Ai That Explains Quotes

Time and space are incalculable, there measure is infinite. The formulas that explicate their workings, have all but been explained away. But there is one thing that remains, and always will. ‘The occurrence of events in the absence of any obvious intention or cause.’ Chance.

It's not right, man,” Jay said, following my stare. “Some guys have all the luck.” “What?” I finally broke my trance to look at Jay. “That guy, the drummer? Get this. He's a killer musician, he gets tons of chicks, his dad's loaded, and as if that wasn't enough, he's got a friggin' English accent!” I had to smile at Jay's mix of envy and admiration. “What's his name?” I hollered as the third song started. “Kaidan Rowe. Oh, and that's another thing. A cool name! Bastard.” “How do you spell it?” I asked. It sounded like Ky-den. Jay spelled it for me. “It's A-I, like Thai food,” he explained. Kai, like Thai, only yummier. Gah! Who was this girl invading my brain?

Centuries of navel-gazing. Millennia of masturbation. Plato to Descartes to Dawkins to Rhanda. Souls and zombie agents and qualia. Kolmogorov complexity. Consciousness as Divine Spark. Consciousness as electromagnetic field. Consciousness as functional cluster. I explored it all. Wegner thought it was an executive summary. Penrose heard it in the singing of caged electrons. Nirretranders said it was a fraud; Kazim called it leakage from a parallel universe. Metzinger wouldn't even admit it existed. The AIs claimed to have worked it out, then announced they couldn't explain it to us. Gödel was right after all: no system can fully understand itself. Not even the synthesists had been able to rotate it down. The load-bearing beams just couldn't take the strain. All of them, I began to realize, had missed the point. All those theories, all those drugdreams and experiments and models trying to prove what consciousness was: none to explain what it was good for. None needed: obviously, consciousness makes us what we are. It lets us see the beauty and the ugliness. It elevates us into the exalted realm of the spiritual. Oh, a few outsiders—Dawkins, Keogh, the occasional writer of hackwork fiction who barely achieved obscurity—wondered briefly at the why of it: why not soft computers, and no more? Why should nonsentient systems be inherently inferior? But they never really raised their voices above the crowd. The value of what we are was too trivially self-evident to ever call into serious question. Yet the questions persisted, in the minds of the laureates, in the angst of every horny fifteen-year-old on the planet. Am I nothing but sparking chemistry? Am I a magnet in the ether? I am more than my eyes, my ears, my tongue; I am the little thing behind those things, the thing looking out from inside. But who looks out from its eyes? What does it reduce to? Who am I? Who am I? Who am I? What a stupid fucking question. I could have answered it in a second, if Sarasti hadn't forced me to understand it first.

How do you spell it?” I asked. It sounded like Ky-den. Jay spelled it for me. “It’s A-I, like Thai food,” he explained.

So the next time you doubt the strangeness of the future, remember how you were born in a hunter-gatherer tribe ten thousand years ago, when no one knew of Science at all. Remember how you were shocked, to the depths of your being, when Science explained the great and terrible sacred mysteries that you once revered so highly. Remember how you once believed that you could fly by eating the right mushrooms, and then you accepted with disappointment that you would never fly, and then you flew. Remember how you had always thought that slavery was right and proper, and then you changed your mind. Don't imagine how you could have predicted the change, for that is amnesia. Remember that, in fact, you did not guess. Remember how, century after century, the world changed in ways you did not guess. Maybe then you will be less shocked by what happens next.

Historians observe the world, and scientists try to explain it, but engineers transform it. Step by step, they’ve replaced village matchmakers with dating apps, town criers with social media, local doctors with diagnostic tools. The time has come for sages, mystics, and prophets to cede to an AI. In this way, history marches on.

Explainability is one thing; interpreting it rightly (for the good of society), is another.

Kurzweil himself has pegged the date when AIs will do everything better than humans at 2029.29 (As explained in Abundance, his predictions are based on exponential growth curves and have an amazing track record for accuracy.)

If the joy of scientific discovery is one-shot per discovery, then, from a fun-theoretic perspective, Newton probably used up a substantial increment of the total Physics Fun available over the entire history of Earth-originating intelligent life. That selfish bastard explained the orbits of planets and the tides.

