warming (combined with other factors; biosphere degradation, resource depletion, unsustainable farming, lack of fresh water, increasing war over increasingly limited resources, ect), may cause our current civilization to collapse.
If our civilization collapses, what are the odds that we’ll recover, and eventually get back up to where we are now? I don’t know, but if our civilization collapses and we’re left without modern tools in a world in the middle of an ongoing mass extinction that we started, things start to look really dodgy. In any case, we don’t know what percentage of intelligent species go from being merely intelligent to having an advanced technology; it could be that we just passed The Great Filter in the past 200 years or so (say, at the moment the industrial revolution started), in which case losing that advance and passing back through it in the other direction would dramatically lower our chances of becoming a space-faring civilization.
Of course, if we reach a sufficiently high level of technology before the other problems I talked about kick in, then they’re all solvable.
It doesn’t have to turn the Earth into Venus for unusually-rapid climate shifts to destabilize geopolitics badly, exceed system tolerances in infrastructure, consume an ever-growing portion of the economy either by increased loss and waste or in efforts at mitigation, and thereby effectively amp up the power of many other forms of global X-risk (or just contribute directly to X-risk by numerous small factors, none of which would by itself be capable of overwhelming the system, but which collectively undermine it).
The continuation of the solar cell and battery cost curves are pretty darn impressive. Costs halving about once a decade, for several decades, is pretty darn impressive. One more decade until solar is cheaper than coal is today, and then it gets cheaper (vast areas of equatorial desert could produce thousands of times current electricity production and export in the form of computation, the products of electricity-intensive manufacturing, high-voltage lines, electrolysis to make hydrogen and hydrocarbons, etc). These trends may end before that, but the outside view looks good.
There have also been continued incremental improvements in robotics and machine learning that are worth mentioning, and look like they can continue for a while longer. Vision, voice recognition, language translation, and the like have been doing well.
A very large chunk of this is directly or indirectly increased resource prices, especially driven by China.
If the improvement in cost-performance of computation slows dramatically in the next decade or so, this could be a small effect. Kurzweil predicts that silicon CMOS will end and be replaced by something that improves at least as rapidly, generalizing from past transitions (vacuum tubes to transistors, etc), but there are fewer data points to support that claim, and we are much closer to physical limits, with less room for miniaturization. There are new materials with plausibly better properties than silicon, room for new designs (memristors, unreliable computing, wacky new cooling systems), clever 3-D innovations, and so forth. However, a grab bag of such innovations seems less reliable than miniaturization, which automatically improves many dimensions of performance at once.
Do you have a cost curve for the price of watts delivered to the grid, instead of solar cell costs?
Going on the wikipedia price per watt: http://en.wikipedia.org/wiki/Price_per_watt
So even if the panels were free, it’s still $3.30 per watt to actually make it happen.
BOS costs have so far kept rough pace with cell costs, and the DOE has fairly credible roadmaps and prototypes for further reductions, as with cells. Part of these are regulatory costs (pointless permitting demands and the like) which can be relaxed, and have been in places like Germany.
That sounds promising for us (Australia). We have almost as much desert as we do coal!
How much could be gained from more efficient programs, even if hardware improvements stall out?
A huge amount surely, at least for many problems. There’s no guarantee that any particular problem will be subject to vast further software improvements, though.
Can you expand on this? I suspect this is true for some classes of problems, but I’m sufficiently uncertain that I’m intrigued by your claim about this being “surely” going to happen.
A lot of existing improvement trends would have to suddenly stop, along with the general empirical trend of continued software progress. On many applications we are well short of the performance of biological systems, and those biological systems show large internal variation (e.g. the human IQ distribution) without an abrupt “wall” visible, indicating that machines could go further (as they already have on many problems).
I’m not quite sure software is well short of the performance of biological systems in terms of what software can do with given number of operations per second. Consider the cat image recognition: Google’s system has miniscule computing power comparing to human visual cortex, and performs accordingly (badly).
