[nfb-talk] Fw: [nesfa-open] Top futurist, Ray Kurzweil, predicts how technology will change humanity by 2020

John G. Heim jheim at math.wisc.edu
Mon Dec 14 21:41:37 UTC 2009

One thing that has always bugged me about RayKurzweil's predictions is that 
about the only thing that even comes close to meeting his criteria is 
Moore's Law. There is this one thing that actually behaves the way his 
predictions do and dozens of things that don't. Yet he acts like his ideas 
are written in stone.

If technology advances in a exponential curve, why do we still have trains? 
That's pretty much the same technology invented 150 years ago. Automobiles 
are 100 years old. Land line telephones over 100. The Wright brothers would 
be able to explain what keeps a Boeing 767 in the air. We're still 
generating most of our power by the same old technologies that they used 
seventy to eighty years ago, hydroelectric, coal, and oil.  There asn't been 
an exponential increase in the technology behind vaccines., surgery, or even 
drug treatments. Life  expectancy has not increased exponentially.

Kurzweil ignores all the technologies that don't follow Moore's Law and 
focuses all of his attention on the one that does. Kursweil says 
"technological change is exponential". No, some technological change is 
exponential. Most of it is not. Quite a bit of it isn't even increasing 

From: "Ed Meskys" <edmeskys at roadrunner.com>
To: "blind-sf" <blind-sf at yahoogroups.com>
Cc: "nfb-talk" <nfb-talk at nfbnet.org>
Sent: Monday, December 14, 2009 12:20 PM
Subject: [nfb-talk] Fw: [nesfa-open] Top futurist, Ray Kurzweil,predicts how 
technology will change humanity by 2020

> ----- Original Message ----- 
> t at nasw.org>
> To: "NESFA Open Mailing List" <nesfa-open at lists.nesfa.org>
> Sent: Monday, December 14, 2009 8:32 AM
> Subject: Re: [nesfa-open] Top futurist, Ray Kurzweil,predicts how 
> technology will change humanity by 2020
>> At 10:16 PM -0500 12/13/09, Mark L. Olson wrote:
>>>Most people are confident that we have another 10 years of Moore's Law
>>>(about a 30x improvement in price/performance) because we can see the
>>>technology that will get us there, and a lot more than that is certainly
>>>possible.  (It's also true that people have been saying that Moore's Law 
>>>only a decade left for the past 40 years.)
>> The original formulation of Moore's law was the number of transistors per 
>> unit area, and that improvement _has_ been slowing.
>> The real sticky issue in computer-chip performance has become signal 
>> transmission on and off the chip. Raw speed per processing node has 
>> pretty well stalled out at several gigahertz, and chip developers have 
>> instead put multiple cores on the chips. However, that doesn't translate 
>> into raw speed because effective use of multiple processors requires 
>> parallel processing -- massively parallel as the number of cores 
>> increases -- and that requires developing new software, as you noted.
>>>My guess is that about 1000x improvement is possible without radically 
>>>technology, but that will come only with great difficulty.  The biggest
>>>problem is that it will certainly require massive parallelism, and it's
>>>really hard to program so as to use massive parallelism.  OTOH, there's a
>>>limit to how fast we need Excel to be, and there are other things which 
>>>do poorly now (e.g., speech recognition and animation) which would 
>>>hugely from it.)
>> I think we're at a point where microprocessor technology is going to 
>> split into at least two distinct classes -- one for simple single-stream 
>> processing (e.g., for word processing in PCs), the other for operations 
>> that can be performed in massively parallel ways. The improvements in 
>> single-stream processing are going to come from cutting the fat from 
>> bloatware and shifting parallel processing out of the single stream. 
>> There is some impressive and interesting ongoing work in massively 
>> parallel supercomputing (e.g., the Roadrunner supercomputer at Los 
>> Alamos), but that's aimed at a limited range of applications. The 
>> interesting software challenges are in finding ways to use that 
>> parallelism for things like speech recognition and animation.
>> -- 
>> Jeff Hecht science & technology writer
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