IBM’s new RoadRunner supercomputer is set to break the world’s supercomputing record by performing more than a quadrillion operations per second. That’s right, a quadrillion. For those of you like me who hadn’t heard that word before, it means 1000 trillion, or more explicitly: 1,000,000,000,000,000.
That number resonates with me because I’ve read several books that discuss the future of technology and how we are on the cusp of approaching the computing capacity of the human brain. One of the better books I’ve read on the topic is The Singularity is Near by Ray Kurzweil. In it he talks a lot about The Law of Accelerating Returns which states that the rate of technological change is actually accelerating, and not fixed.
To make this more clear, Moore’s Law says that computing power doubles every 18 months and most claim that this “law” has held consistent throughout the last half century. However, if we take a look at the improvements in supercomputing capacity then we notice that over a longer period of time, the rate at which speeds are doubling is actually shortening over time. Take a look at the table below, it shows the time taken for a thousand times increase in the top supercomputing speed globally. Notice that each successive 1000x increase has taken less time than the previous one. Hence the Law of Accelerating Returns.
So what does all this mean for us? Well Ray Kurzweil is renowned for having made many successful predictions, one of the most famous of these being that a computer would beat the best human at chess in 1998. It actually happened a year earlier in 1997. He made the prediction almost 10 years prior in one of his books.
Kurzweil estimates the computing capacity of the human brain at 20 million billion FLOPS – or 20 (here it comes) quadrillion FLOPS. It’s not easy to precisely calculate the computational speed of the human brain, but if we were assume he is correct then based on the historical data above we should see supercomputers reaching human-like speeds within the next 6 years – so by 2013. But due to the Law of Accelerating Returns, even if he is off by a factor of 10 or 100, that will only add a couple of years to the estimate. So we can very safely predict that by 2015 we will have machines with the computing capacity of the human brain.
Now that’s a milestone!
The Enlightened Blog 
Hi, just came across this and I’m pretty impressed by what you’ve written. They expect by 2018 the first exaflop computer. Thing is, exaflop is more powerful than the brain-we already created the petaflop in 2008 and with optolithography and optical chip making, they should exceed what the human brain processes by 2018. Simply astounding.
http://nextbigfuture.com/2010/06/cray-talks-systained-exaflop.html
Today we already have laboratory technology that enables us to have optical processing – even the storage problem was solved with several competing proposals actually. The next step is to make a scalable production facility, that’s a business investment challenge. A company like Apple for example, could easily do that with a fraction of their money “stock”.
This is the most exciting time in human history! These advances will make our live even better! I am glad to be alive during this time!
great info man, great info *slow clap*
Human brain is 100 ExaFLOPS.
http://4volt.com/Blog/archive/2010/02/05/power-required-to-emulate-a-human-brain.aspx
No. 100 exaflops are estimated to be required for whole brain simulation. This is a completely different thing than estimation of the computational power of the brain itself, in flops equivalent
The Fujitsu Supercomputer K runs 8.162 petaflops. With the size of 862 cabinets and using 9.89 MegaWatts of power (huge electric bill), the human brain is more efficient, smaller, and uses less electricity.
That’s why we should harvest human brains.
16.3 Petaflops as of June 2012…
http://www.wired.com/wiredenterprise/2012/06/top500-llnl/
Actual computational capacity of human brain is 100 teraflops. The real beauty is the memory hierarchy, which is zero-delay as opposed to moder computers where accessing the hard drive is an order of magnitudes slower than register access.
Brain FLOPS under-estimated? Astrocyctes missing:
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Astrocytes seem left-out of brain FLOPS estimates which take, IIRC, num_synapses * frequency ~= 38 Peta-FLOPs (IBM?)
Is it reasonable to leave out astrocytes? If not, by what factor would the FLOPs estimate of the brain need be increased? Astrocyctes are the most numerous of brain cells, and interconnect with several to 100s thousands synapses.
Why would astrocytes need to be considered?
1) Astrocyctes affect synaptic signal strength, and thereby neuron firing. Astrocyctes communicate with each other and with synapses, so shouldn’t the processing represented by the collective states therein need to be considered as more than just a single alteration of the “floating point” value, and, rather, an alteration of the calculation necessary for the value?
2) Something to also consider) Recent discoveries such as, e.g., augmented intelligence in mice injected with human astrocytes.
In related news, defense firm Cyberdyne Systems has sold their new Skynet computer system to the U.S. military.
TH-2 supercomputer already has 33.86 PFLOPS. I guess they were right…
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Congratulations from the year 2016, your prediction was correct.
2017
We just got busy playing with fidget spinner so nothing like that happened yet
Hmm…