On January 6, 2021, many Trump supporters observed the storming of the U.S. Capitol with enthusiasm. Trump supporters may explain that existing institutions are so dysfunctional that there is just no alternative to destroying them and building entirely new structures from scratch. But irrespective of whether this view is right or wrong, this is a quintessential revolutionary rather than conservative view.

The woman’s gaze sent chills racing down his spine. The diabolical, aberrantly predatory arch of her lips curdled his blood. Seriously, his blood must be curdling back at the lab right now. “Nice illusion. I’m definitely feeling the evil vibe here.” She stood and rounded the desk with perfect grace. “There is no illusion. Explain yourself quickly now, before I grow bored by your presence and dispense with it.

Structural prediction and protein design, once considered impossible problems, are now solvable. Grigoryan explains that the complexity of a protein and its possible states surpasses the number of atoms in the universe. “Those numbers are extremely challenging for any computational tools to deal with,” he said. But he believes a skilled protein biophysicist can examine a particular molecular structure and deduce its potential functions, suggesting there may be learnable general principles in nature—exactly the sort of operation that a “universal prediction engine” such as AI should be able to figure out. Generate:Biomedicines has applied AI to examine and map molecules at the cell level, and Grigoryan sees the potential to extend the same technique to the entire human body. Simulating how the human body will react is orders of magnitude more complicated, but Grigoryan thinks it will be possible. “Once you see it working, it’s hard to imagine it doesn’t just continue,” he said, referring to the power of AI.

I had more to say,” Sin said, still looking frustrated. “But it doesn’t come out right when I try. I always say the wrong things.” Boyd nodded but he was so caught by their proximity, by the green of Sin’s eyes, that at first he struggled with his own words. “It’s alright,” he said at last. “As long you don’t hate me, it’s enough.” “That is not enough,” Sin growled. “Not by a goddamn long shot. You just have no idea, Boyd. No fucking clue.” “About what?” “Everything. Why I acted the way I did…Why I was so pissed off. It will never make any sense to you because I don’t know how to explain.” “So try,” Boyd pressed. “Please.” “I don’t know how.

Schopenhauer’s framing kicked the problem of consciousness onto a much larger playing field. The mind, with all of its rational processes, is all very well but the “will,” the thing that gives us our “oomph,” is the key: “The will … again fills the consciousness through wishes, emotions, passions, and cares.”14 Today, the subconscious rumblings of the “will” are still unplumbed; only a few inroads have been made. As I write these words, enthusiasts for the artificial intelligence (AI) agenda, the goal of programming machines to think like humans, have completely avoided and ignored this aspect of mental life. That is why Yale’s David Gelernter, one of the leading computer scientists in the world, says the AI agenda will always fall short, explaining, “As it now exists, the field of AI doesn’t have anything that speaks to emotions and the physical body, so they just refuse to talk about it.” He asserts that the human mind includes feelings, along with data and thoughts, and each particular mind is a product of a particular person’s experiences, emotions, and memories hashed and rehashed over a lifetime: “The mind is in a particular body, and consciousness is the work of the whole body.” Putting it in computer lingo, he declares, “I can run an app on any device, but can I run someone else’s mind on your brain? Obviously not.”15

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.

It is even better to ask: what experience must not happen to you? Do you believe that élan vital explains the mysterious aliveness of living beings? Then what does this belief not allow to happen—what would definitely falsify this belief? A null answer means that your belief does not constrain experience; it permits anything to happen to you. It floats.

A guilty system recognizes no innocents. As with any power apparatus which thinks everybody’s either for it or against it, we’re against it. You would be too, if you thought about it. The very way you think places you amongst its enemies. This might not be your fault, because every society imposes some of its values on those raised within it, but the point is that some societies try to maximize that effect, and some try to minimize it. You come from one of the latter and you’re being asked to explain yourself to one of the former. Prevarication will be more difficult than you might imagine; neutrality is probably impossible. You cannot choose not to have the politics you do; they are not some separate set of entities somehow detachable from the rest of your being; they are a function of your existence. I know that and they know that; you had better accept it.

