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Transcending Complacency on Superintelligent Machines

43 pointsby hedgesabout 11 years ago

4 comments

cliveowenabout 11 years ago
Am I the only one who&#x27;s skeptical about the feasibility of AI? As I see it there are two ways to think about AI: first there&#x27;s the kind of AI that arises from software emulating parts of the human brain based on our current understanding of its inner functioning and produces human-like intelligence, so even if the mechanisms are different from those actually employed by the brain the output is similar in response and depth of reasoning; then there&#x27;s the AI that stems from creating an artificial brain by reverse-engineering the human brain, but we are an awfully long way from doing that, mostly because we can&#x27;t expect to unravel in a few decades what evolution has spent millennia perfecting.<p>It looks to me, a layman, that the only approach that holds any water is the first one. But then again, it mostly looks like people are implementing software based on a flawed understanding of cognitive functions and basically hoping that something magic happens. How can a scattershot approach like this ever produce anything even remotely resembling human intelligence?
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TheIronYuppieabout 11 years ago
I think that one thing that people are missing when they think AI is not a threat is there does not have to be a singular AI for every problem.<p>Chess computers are better than humans, but I wouldn&#x27;t trust them to manage the electricity grid. What if there was an equivalent quality of computer specialized for every significant area of society - electricity grid, packet routing, high speed trading, etc etc.
swombatabout 11 years ago
Obviously agreeing with the points, but this seems to be more an awareness piece than an actionable one.
todd8about 11 years ago
I&#x27;m no expert in this area so I welcome corrections to my rough numbers below.<p><pre><code> Approximate number of human neurons: 1.0e11 Approximate number synapses in a human: 1.0e14 </code></pre> These are big numbers, but not impossibly big numbers. There are different kinds of neurons, and signals on synapses are not simply binary. However, even with these complications, the hardware needed to reach these scales isn&#x27;t hard to imagine.<p><pre><code> Transistors in XBox One: 1.0e09 </code></pre> Brains are biological computers so they suffer from very slow switching speeds at the neural level. Neurons run in parallel, but they are not fast:<p><pre><code> Approximate neural switching speed: 1.0e03&#x2F;sec </code></pre> Even if all of the synapeses could sustain this rate in parallel (they can&#x27;t) and even if all of the brain was 100% occupied with solving a single task (it isn&#x27;t) this would mean that we absolutely can&#x27;t compute faster than:<p><pre><code> Speed * synapses (brain ops per second): 1.0e17&#x2F;sec </code></pre> For comparison, the fastest bitcoin hardware I see is advertised to operate at the following speed:<p><pre><code> Minerscube 15 (hashes per second): 1.5e12&#x2F;sec </code></pre> And a regular GPU is capable of simple instructions that run at the following speed:<p><pre><code> AMD Radeon HD 6990 32-bit instructions: 2.6e12&#x2F;sec </code></pre> From this we can see that hardware is catching up with the raw computing ability of the human brain. Now consider the problem of programming a brain. It isn&#x27;t necessary to program every synapse. The brain learns, and essentially programs itself. To see why this is true consider the programming that we are born with:<p><pre><code> Bits of information in human genome: 1.0e10 </code></pre> This is far less than the number of synapses that we have. Therefore, the brain must program itself, somehow.<p>Now, to address the argument about evolution taking millions of years. First, we can evolve programs much faster than nature can evolve humans. There have been, perhaps, 100 million generations of humans. Even if it takes six seconds of computing time to run an evolutionary computation for a single generation it will take no more than 20 years to run over 100 million generations.<p>Brute force evolution isn&#x27;t the only way to build strong AI. A program can exhibit behavior that we don&#x27;t anticipate. I&#x27;ve written simple programs that beat me easily at games such as Othello or Freecell.<p>Finally, once machines get smart enough to design other machines there may be a rapid acceleration of progress in this area as we employ them in designing subsequent generations.<p>I feel that strong AI may pose a significant risk to humans; consequently, we should proceed with caution. Here is a thought experiment. If a chimpanzee could be taught to drive, would you trust it to pick your kids up from school? What sort of value judgements would it make in the case of an impending emergency? Would you let an elephant baby sit for you? Even if was much &quot;smarter&quot; than a normal elephant?<p>Strong AI will not be like us. It will learn and develop without a human body, and it will not interact with the world and society as we do and may end up being very foreign to us. Will it be sociopathic? Or will it be like whales, intelligent, but mysterious, perhaps spending all its time singing AI songs to other AIs.