Kurzweil predicts personal computers with the power of the human brain by 2025

By August 17, 2010Ray Kurzweil

This is the second post in a series summarising the key arguments of Ray Kurzweil’s The Singularity is near: When humans transcend biology.  The first post entitled Ray Kurzweil, The Singularity and the accelerating pace of progress can be found here.


image The second idea I’m going to pick out from The Singularity is Kurzweil’s prediction that by 2025 personal computers (I think costing less than $1,000 in today’s money) will have the power of the human brain.

The first component to this prediction is an assessment of the computational power of the human brain.  Kurzweil looks at a number of different ways to think about this question and they all yield estimates in the range of 10(exp 14) to 10(exp 15) calculations per second (henceforth cps) – that is one hundred million trillion cps to one billion trillion cps.

Today’s personal computers, or at least those back in 2005 when The Singularity was published provided 10(exp 9) cps and an extrapolation historical increases in computing power going forward yields the prediction that personal computers will have a capacity of 10(exp 16) cps by 2025.

Kurzweil goes on to add substance to this prediction by discussing the technologies that will yield the increase in computing performance that he is predicting.

First up is Moore’s law.  As many of you will know Moore’s law was coined in 1965 and described the annual doubling of the number of transistors that can be fitted onto an integrated circuit (and remember if something is doubling every year it’s rate of increase is exponential).  At the time Moore predicted the trend which he had only observed from 1959-65, would continue to 1975, a prediction that was widely seen as premature.  Writing in 2005 Kurzweil cited Intel’s latest estimate for the end of Moore’s law as 2020.

A common reaction to the prediction of never ending exponential growth is that it has to end some day, e.g. through physical limits.  That seems intuitive to people who observe exponential increases in populations tail off over time.

Kurzweil’s answer to that, which I think is a good one, is that the rate of increase will inevitably eventually tail off within a given paradigm, but that we always invent a new paradigm that will maintain the high level trend.  This means that the long term exponential increase curve is formed from a series of s-shaped curves which combine together.  Each s-curve represents a distinct technology which shows slow growth in the early years, very rapid growth in the middle years before tailing off in the later years during which period the next technology is invented.

Moore’s law describes the rapid growth period of the integrated circuit era and as we are coming to the end of that period there are a number of technologies in the formative stage which are candidates for creating the next s-curve.

The first thing to note is that integrated circuits are essentially 2-dimensional arrangements and transitioning to 3-dimensions will unlock the next period of growth.  Kurzweil discusses a number of emerging computing paradigms that could enable that transition:

  • nanotubes and nanotube circuitry
  • molecular computing
  • self assembly in nanatube circuits
  • biological systems emulating circuit assembly
  • computing with DNA
  • spintronics (computing with the spin of electrons)
  • computing with light
  • quantum computing

It is beyond the scope of this post to examine each of these in detail, but Kurzweil’s description of developments in each of these fields coupled with the time left in Moore’s law, and the fact that throughout history a new invention has always been found to continue the trend in increasing computing power, leave me believing it is reasonable to predict that a personal computer will have the raw power of the human brain sometime in the 2020s.

Of course having the raw power of a human brain isn’t the same as being a human brain.  For that you need software, which will be the topic of tomorrow’s post.

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  • Anon


    Since there are all sorts of factors at play and human evolution and intelligence means that whenever we’ve happened across anything that didn’t make scientific sense (yet) or the environment isn’t conducive, we’ve gone out to try and discover the solutions in more favorable places or simply written its proof in a different way/language.

    So as I wrote in the comments to your first post in the series……….

    “It [sic: realizing a Singularity] will need us to innovate new scientific instruments, new mathematics, new code, new constructs of value (moral, perception, tastes and more) and new socio-economics.”

    The conclusion from this is that Kurzweil can broad-brush architect the fact that we need those emerging computing paradigms to reach the Singularity, but there are 3 key issues/ flaws/ challenges to his position:

    (1.) As with everything, it’s the execution that counts not the theory. Execution, execution, execution to emphasise.

    (2.) We need computing paradigms that are not only empirically or science based but also to cross-pollinate it with social science metrics.

    (3.) The machines still cannot yet comprehend or contextualize the wealth of data out there.

    They can categorize and connect but not make any of it into a coherent whole that encompasses empiricism, emotions, random extrapolation, imagination and consequentiality in the way that our natural brains can.

    Given all this, is it possible that we can have PCs with the power of the human brain by 2025?

    Hmmn……..Well if my generation is lucky enough to have more than a few Sir Tim Berners-Lees, Alan Kays, Steve Jobs, Ada Lovelaces, Anita Borgs, Grace Murray Hopper, Alan Turings and others (particularly the polyglot polymaths who could synch art, science, computing, linguistics and the humanities) collaborating on it in a coherent and concerted way……..

    Sure, why not.

    I look forward to your next installment in this series, :*).

  • Anon

    Well I wrote those 4 (not 3 in the end) segments late last night and then this morning at 6AM I read this link from an American friend:

    * http://gizmodo.com/5614927/ray-kurzweil-does-not-understand-the-brain?