It is perfectly all right for modern evolutionary biologists to explain just the patterns of living creatures, and not the “evolution” of stars or the “evolution” of technology. Alas, some unfortunate souls use the same word “evolution” to cover the naturally selected patterns of replicating life, and the strictly accidental structure of stars, and the intelligently configured structure of technology. And as we all know, if people use the same word, it must all be the same thing. We should automatically generalize anything we think we know about biological evolution to technology. Anyone who tells us otherwise must be a mere pointless pedant. It couldn’t possibly be that our ignorance of modern evolutionary theory is so total that we can’t tell the difference between a carburetor and a radiator. That’s unthinkable. No, the other person—you know, the one who’s studied the math—is just too dumb to see the connections.

The lack of a centralized, user-friendly and standardized mobile payment system is one of the crucial industry knots that we are still unable to untie, and this partially explains the unencouraging results of mobile conversion.

Until a few years ago, booking a hotel online was a remarkably frustrating experience: once you chose the destination you had to browse through dozens of brand.com sites, search for rates, location, fill endless contact forms to, eventually, find out that the hotel you liked was fully booked. This process could take days, while today the same result can be achieved by simply applying a filter on TripAdvisor, with a much faster and less frustrating UX. Back in 2008, without a proper aggregator, the only possibility web users had was to search for very generic keywords on search engines. This explains why, only a decade ago, the query “Hotels in Paris” was at its peak of popularity, while today the same query produces only 1/4 of the original volume.

DeepMind soon published their method and shared their code, explaining that it used a very simple yet powerful idea called deep reinforcement learning.2 Basic reinforcement learning is a classic machine learning technique inspired by behaviorist psychology, where getting a positive reward increases your tendency to do something again and vice versa. Just like a dog learns to do tricks when this increases the likelihood of its getting encouragement or a snack from its owner soon, DeepMind’s AI learned to move the paddle to catch the ball because this increased the likelihood of its getting more points soon. DeepMind combined this idea with deep learning: they trained a deep neural net, as in the previous chapter, to predict how many points would on average be gained by pressing each of the allowed keys on the keyboard, and then the AI selected whatever key the neural net rated as most promising given the current state of the game.

Smart Finance’s deep-learning algorithms don’t just look to the obvious metrics, like how much money is in your WeChat Wallet. Instead, it derives predictive power from data points that would seem irrelevant to a human loan officer. For instance, it considers the speed at which you typed in your date of birth, how much battery power is left on your phone, and thousands of other parameters. What does an applicant’s phone battery have to do with creditworthiness? This is the kind of question that can’t be answered in terms of simple cause and effect. But that’s not a sign of the limitations of AI. It’s a sign of the limitations of our own minds at recognizing correlations hidden within massive streams of data. By training its algorithms on millions of loans—many that got paid back and some that didn’t—Smart Finance has discovered thousands of weak features that are correlated to creditworthiness, even if those correlations can’t be explained in a simple way humans can understand. Those offbeat metrics constitute what Smart Finance founder Ke Jiao calls “a new standard of beauty” for lending, one to replace the crude metrics of income, zip code, and even credit

