I went to see Ray Kurzweil talk at the Commonwealth Club in support of his new book: How to Create a Mind. As I suspected, Ray couldn’t resist trotting out the exponential-growth-of-computing-price-performance spiel for the Commonwealth audience who might not have been exposed to this material. However, instead of being bored by this stuff which I first read years ago in the Singularity Is Near, I found it to be an interesting refresher. It is pretty cool how computing performance improves in a smooth, super-exponential curve across the entire 20th century, seemingly unaffected by war or economic depression.
Ray explains that this progress is driven by using the current generation of technology to build the next generation of tools. One new example that Ray offered of this was that of his father working as a composer. In order for his father to actually hear a full performance of an orchestral composition, he needed to get funding and actually assemble an orchestra. If changes needed to be made, the entire arduous process had to be repeated. In contrast, any college student with a laptop can preview a complete orchestration of their music using modern software. These same students with laptops created Google, Facebook, and Twitter. And they are creating the next technological paradigm that will build upon and extend social/mobile/cloud technology.
Overall, Kurzweil was characteristically positive and optimistic. He believes that technology, and social media in particular, are having a democratizing effect on the world (and he takes for granted that this is a good thing). He showed a animated graph of GDP and the life expectancy in major parts of the world from 1800 to the present, and though the “haves” were clearly divided from the “have-nots,” the rising tide did raise all boats. Even the worst off today are better off than the most advanced nations of 1800 by these metrics. No wonder Pinker spoke at the Singularity Summit this year. It’s a whig conspiracy.
I also forget sometimes what a sincere and likable presenter Ray is. He cracked jokes throughout the evening and showed his human side. At one point he commented that the cutting edge of human intelligence consisted of things like poetry, humor, being sexy, and being loving. These are the sorts of things that my girlfriend is always calling intelligence (well, she doesn’t consider being sexy intelligent for some reason) and I always have trouble with that. Intelligence is problem solving or pattern recognition or prediction in my mind. But the more I think about it, I realize that poetry, humor, and love all require vast amounts of problem solving, pattern recognition, and prediction. “What must I do to keep her/him from leaving?” “How will the audience react to this line?” You’ve got to work for love.
Kurzweil does concede that areas outside of information technology have not progressed at the same rate (which Thiel harps on), but he insists that more and more fields will effectively become information technologies. He cited health and medicine as examples, and brought up the exponential improvements in gene sequencing and biological simulation. He suggested that drug discovery will transform into drug design as molecular-level simulation becomes more attainable.
The technology of atoms (as opposed to bits) will also begin accelerating as 3D printing evolves. Kurzweil pointed out that 3D printers can now pring 70% of the parts needed to create a 3D printer. (assembly is another matter) He also mentioned that these printers are able to work with more and more materials and referred to a metal ring he was wearing that was created using an additive process.
It was almost 40 minutes into his one hour talk before he touched on the apparent topic of his book, namely artificial intelligence. He considers the (exponential!) improvements in brain imaging to be the most promising path toward developing AI. Our brains are an important “source of templates for intelligence.” One recurring theme of Kurzweil’s is that the brain is possibly simpler than it appears. He likes to point out that the neocortex is relatively uniform in structure. He dismisses Paul Allen’s criticism that the brain is too complex to model by pointing out that Allen is assuming that every twig in the forest has significance. Kurzweil contends that the brain is actually massively redundant, so the actions of individual neurons are of little importance. He also asks where all of this design information would even come from given the limited bytes of information in the genome responsible for the brain (25 MB with lossless compression).
To support his argument, he mentioned some recent papers that are illuminating the structure of the brain. One was the paper: The Geometric Structure of the Brain Fiber Pathways: A Continuous Orthogonal Grid (described for us laymen here). The gist of which is that the brain’s connections are arranged like ribbon cables “that cross paths at right angles, like the warp and weft of a fabric.” He also mentioned another paper that posited pattern recognizing modules composed of 100-neuron bundles. I wasn’t able to locate this paper, but this one might be it (Damn my hardcopy version of How to Create a Mind, no search capability!). I am somewhat sympathetic with Ray’s critics here. He might be too simplistic in his modeling. But I will read the book at some point and then I will have a more informed opinion.
Speaking of books, check out the new GoodReads.com group I created. I will be posting all of the books I reference and some impressions of each one (see widget to the right). If you don’t know about GoodReads.com, you should check it out. It’s a great way to share and manage the books in your life.
Ray mentioned that he was not a fan of neural networks. In his view a neuron is too weak computationally. It is these 100-neuron modules that serve as pattern recognizers that capture his attention. He discussed the hierarchal nature of the neo-cortex wherein more complex ideas are handled by modules structurally similar to those that handle lower order ideas. The modules handling complex ideas are simply connected at the top of neocortical hierarchies. This is similar to Numenta founder Jeff Hawkins’ thesis from On Intelligence. Though it’s interesting to note that Numenta co-founder Dileep George has jumped ship and struck out in his own direction with his new company, Vicarious.
Kurzweil expressed admiration for Watson’s Natural Language Processing abilities. Nonetheless, he appears to be working on his own version of the digital neocortex in competition with IBM, Google, Numenta, Vicarious, and all the other seekers of AGI. Given his track record with optical character and voice recognition, he probably should be considered a serious contender. He knows his Hidden Markov Models.
In Ray’s view machines are an extension of ourselves and will even allow us to increase and extend our emotional reach. He points out that we already offload many of our mental processes to the internet. He felt cognitively constrained during the SOPA strike. In this sense his position is similar to Alva Noë and other embodied embedded cognition folks.
intelligent behaviour emerges out of the interplay between brain, body and world.
Though the embodiment crowd probably parts ways with Kurzweil on the brain in a vat question.
One final thought I found interesting was Ray’s approach to brainstorming. He said that prior to sleeping each night, he assigns himself a problem to solve, either from work or in his emotional life. During sleep, while dreaming, all of his rational faculties are disabled. Which is why ridiculous events can occur in dreams without surprising us. Our right brains are non-judgemental. All of the censors that inhibit our thoughts are quieted during sleep. As he awakens in the night, he is aware that his dreams often are related to the problem he assigned himself in some way. But it is during the interstitial time between sleep and waking when he finally tries to retrieve and salvage the solutions or suggestions provided during his dreamstate. He said that this days are often spent writing down the key insights and carrying out the decisions made in dreams.
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I am glad to see that the “brain is simpler than the brain thinks it is” approach has begun to come into fashion. See http://io9.com/5950984/why-slime-molds-can-solve-mazes-better-than-robots for an example of something “thinking” without even having a brain, or for that matter a body as we understand a body. Minds have to be built up from components that are built up from components, because there aren’t any other options that don’t involve fantasy. Large numbers of simple structures following simple rules of interaction can do amazing things that the simple structures on their own could never do. I.E. slime molds, ants, bees, termites…