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Artificial Intelligence Quotes

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Artificial Intelligence Quotes

“Our brain is therefore not simply passively subjected to sensory inputs. From the get-go, it already possesses a set of abstract hypotheses, an accumulated wisdom that emerged through the sift of Darwinian evolution and which it now projects onto the outside world. Not all scientists agree with this idea, but I consider it a central point: the naive empiricist philosophy underlying many of today's artificial neural networks is wrong. It is simply not true that we are born with completely disorganized circuits devoid of any knowledge, which later receive the imprint of their environment. Learning, in man and machine, always starts from a set of a priori hypotheses, which are projected onto the incoming data, and from which the system selects those that are best suited to the current environment. As Jean-Pierre Changeux stated in his best-selling book Neuronal Man (1985), “To learn is to eliminate.”

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Book:How We Learn: Why Brains Learn Better Than Any Machine . . . for Now
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“Humans will add value where machines cannot. As we encounter more and more artificial intelligence, real intelligence, real empathy, and real common sense will be scarce. The new jobs will be predicated on know how to work with machines, but also on these uniquely human attributes.”

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Book:Hit Refresh: The Quest to Rediscover Microsoft's Soul and Imagine a Better Future for Everyone
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“Yann LeCun's strategy provides a good example of a much more general notion: the exploitation of innate knowledge. Convolutional neural networks learn better and faster than other types of neural networks because they do not learn everything. They incorporate, in their very architecture, a strong hypothesis: what I learn in one place can be generalized everywhere else. The main problem with image recognition is invariance: I have to recognize an object, whatever its position and size, even if it moves to the right or left, farther or closer. It is a challenge, but it is also a very strong constraint: I can expect the very same clues to help me recognize a face anywhere in space. By replicating the same algorithm everywhere, convolutional networks effectively exploit this constraint: they integrate it into their very structure. Innately, prior to any learning, the system already “knows” this key property of the visual world. It does not learn invariance, but assumes it a priori and uses it to reduce the learning space-clever indeed!”

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Book:How We Learn: Why Brains Learn Better Than Any Machine . . . for Now
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“The moral here is that nature and nurture should not be opposed. Pure learning, in the absence of any innate constraints, simply does not exist. Any learning algorithm contains, in one way or another, a set of assumptions about the domain to be learned. Rather than trying to learn everything from scratch, it is much more effective to rely on prior assumptions that clearly delineate the basic laws of the domain that must be explored, and integrate these laws into the very architecture of the system. The more innate assumptions there are, the faster learning is (provided, of course, that these assumptions are correct!). This is universally true. It would be wrong, for example, to think that the AlphaGo Zero software, which trained itself in Go by playing against itself, started from nothing: its initial representation included, among other things, knowledge of the topography and symmetries of the game, which divided the search space by a factor of eight. Our brain too is molded with assumptions of all kinds. Shortly, we will see that, at birth, babies' brains are already organized and knowledgeable. They know, implicitly, that the world is made of things that move only when pushed, without ever interpenetrating each other (solid objects)—and also that it contains much stranger entities that speak and move by themselves (people). No need to learn these laws: since they are true everywhere humans live, our genome hardwires them into the brain, thus constraining and speeding up learning. Babies do not have to learn everything about the world: their brains are full of innate constraints, and only the specific parameters that vary unpredictably (such as face shape, eye color, tone of voice, and individual tastes of the people around them) remain to be acquired.”

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Book:How We Learn: Why Brains Learn Better Than Any Machine . . . for Now
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“When I was young, my friends and I always tested the PIs level of patience. For example, when synthesizing the specialties of old-days, the one-time risk of eating those dishes was calculated for minutes. Of course, in the end, we always wolfed down the unique meals they declared inedible. For example, the so-called hamburger we wanted to eat forced the PIs to assess the scale of risks while we were slurping up a half a deciliter of synthesized fat.”

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Book:Conjunction
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“To think that we can or should all ‘go Amish’ and stick our heads in the sand with regard to technology is wishful thinking, but so too is the black-pilled fantasy that we can’t and shouldn’t use technology in our own projects and creations. In the end technology is just a contemporary iteration of Prometheus’s fire. It can burn, yes, and its smoke can blind our eyes. But it can also revolutionize our creativity and aid those of us employing it for higher than material purposes to shine a light through the shadows for anyone capable of seeing and following our freedom beacon.”

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Book:Get Out of Here Alive: Inner Alchemy & Immortality
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“People never expose themselves totally to others. We always hold back parts of our true selves. Perhaps because we do not totally understand those parts ourselves. Or perhaps it is a survival instinct to hold something back. In that way we cannot be totally controlled, or imprisoned. But if we have computers connected to our brain, then those freedoms will disappear. Everything will be seen, and there will be no place for our stream of consciousness to hide.”

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Author:Jack Freestone
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“...human beings need someone friendly to listen to them when they’re grieving. So feel free to talk to me. I will be friendly. You have nice shoes.” “Is that the only thing you notice about people?” “I’ve always wanted shoes. They’re the sole piece of clothing that makes any sense, assuming ideal environmental conditions. They don’t play into your strange and nonsensical taboos about not letting anyone see your—” “Is this really the only thing you can think of to comfort someone who is grieving?” “It was number one on my list.” Great. “The list has seven million entries. Do you want to hear number two?” “Is it silence?” “That didn’t even make the list.” “Move it to number two.” “All right, I . . . Oh.”

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Book:Skyward
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“I picked up a fallen branch and struck a tree with it. Apples fell from the tree. The rope around one of the skeletons gave way and it fell to the ground. It lay there, crumpled and bent in ridiculous angles. I wondered if the person who the skeleton used to live inside would be embarrassed if he or she could see themselves now. I looked around the area but didn’t see any ghosts. Why would I see a ghost? They didn’t exist. Still, I looked a second time.”

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Book:Orchard of Skeletons
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“The result will not be an Orwellian police state. We always prepare ourselves for the previous enemy, even when we face an altogether new menace. Defenders of human individuality stand guard against the tyranny of the collective, without realising that human individuality is now threatened from the opposite direction. The individual will not be crushed by Big Brother; it will disintegrate from within. Today corporations and governments pay homage to my individuality, and promise to provide medicine, education and entertainment customised to my unique needs and wishes. But in order to so, corporations and governments first need to break me up into biochemical subsystems, monitor these subsystems with ubiquitous sensors and decipher their working with powerful algorithms. In the process, the individual will transpire to be nothing but a religious fantasy. Reality will be a mesh of biochemical and electronic algorithms, without clear borders, and without individual hubs.”

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Book:Homo Deus: A History of Tomorrow
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“The awakening of machines will be similar to that of Man, only quicker. Humans, by comparison, are characterized and limited by their slow biological evolution, late realizations, and easy distractibility. Man is too rich and blessed to compete against the single-minded dedication of the binary brain.”

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Book:Super Dense Crush Load: The Story of Man Redux
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“In the era where artificial intelligence and algorithms make more decisions in our lives and in organizations, the time has come for people to tap into their intuition as an adjunct to today’s technical capabilities. Our inner wisdom can embed empirical data with humanity.”

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Book:small wins BIG SUCCESS: A handbook for exemplary success in post Covid19 Outbreak Era
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