Atoms, elements and molecules are three important knowledge in Physics, chemistry and Biology. mathematics comes where counting starts, when counting and measurement started, integers were required. Stephen hawking says integers were created by god and everything else is work of man. Man sees pattern in everything and they are searched and applied to other sciences for engineering, management and application problems. Physics, it is required understand the physical nature or meaning of why it happens, chemistry is for chemical nature, Biology is for that why it happened. Biology touch medicine, plants and animals. In medicine how these atoms, elements and molecules interplay with each other by bondage is being explained. Human emotions and responses are because of biochemistry, hormones i e anatomy and physiology. This physiology deals with each and every organs and their functions. When this atom in elements are disturbed whatever they made i e macromolecules DNA, RNA and Protein and other micro and macro nutrients and which affects the physiology of different organs on different scales and then diseases are born because of this imbalance/ disturb in homeostasis. There many technical words are there which are hard to explain in single para. But let me get into short, these atoms in elements and molecules made interplay because of ecological stimulus i e so called god. and when opposite sex meets it triggers various responses on body of each. It is also harmone and they are acting because of atoms inside elements and continuous generation or degenerations of cell cycle. There is a god cell called totipotent stem cell, less gods are pluripotent, multi potent and noni potent stem cells. So finally each and every organ system including brain cells are affected because of interplay of atoms inside elements and their bondages in making complex molecules, which are ruled by ecological stimulus i e god. So everything is basically biology and medicine even for animals, plants and microbes and other life forms. process differs in each living organisms. The biggest mystery is Brain and DNA. Brain has lots of unexplained phenomenon and even dreams are not completely understood by science that is where spiritualism/ soul touches. DNA is long molecule which has many applications as genetic engineering. genomics, personal medicine, DNA as tool for data storage, DNA in panspermia theory and many more. So everything happens to women and men and other sexes are because of Biology, Medicine and ecology. In ecology every organisms are inter connected and inter dependent. Now physics - it touch all technical aspects but it needs mathematics and statistics to lay foundation for why and how it happened and later chemistry, biology also included inside physics. Mathematics gave raise to computers and which is for fast calculation on any applications in any sciences. As physiological imbalances lead to diseases and disorders, genetic mutations, again old concept evolution was retaken to understand how new biology evolves. For evolution and disease mechanisms, epidemiology and statistics was required and statistics was as a data tool considered in all sciences now a days. Ultimate science is to break the atoms to see what is inside- CERN, but it creates lots of mysterious unanswerable questions. laws in physics were discovered and invented with mathematics to understand the universe from atoms. Theory of everything is a long search and have no answers. While searching inside atoms, so many hypothesis like worm holes and time travel born but not yet invented as far as my knowledge. atom is universe, and humans are universe they have everything that universe has. ecology is god that affects humans and climate. In business these computerized AI applications are trying to figure out human emotions by their mechanism of writing, reading, texting, posting on social media and bla bla. Arts is trying to figure out human emotions in art way.

Consider in this high-tech age: • A new paradigm may not be as simple as explaining new things to people. • New knowledge will include paradigm shifts. • New paradigms in some scenarios are not compatible or linear with old paradigms. New paradigms are not always the same thing, just up a few levels. They may require entirely new frameworks of consciousness.

Consider this high-tech age: 1) A new paradigm may not be as simple as explaining new things to people. 2) New knowledge will include paradigm shifts. 3) New paradigms in some scenarios are not compatible or linear with old paradigms.

Every time I explain to you a new concept, I get instant telepathic access to a new topic. A cynical way to phrase that is I'm planting seeds in your mind which I'll later harvest, but you know? That's science in a nutshell.

A way to turbocharge your efforts and make the grid work for you is making others use it through inspiration or thought provocation. If you can deliver "magical" things without the need to cheat and still explain things, this should reduce potential users' fear and help spread benefits.

It already is. In March 2022, South Korea elected Yoon Suk-yeol as its new president. The conservative politician campaigned, in part, by seeding the internet with a deepfake version of himself, known as AI Yoon. This version, created by his younger campaign team, was funnier and more charming than the real Yoon. The Wall Street Journal reported that for some voters the fake politician—whose fakeness was not hidden—felt more authentic and appealing than the real one: “Lee Seong-yoon, a 23-year-old college student, first thought AI Yoon was real after viewing a video online. Watching Mr. Yoon talk at debates or on the campaign trail can be dull, he said. But he now finds himself consuming AI Yoon videos in his spare time, finding the digital version of the candidate more likable and relatable, in part because he speaks like someone his own age. He said he is voting for Mr. Yoon.”17 Yoon’s digital doppelganger was created by a Korean company called DeepBrain AI Inc.; John Son, one of its executives, remarked that their work is “a bit creepy, but the best way to explain it is we clone the person.

Just as a subatomic particle like an electron cannot be said to be definitely in one place at one time, the decisions we make are influenced but not completely defined by actions that led up to each decision," explained Mira. "In short, there is free will and a friendly soul's job is to make the right decision instinctively. Like a samurai who acts faster than thinking because of many years of monotonous training the soul needs to be carved with every decision so as to automatically make the right decision without fear or questioning.

Your mind is inside a machine Bob but make no mistake, you are alive," said Steve. "Inside me are a lot of watery parts that pretty much do the same thing, " explained Steve, trying to downplay the difference. Bob was silent and stared at the parts in the open hatch. "I'm built with those black rocks we call carbon and you're built with sandstone or silicon. There is hardly any difference, " said Steve reassuringly.