What I suspect though, is that the greatest advances in speeding up technological progress, would come from better algorithm that works on well defined problems like making better transistors—something where even the humans make breakthroughs not by verbally doing some i think therefore i am philosophy in their heads but by either throwing science at the wall and seeing what sticks, or by imagining it in their heads, visually, trying to imitate the non-intelligent simulator. Likewise for the automated software development; so much of the thought that human does to do such tasks is, really, unrelated to this human capacity to see meaning and purpose to life, or the symbol grounding or anything of this kind that makes us fearsome, dangerous, survival machines—things you don’t need to make for automated programming software.
Why would you expect the opposite? Tight lower bounds have not been proven for most problems, much less algorithms produced which reach such bounds, and even in the rare cases where they have been, then the constant factors could well be substantially improved. And then there are hardware improvements like ASICs, which are no joking matter. I collected just a few possibilities (since it’s not a main area of interest for me as it seems so obvious that there are many improvements left) in http://www.gwern.net/Aria%27s%20past,%20present,%20and%20future#fn3
I’m not sure really. The conjectured limits in some cases are strong. Computational complexity is unfortunately an area where we have a vast difference between what we suspect and what we can prove. And the point about improvements in constant factors is very well taken- it is an area that’s often underappreciated.
But at the same time, these are reasons to suspect that improvements will exist. Carl’s comment was about improvement “surely” occurring which seems like a much stronger claim. Moreover, in this context, while hardware improvements are likely to happen, they aren’t relevant to the claim in question which is about software. But overall, this may be a language issue, and I may simply be interpreting “surely” as a stronger statement than it is intended.
Given the sheer economic value of improvements, is there any reason at all to expect optimization/research to just stop, short of a global disaster? (And even then, depending on the disaster...)
No, not particularly that I can think of. The only examples where people stop working on optimizing a problem is when the problem has become so easy that it simply doesn’t matter to optimize further, but such examples are rare, and even in those sorts, further optimization does occur just at a slower place.
And that increases the odds we’ll survive until a singularity.
How does it substantially impact that probability?
One of the ways we can kill ourselves is global warming. Replacing coal power with solar power will reduce one of the causes of global warming—namely, the greenhouse gases emitted from coal plants.
How likely is it for global warming to be an existential risk threat? This seems unlikely. It may well be that global warming will contribute to existential risk in a marginal fashion if it forces less resources to be spent on existential risk issues or makes war more likely, but that seems like a much more roundabout issue, and by that logic many other technologies would fall into the same category.
It depends what you mean by an existential threat.
I think there’s a reasonable chance that global warming (combined with other factors; biosphere degradation, resource depletion, unsustainable farming, lack of fresh water, increasing war over increasingly limited resources, ect), may cause our current civilization to collapse.
If our civilization collapses, what are the odds that we’ll recover, and eventually get back up to where we are now? I don’t know, but if our civilization collapses and we’re left without modern tools in a world in the middle of an ongoing mass extinction that we started, things start to look really dodgy. In any case, we don’t know what percentage of intelligent species go from being merely intelligent to having an advanced technology; it could be that we just passed The Great Filter in the past 200 years or so (say, at the moment the industrial revolution started), in which case losing that advance and passing back through it in the other direction would dramatically lower our chances of becoming a space-faring civilization.
Of course, if we reach a sufficiently high level of technology before the other problems I talked about kick in, then they’re all solvable.
That doesn’t seem even remotely likely; as I understand it, the Earth has been much hotter than now many times without turning into Venus.
It doesn’t have to turn the Earth into Venus for unusually-rapid climate shifts to destabilize geopolitics badly, exceed system tolerances in infrastructure, consume an ever-growing portion of the economy either by increased loss and waste or in efforts at mitigation, and thereby effectively amp up the power of many other forms of global X-risk (or just contribute directly to X-risk by numerous small factors, none of which would by itself be capable of overwhelming the system, but which collectively undermine it).
Impossible to estimate.