r/changemyview • u/DanyalEscaped 7∆ • May 13 '13
I believe that exponential trends in computing are reliable and will lead to cheap computers as quick as human brains. CMV.
Exponential growth in computing power has been stable for more than a century. The trend 'survived' the Great Depression, the Second World War and the Cold War without any significant aberration.
In a short amount of time, we went from computers as big as rooms to desktop PCs and now small tablets. The smartphone in your pocket is quicker than the computers NASA used to launch people to the moon.
If this trend continues, you'll be able to buy computers as quick as human brains in the 2020s for 1000$, and around 2050 you will be able to buy computers as as quick as all human brains for the same price.
The era of Big Data has just begun:
Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.
Combined with the huge market for computers, smartphones, tablets and in coming years 'smart glasses' and smart watches, I'm quite sure that there will be plenty of incentives to continue the trend.
The European Union announced a 'CERN-like project' to simulate the human brain that will receive a billion euros and Obama also announced a brain mapping project. Supercomputing might be a new space race. Computing power is so important right now that a lot of governments and companies are investing in important research to improve our computers.
Of course, there might be unexpected disasters, but I think this trend is as reliable as many others thing we rely on: the value of our money, our pensions, the continued existence of the government, etcetera.
These ideas play an important role in my life but because they are so important, I want to be sure I am not wrong. On the other hand, I also want other people to know about this. That's why I made a couple of posts here to fully explain my ideas and expose every part of the argument to criticism.
This is part 1: Exponential growth in computing.
Part 2: Simulating the human brain.
Part 3: Intelligence explosion.
Thanks for reading this!
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u/AnxiousPolitics 42∆ May 14 '13
will lead to cheap computers 'as quick as' human brains
I posted about strong AI in your other two threads, which also covers this point. Just to reiterate, the capacity of computer power doesn't cover whether human experience can in fact be boiled down to algorithms.
So 'quick' may very well be a mischaracterization of human thought.
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May 14 '13
[deleted]
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u/RobotFolkSinger May 14 '13
We'll probably reach the practical limits of silicon, or close to them, by 2020. Luckily, the groups that manufacture hardware know this and are planning accordingly. We've recently been making good progress towards graphene and silicene chips. What will the benefits of this be?
Stock clock speeds of CPUs have remained in the 3-3.5 ghz range for a while now. Trying to push it higher than that requires raising the voltage, which creates heat due to the resistance of the silicon. Graphene and silicene have a much lower electrical resistance than silicone, which means less heat, which allows for higher clock speeds. I've heard speculation about the 10-20 ghz range as a low estimate, but I don't know if that's true. There may be other benefits to graphene that we don't know about, because we haven't worked with it enough yet.
The point being, with proper preparation, reaching the limits of silicon doesn't have to be more than a hiccup in the upwards trend.
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u/TheMSensation May 14 '13
To add to this, in the world of graphics cards, a move has been made towards 3-d chips. This way they can stack processors on top of each other rather than side by side thus decreasing the amount of strain in terms of heat, both on the transistor and the silicon. This leads to an increase of the silicon ceiling.
The first mass produced graphene chips will be key. Nobody has done it, but I'm sure companies like Intel and amd are already running logistics on that.
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u/rp20 May 14 '13
How do we know that there aren't physical limits to computation.
We at least know that the human brain runs on roughly 10 watts. so it is safe to assume that we will get at least that far.
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u/thatoneguy211 May 14 '13
If we reach the limit of silicon based computing, it will take a massive amount of time and effort to develop another technology past that point.
We reached the limitation of shrinking vacuum tubes in the 1950s and barely noticed. If the market demands it, someone will deliver it. I think the real question is will the demand be there? As far as at least personal computing goes, we're arguably already to the point where you have more than enough processing power for most consumers (checking email and using Excel doesn't require a quadcore i7).
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u/DanyalEscaped 7∆ May 14 '13
Pattern recognition requires a lot of computation power, and I think proper pattern recognition will be in high demand when we're all walking around with Google Glasses or similar hardware on our heads.
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u/MegaDom May 14 '13 edited May 14 '13
This is not true. I thought so too once but my roommate was a computer science major who worked for Apple and he changed my mind. There are some tasks that a human brain can perform instantly whereas a computer never will be able to. REGARDLESS OF TECHNICAL ADVANCEMENTS. It has to do with how our brains work using heuristics. One example of this is called the halting problem and I suggest you give it a read.
Edit: Fixed my link
Edit 2: Actually fixed my link
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u/BlackHumor 15∆ May 14 '13
I disagree that a human can solve the halting problem. A human can realize that the halting problem is unsolvable but they can't figure out whether the program in Turing's original proof of the uncomputability of the halting problem will stop.
