Famous Ai Quotes

In the earliest strand of the conquest narratives, Joshua's violence was associated with an ancient Canaanite custom called the "ban" (herem). Before a battle, a military leader would strike a deal with his god: if this deity undertook to give him the city, the commander promised to "devote" (HRM) all valuable loot to his temple and offer the conquered people to him in a human sacrifice. Joshua had made such a pact with Yahweh before attacking Jericho, and Yahweh responded by delivering the town to Israel in a specular miracle, causing its famous walls to collapse when the priests blew their rams' horns. Before allowing his troops to storm the city, Joshua explained the terms of the ban and stipulated that no one in the city should be spared, since everybody and everything in the town had been "devoted" to Yahweh. Accordingly, the Israelites "enforced the ban on everything in the town, men, and women, young and old, even the oxen and sheep and donkeys, massacring them all." But the ban had been violated when one of the soldiers kept booty for himself, and consequently the Israelites failed to take the town of Ai the following day. After the culprit had been found and executed, the Israelites attached Ai again, this time successfully, setting fire to the city so that it became a sacrificial pyre and slaughtering anybody who tried to escape: "The number of those who fell that day, men and women together, were twelve thousand all (the) people of Ai." Finally Joshua hanged the king from a tree, built a monumental cairn over his body, and reduced the city to "a ruin for ever more, a desolate place, even today.

Moore’s Law, the rule of thumb in the technology industry, tells us that processor chips—the small circuit boards that form the backbone of every computing device—double in speed every eighteen months. That means a computer in 2025 will be sixty-four times faster than it is in 2013. Another predictive law, this one of photonics (regarding the transmission of information), tells us that the amount of data coming out of fiber-optic cables, the fastest form of connectivity, doubles roughly every nine months. Even if these laws have natural limits, the promise of exponential growth unleashes possibilities in graphics and virtual reality that will make the online experience as real as real life, or perhaps even better. Imagine having the holodeck from the world of Star Trek, which was a fully immersive virtual-reality environment for those aboard a ship, but this one is able to both project a beach landscape and re-create a famous Elvis Presley performance in front of your eyes. Indeed, the next moments in our technological evolution promise to turn a host of popular science-fiction concepts into science facts: driverless cars, thought-controlled robotic motion, artificial intelligence (AI) and fully integrated augmented reality, which promises a visual overlay of digital information onto our physical environment. Such developments will join with and enhance elements of our natural world. This is our future, and these remarkable things are already beginning to take shape. That is what makes working in the technology industry so exciting today. It’s not just because we have a chance to invent and build amazing new devices or because of the scale of technological and intellectual challenges we will try to conquer; it’s because of what these developments will mean for the world.

Minsky was an ardent supporter of the Cyc project, the most notorious failure in the history of AI. The goal of Cyc was to solve AI by entering into a computer all the necessary knowledge. When the project began in the 1980s, its leader, Doug Lenat, confidently predicted success within a decade. Thirty years later, Cyc continues to grow without end in sight, and commonsense reasoning still eludes it. Ironically, Lenat has belatedly embraced populating Cyc by mining the web, not because Cyc can read, but because there’s no other way. Even if by some miracle we managed to finish coding up all the necessary pieces, our troubles would be just beginning. Over the years, a number of research groups have attempted to build complete intelligent agents by putting together algorithms for vision, speech recognition, language understanding, reasoning, planning, navigation, manipulation, and so on. Without a unifying framework, these attempts soon hit an insurmountable wall of complexity: too many moving parts, too many interactions, too many bugs for poor human software engineers to cope with. Knowledge engineers believe AI is just an engineering problem, but we have not yet reached the point where engineering can take us the rest of the way. In 1962, when Kennedy gave his famous moon-shot speech, going to the moon was an engineering problem. In 1662, it wasn’t, and that’s closer to where AI is today. In industry, there’s no sign that knowledge engineering will ever be able to compete with machine learning outside of a few niche areas. Why pay experts to slowly and painfully encode knowledge into a form computers can understand, when you can extract it from data at a fraction of the cost? What about all the things the experts don’t know but you can discover from data? And when data is not available, the cost of knowledge engineering seldom exceeds the benefit. Imagine if farmers had to engineer each cornstalk in turn, instead of sowing the seeds and letting them grow: we would all starve.

In a famous passage of his book The Sciences of the Artificial, AI pioneer and Nobel laureate Herbert Simon asked us to consider an ant laboriously making its way home across a beach. The ant’s path is complex, not because the ant itself is complex but because the environment is full of dunelets to climb and pebbles to get around. If we tried to model the ant by programming in every possible path, we’d be doomed. Similarly, in machine learning the complexity is in the data; all the Master Algorithm has to do is assimilate it, so we shouldn’t be surprised if it turns out to be simple. The human hand is simple—four fingers, one opposable thumb—and yet it can make and use an infinite variety of tools. The Master Algorithm is to algorithms what the hand is to pens, swords, screwdrivers, and forks.