    This is consistent with my comment, “Actually there are challenges and current limitations with each and these are tied to consistency, completeness and coherency with existing scientific research in the fields of …. genomics…”

    As an associated point, I recently caught up with one of my former maths professor who reminded me that human knowledge of DNA is incomplete and that a “strand does not a sequence make” (mathematicians understand this from strand collapses in chaos theory, btw). I asked him about computing with DNA because I don’t believe the current Rubik’s cube approach in semantic metadata works optimally, so I’ve thought up another framework that has associations with DNA and other organic molecules.

    Anyway, whether it’s…..

    • computing with DNA
    • spintronics (computing with the spin of electrons)
    • computing with light
    • quantum computing

    Hopefully my comments provide some glimpses about where current limitations are and also how we might overcome those (not that I or anyone else has any definitive answers yet; we’re simply on an expedition for it).

    I should clarify that when I wrote “Sure, why not” I’m referring to proxying the functional mechanistic aspects of the brain (logic, categorization, sequentiality, recollection — but not memory as such since as I noted there are emotional aspects intrinsic therein which are not currently accounted for in the code of computer storage, and more).

    If readers will (and I have no intention to start a “battle of the sexes” scenario), we could potentially reverse engineer the left “male” hemisphere of the human brain. The right hemisphere which is concerned with language, intuition, free association, consequentiality and more may prove to be more of a challenge.

    Now………Even if we did manage to reverse engineer both sides of the brain this still doesn’t necessarily mean the machine would be as intelligent or capable of sense-making as us. This is before we’ve even factored in the fact that intelligence varies in the human population and so this variance would be replicated in whichever reverse engineered artificial brain we built. It would have the intelligence of its human creators and that intelligence would be limited by their intelligence (reference points, linguistic abilities, perceptions and modalities of thinking etc.)

    Moreover, we would still encounter the crux of consciousness that separates Man from machine: the biochemistry of emotions that informs our values, our beliefs, our morals, our humanity, our empathy and consideration for others and for Society.

  • Once again interesting, and just in time for section 3 which I’m writing now.

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  • Anon

    Thanks and you’re welcome.

    I’m neither an advocate nor a naysayer for Kurzweil’s Singularity theory. His enthusiasm for pushing the boundaries and integrations between technologies from multi-disciplinary fields of the natural sciences is infectious. Nonetheless, at a pragmatic and scientific level there’s still a lot of solution finding ahead and some of his assumptions orientate us to look for solutions in inappropriate places.

    Ergo, just as with investment proposals and balance sheet projections, we need to due diligence those assumptions and approaches that underpin the numbers.


    Artificial intelligence is emerging from the petri dish into commercial applications (pls see Apple’s near US$200 mln acquisition of SIRI):

    * http://www.intomobile.com/2010/04/29/apple-acquires-siri-may-the-voice-powered-wars-begin/

    It’s certainly an area with potential upside for VCs and other investors, particularly if they grasp the technicalities at a granular level.

    At the broader level of creating platforms and tools for Global Consciousness, Vint Cerf of Google and Larry Brilliant have commented on it here during a Google Tech Talk back in Nov 2008:


    It’s worthwhile watching all 6 parts (although for the time-pressed, Parts I and II can be skipped without losing the essence of the talk).

    Cerf’’s points are interesting because they focus on that requirement for VCs and entrepreneurs alike…….

    So just as the Lee Strasberg School of Actors may say, “What’s our motivation?” Kurzweil and the Singularity aside, what’s the purpose and potential in building an artificial Global Brain and “conscious” machines.

    The altruistic answer would be: to solve humanity’s greatest common challenges………(in no particular order)……..

    • disease eradication
    • educational equivalence
    • democratic inclusion
    • value creation
    • calibrated consumption.

    The answer to investors would be: the more intelligent the technology, potentially the more effectively it could filter in the investment propositions that meet criteria and enable the tracking of metrics that contribute to their success across digital platforms.

    So it’s better to view Kurzweil’s theories and the advances in AI not in isolation but rather as a composite value sphere (not the typical and inherited Kotler value chain).

    Now in 20-30 years time Kurzweil, Sir TBL, Alan Kay, Vint Cerf, Steve Jobs et al will be in their 80s and 90s.
    That means that if a there is going to be a PC with the power of a human brain in 20-30 years time then it’s my generation (Facebook-Google) that needs to have the wherewithal to create it and drive it forward.

  • I don’t have trouble believing that the current (or next) generation of entrepreneurs will be equally if not more gifted than Jobs, Gates, TBL etc. They are, after all, standing on the shoulders of giants.

    Hopefully we in the finance community are also getting better at supporting them.

  • All of this leaves me thinking that whilst 2025 might or might not be an optimistic date for personal computers matching the human brain there is every reason to think we will get in say 20-30 years.

  • All of this leaves me thinking that whilst 2025 might or might not be an optimistic date for personal computers matching the human brain there is every reason to think we will get in say 20-30 years.

    Thanks for all the comments. Very illuminating.

  • I do not think that the desire of Kurzweil will be fulfill.
    Thanks for it.

  • I do not think that the desire of Kurzweil will be fulfill.
    Thanks for it.

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