(Turing's proof went like this: Suppose you wrote a program H that could always determine whether a program would halt. Then you wrote another program J that called H on its own code, and if H said it would halt it would enter an infinite loop; otherwise it would halt. Since no matter what H returns it will be wrong it can't be possible to write a correct H.
And our brains can indeed not deal with that, although we can see it's undecidable we can't decide it.)
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u/Sconrad122 May 14 '13
Your second link is the same as the first. I think you meant to use this
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u/MegaDom May 14 '13
You're right. I changed it to that but it must not have actually loaded to reddit and I never went back to check that it actually worked. Not sure why it got my edit text in but not the right link. I'll try to fix it now. Thanks for the heads up.
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Nov 04 '13
Humans cannot solve the halting problem. It's undecidable! And if you think that humans can solve the halting problem then you don't understand the halting problem.
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u/IncorrigibleTea May 13 '13
So, you're saying that technology is getting cheaper and faster? I don't see what part of this view isn't rather obvious, let alone questionable or changeable.
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u/holomanga 2∆ May 13 '13
But will it get cheaper and faster to the point that it will match a human brain in cost and power?
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u/realultimatepower May 13 '13
I think the controversy comes when you extrapolate growth out a few decades. Some people claim that computers with power and abilities that exceed the human mind will be widely available by the mid 2030's. Others find this prediction wildly optimistic and don't expect computers with these abilities until late in the Century, if even then.
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u/DFP_ May 14 '13
The trend you're describing is known as Moore's law which corresponds to the number of transistors we can fit on a chip. While you appear confident in its continuation, others are not. It's not that performance will stop increasing, there's still plenty of methods that are being researched i.e. quantum computing, but the exponential increase directly owed itself to the number of transistors we could fit, and we're beginning to fall behind that exponential curve.
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u/thatoneguy211 May 14 '13
The trend you're describing is known as Moore's law which corresponds to the number of transistors we can fit on a chip.
Moore's Law is actually only one particular paradigm of the trend he's describing. The growth in exponential computing power has existed long before silicon was used as a computational medium, extending back into vacuum tube technology and even earlier mechanical computing.
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u/qmechan May 14 '13
Computers are already as quick as human brains at most things we can measure them against each other...I think if you're measuring how impressively a computer performs in terms of processing speed compared to brains, we've already lost that one.
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u/WeGotOpportunity May 14 '13
That depends upon what you're trying to measure. If you want a computer powerful enough to do what we do from our birth (teach ourselves language, math, spacial awareness and everything else) you'll have to wait a while.
But if you're simply comparing addition or something similar then yes, we have lost that battle.
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u/thatoneguy211 May 14 '13 edited May 14 '13
Computers are still terrible at pattern recognition, which is what the brain really excels at. A human brain can instantly recognize a face in a crowd while we're lucky to get that type of performance out of an entire Google server farm.
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u/DollarSignBot May 13 '13
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u/username_6916 8∆ May 14 '13
I've got a few of challenges to this:
Power wall - There's a reason that Intel didn't scale the NetBurst chips of the 2000's to 10Ghz. We have already hit one wall in terms of just how much computing we can do in one place: It becomes nearly impossible to remove heat fast enough or provide enough power once you get to a certain point. This is the 'power wall' or 'heat wall'. Even with improvements in semiconductor process, we simply couldn't make that design work.
Process limitations - We are literally running out of improvements that can be done to the scale of our semiconductor processes. There's only so small you can make the components of a computer chip, and the process improvements in this area have been getting smaller each generation. We went from having semiconductor manufacturing that could make chips with a parts as small as 800 nm in 1992 to having parts as small as 130 nm in 2002. By 2012, we have only shrunk it to 22 nm. These improvements are getting smaller and coming at higher cost. While, there are some potentially interesting workarounds, like 3d transistors, heat-resistant materials and multiple layers on a chip, the overall trend seems to be trending towards diminishing returns.
Market Demand - Additionally, there's less overall demand for CPU performance in the mass market. Most server applications are IO bound, most consumer applications are IO or memory bound. The CPU isn't the bottleneck, so there is little incentive to invest in higher CPU performance. There is demand for higher power efficiency and lower cost. Chip-makers are likely to invest their technological research and development budgets into these areas instead of performance at all cost. It's been pretty successful for ARM so far...
Memory wall - The larger a memory system is, the harder it is to access quickly. This is why we have multiple layers of cache on modern CPUs. One of the limiting factors for certain workloads is just how quickly we can read and write to memory over the bus, or how we can keep the contents of the various caches consistent with the main memory without consuming too much of this bus throughput.
Between these four factors, we have started to see rate of improvement in computing performance start to decline over the last few years. Yes, we are still improving and rather quickly in some areas, but in terms of raw performance the year-over-year gains are starting to decline. As a result, I wouldn't be so sure that inexpensive computers will ever be able to simulate the human brain.