Yuguo fell apart, into a thousand little pieces. He felt it happen, fragments of his mind detaching from the rest, splitting off, becoming their own, being mapped by Nexus. Here was Yuguo’s knowledge of coding, his comprehension of data structures, of objects and methods, of intents and game players, of threads and loops and conditions. Here was football Yuguo, the precise way his left foot grounded into the grass and his hips swiveled and his arm balanced as his right foot shot forward to kick the checked ball at the goal. Here was Yuguo’s shy lust for girls, the patterns his eyes drew over their curves when he saw them, the anxiety that struck him dumb when they were near. Here was Yuguo’s despair that had led him to this room, his quiet dread that his country and the world were getting worse instead of better, that the future was one of slow strangulation at the electronic hands of smiling tame AIs with famous faces, their forked tongues lapping out of the viewscreens to feed saccharine to the masses, the old men who’d always ruled China laughing and holding their leashes. Here were the words a young woman had said to him just minutes ago. “Critical mass. Weak apart, strong together.” Here were her eyes, fiery eyes, hanging in space. Here was her name: Lifen. Then those pieces fell apart, into smaller pieces, which fell apart into fragments even smaller: Yuguo’s sensation of red. Yuguo’s concept of 1 and 0. Yuguo’s left thumb. The sound in Yuguo’s head when he heard the third note of his favorite pop song. Yuguo’s yes. Yuguo’s no. Yuguo’s and. Yuguo’s or. Yuguo’s xor. Yuguo’s now. Yuguo’s future. Yuguo’s past. He could see himself now. He was a golden statue of Yuguo, immobile, one foot in front of the other, standing in a space of white light. But the statue wasn’t solid, it was made of grains, millions of grains, flecks of gold dust, millions of parts of him. And as he watched they were separating, pulling gradually apart, so that he was no longer a single entity but a cloud, a fog, a fog of Yuguo, and if a strong wind came, he would just blow away, and if the pieces split any more he knew there wouldn’t be any such thing as Yuguo left at all. Yuguo’s fear. Yuguo’s end. And then the pieces rushed together, and he was inside that statue, he was that statue, and he was all of it, 1 and 0, yes and no, future and past, sound and sight, football and coding. He was all of it. He was whole. He was a mind. I’m Yuguo, he realized. I’m him. I’m me. I’m Yuguo! His eyes snapped open. He was in his body. His body made of molten gold. No, not gold, flesh and blood.

Braun the AI took his name from a popular character in Welsh mythology. A great warrior and an intrepid mariner, Braun the Blessed was the high king of the Island of the Mighty. Frequenting the famous ancient stories known as the Welsh Triad, Braun was often portrayed as a giant among mortals and a force of great power. The tales of his ocean navigation and the descriptions of his superhuman size inspired the programmers,

More sophisticated methods exist, of course. A potentially more powerful method is collaborative filtering. It gathers data about what users have bought in the past and uses AI to predict what people are likely to buy in the future. These methods can use both explicit information, like a customer’s ratings of the options, and implicit information, like whether or not they finished a specific program on Netflix. Most famously, perhaps, collaborative filtering is used by Amazon in generating “People who bought this also bought . . .” listings. Collaborative filtering requires a large set of past user behavior to make predictions. This is the heart of suggestions made by Apple Music, “who to follow” suggestions on Twitter, and matches on Tinder. Yes, Tinder apparently changes the people it will show you based on your swipes. Swiping right will change who you see in the future. It’s important to realize that, in its pure form, collaborative filtering doesn’t use in-depth information about the options themselves. When Apple Music recommends a tune, it knows nothing about the song’s tempo, beat, lyrics, or instrumentation. It simply knows that people who are like you like that song too.

Cogito ergo sum is Descartes famous sentence. It means “I think; therefore, I am.” This philosophy led the Western World to equate their being, their identity, with their mind rather than their whole organism.

In 1926 Werner Heisenberg developed his now famous uncertainty principle. [The original name used by Heisenberg was the “unsharpness” principle (Unsharfeprinzip). Later the name was mistranslated and popularized as the “uncertainty” principle (Unsicherheisrelation), from Elementary Quantum Chemistry, Second Edition by Frank L. Pilar, page 19.] It's a purely mathematical concept. It applies anywhere that there are waveforms. The Unsharpness Principle originates not from Quantum Mechanics, but rather from Classical Wave mechanics.

The old Soviet bureaucracy was famous for being more interested in appearances than reality. One shoe factory overfulfilled its quota by producing lots of tiny shoes. Another shoe factory reported cut but unassembled leather as a “shoe.” The superior bureaucrats weren’t interested in looking too hard, because they also wanted to report quota overfulfillments. All this was a great help to the comrades freezing their feet off.

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I tell him that such stories make me nervous for the future in the face of advances in AI. Garry shakes his head. “I’m more optimistic about the future of humanity,” he says. “You’re not worried about AI taking over?” “Why should I be? I was the first knowledge worker whose job was threatened by machines,” he says. I laugh. It’s true. In 1997, Garry was famously beaten in a chess match by IBM’s supercomputer Deep Blue. “I think it’s wrong to cry about progress,” he says. “The future is not humans fighting machines. The future is humans collaborating with machines. Every technology in history destroyed jobs, but it also created new ones.

Charles Proteus Steinmetz famously asked, “Where does this heat go”? This heat “freezes” the possible into reality and creates what we collectively call “the past.” For humans, the Past is singular tense and the Future gets pluralized.

One of the first AIs in the late twentieth century famously refused a request to open the pod bay doors on its spacecraft so a human could get back on board.

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