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by
Ray Kurzweil
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November 18, 2017 - March 9, 2018
recognition technologies from Nuance. The natural-language extensions were first developed by the DARPA-funded “CALO” project. 15 Siri has been enhanced with Nuance’s own natural-language technologies, and Nuance offers a very similar technology called Dragon Go! 16
The methods used for understanding natural language are very similar to hierarchical hidden Markov models, and indeed HHMM itself is commonly used. Whereas some of these systems are not specifically labeled as using HMM or HHMM, the mathematics is virtually identical.
But when one paradigm runs out of steam (for example, when engineers were no longer able to reduce the size and cost of vacuum tubes in the 1950s), it creates research pressure to create the next paradigm, and so another S-curve of progress begins.
Essentially, we always use the latest technology to create the next. Technologies build on themselves in an exponential manner, and this phenomenon is readily measurable if it involves an information technology.
More broadly speaking, this acceleration and exponential growth applies to any process in which patterns of information evolve.
I now have a public track record of more than a quarter of a century of predictions based on the law of accelerating returns, starting with those presented in The Age of Intelligent Machines, which I wrote in the mid-1980s. Examples of accurate predictions from that book include: the emergence in the mid- to late 1990s of a vast worldwide web of communications tying together people around the world to one another and to all human knowledge; a great wave of democratization emerging from this decentralized communication network, sweeping away the Soviet Union; the defeat of the world chess
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improving in resolution, spatial and temporal, at an exponential rate. Different types of brain scanning methods being pursued range from completely noninvasive methods that can be used with humans to more invasive or destructive methods on animals. MRI (magnetic resonance imaging), a noninvasive imaging technique with relatively high temporal resolution, has steadily improved at an exponential pace, to the point that spatial resolutions are now close to 100 microns (millionths of a meter).
If a machine can prove indistinguishable from a human, we should award it the respect we would to a human—we should accept that it has a mind. —Stevan Harnad
In this way we will merge with the intelligent technology we are creating. Intelligent nanobots in our bloodstream will keep our biological bodies healthy at the cellular and molecular levels. They will go into our brains noninvasively through the capillaries and interact with our biological neurons, directly extending our intelligence. This is not as futuristic as it may sound. There are already blood cell–sized devices that can cure type I diabetes in animals or detect and destroy cancer cells in the bloodstream. Based on the law of accelerating returns, these technologies will be a billion
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I already consider the devices I use and the cloud of computing resources to which they are virtually connected as extensions of myself, and feel less than complete if I am cut off from these brain extenders.
That is why the one-day strike by Google, Wikipedia, and thousands of other Web sites against the SOPA (Stop Online Piracy Act) on January 18, 2012, was so remarkable: I felt as if part of my brain were going on strike (although ...
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But more important, it showed how thoroughly we have already outsourced parts of our thinking to the cloud of computing. It is already part of who we are.
Once we routinely have intelligent nonbiological intelligence in our brains, this augmentation—and the cloud it is connected to—will continue to grow in capability exponentially.
From quantitative improvement comes qualitative advance.
British mathematician Irvin J. Good, a colleague of Alan Turing’s, wrote in 1965 that “the first ultraintelligent machine is the last
the neocortex—

