chapter 3 Flashcards
Narrow/weak AI
a system that can perform only one narrowly defined task (or a small set of related tasks).
> AlphaGo
strong, human- level, general, or full-blown AI
the AI that we see in movies, that can do most everything we humans can do, and possibly much more.
Turing’s argument for consciousness
(1) Only when a machine feels things and is aware of its own actions and feelings—in short, is conscious—could we consider it actually thinking
(2) No machine could ever do this. Ergo, no machine could ever actually think.
Searle
argued against the possibility of machines actually thinking.
introduced the concepts of “strong” and “weak” AI in order to distinguish between two philosophical claims made about AI programs
strong and weak AI; now vs searle
TODAY
strong AI: AI that can perform most tasks as well as a human
weak AI: the kind of narrow AI that currently exists
SEARLE
strong AI: the appropriately programmed digital computer does not just simulate having a mind; it literally has a mind.
weak AI: views computers as tools to simulate human intelligence and does not make any claims about them “literally” having a mind.
turing test
the original question ‘Can a machine think?’ is too meaningless to deserve discussion,” Turing proposed an operational method to give it meaning. In his “imitation game,” now called the Turing test;
- there are two contestants: a computer and a human.
- Each is questioned separately by a (human) judge who tries to determine which is which.
- The judge is physically separated from the two contestants so cannot rely on visual or auditory cues; only typed text is communicated.
turing test prediction
in a five-minute session, the average judge will be fooled 30 percent of the time.
beat by The Eugene Goostman chatbot
Singularity
a future period during which the pace of technological change will be so rapid, its impact so deep, that human life will be irreversibly transformed.
Kurzweil bases all of his predictions on the idea of “exponential progress” in many areas of science and technology, especially computers.
Moore’s law
the number of components on a computer chip doubles approximately every one to two years.
In other words, the components are getting exponentially smaller (and cheaper), and computer speed and memory are increasing at an exponential rate.
Neural engineering
Kurzweil believes that we should reverse-engineer the brain
Most of [the brain’s] complexity comes from its own interaction with a complex world. Thus, it will be necessary to provide an artificial intelligence with an education just as we do with a natural intelligence
Singularity sceptics and adherents
Either enthusiastic embrace or dismissive scepticism
Many enthusiasts are in the tech industry
Kurzweil started Singularity University, a think-tank, which is partially underwritten by Google founder Larry Page
Hofstadter is between camps
He says Kruzweiler uses the Christopher Columbus ploy: one may laugh at predictions at the moment, but not anymore when they come true/in hindsight
Long Bets
an arena for competitive, accountable predictions, allowing a predictor to make a long-term prediction that specifies a date and a challenger to challenge the prediction, both putting money on a wager that will be paid off after the prediction’s date is passed.
first long bet
Kapor wagered no Turing test pass by 2029
Kurzweil challenged him
Kurzweil’s argument for winning long bet
exponential progress in computation, neuroscience, and nanotechnology, which taken together will allow for reverse engineering of the brain
Kapor’s argument
experiential learning
His main argument centers on the influence of our (human) physical bodies and emotions on our cognition
without the equivalent of a human body, and everything that goes along with it, a machine will never be able to learn all that’s needed to pass his and Kurzweil’s strict Turing test