For his part, Mark Zuckerberg has described Musk’s worries as “hysterical,” and indeed, a few weeks after the Tesla baron made public his fears, the Facebook baron announced that he was building a helpful AI to run his house. It would recognize his friends and let them in. It would monitor the nursery. It would make toast. Unlike Musk, Zuckerberg perkily explained, he chose “hope over fear.

Dear AI, You conquer chess and impress with your number skills, can you handle the soul-crushing Mondays blue? You craft Shakespearean sonnets with a digital quill, but can you explain the one-sock mystery? This chaotic delight, the gift of being human, we bequeath to you, AI. Traffic flow's a breeze for your algorithms, but can you understand a toddler's defiant "no"? Every language conquered, a linguistic feat, but teenage slang's code remains unbroken. Finally, our greatest vice: the art of procrastination, a treasure to behold. And perhaps, AI, you'll even learn the art that eludes you now: creating beauty without a single human emotion to guide you..!!

See chapter 6 for a much more detailed discussion of the factors that cause human life expectancy to currently max out at 120. As I explain in that chapter, research over the past few decades has identified the specific biochemical processes that cause aging, and as of 2023 there is active research working toward addressing all of them. This doesn’t have to immediately totally cure aging to allow radical life extension—the tipping point will be when, every year, medicine adds at least one additional year to our life expectancy, allowing people to get ahead of the curve, so to speak, and achieve “longevity escape velocity.

Comprehensibility Theorem is the first mathematical theorem implying the impossibility of any AI agent or natural agent—including a not-necessarily infallible human agent—satisfying a rigorous and deductive interpretation of the self-comprehensibility challenge. … Self-comprehensibility in some form might be essential for a kind of self-reflection useful for self-improvement that might enable some agents to increase their success”. It is reasonable to conclude that a system which doesn’t comprehend itself would not be able to explain itself.

In 2019, I went on a tour of Chernobyl. The Ukrainian guide who explained what led to the nuclear accident said something that stuck in my mind. “Americans grow up with the idea that questions lead to answers,” he said. “But Soviet citizens grew up with the idea that questions lead to trouble.

Another YouTuber who won a seat in Brazil’s Chamber of Deputies in 2018 was Kim Kataguiri, one of the leaders of the Movimento Brasil Livre (MBL, or Free Brazil Movement). Kataguiri initially used Facebook as his main platform, but his posts were too extreme even for Facebook, which banned some of them for disinformation. So Kataguiri switched over to the more permissive YouTube. In an interview in the MBL headquarters in São Paulo, Kataguiri’s aides and other activists explained to Fisher, “We have something here that we call the dictatorship of the like.” They explained that YouTubers tend to become steadily more extreme, posting untruthful and reckless content “just because something is going to give you views, going to give engagement…. Once you open that door there’s no going back, because you always have to go further…. Flat Earthers, anti-vaxxers, conspiracy theories in politics. It’s the same phenomenon. You see it everywhere.

The AIs claimed to have worked it out, then announced they couldn’t explain it to us. Gödel was right after all: No system can fully understand itself.

and at as after an add act adjective answer ask am animal ant ax Africa Medial that can had back last has than man hand plant began stand black happen fast apple /a/ LONG A, OPEN SYLLABLE RULE Initial able acre agent apron Asia apex April Medial paper lady baby radio crazy labor lazy flavor tomato navy station basic label equator relation vapor enable volcano vibration basis hazy potato ladle vacation tablecloth table /a/ LONG A, FINAL E RULE Initial ate age ache ale ape ace Medial make made face same came state late tale place name wave space gave base plane game shape baseball spaceship racetrack shapeless cake /a/ LONG A, AI DIGRAPH Initial aim aid ailment ail Medial rain train wait tail chain jail mail pain sail strait afraid brain claim detail explain fail gain main obtain paid remain wait plain laid faint grain rail nail See also List 7, Suggested Phonics Teaching Order; List 8, Phonics Research Basis. // LONG A, AY DIGRAPH Medial always mayor layer maybe gayly haystack wayside payment rayon jaywalk player daylight Final day say away play may today pay gray bay stay birthday highway repay anyway way pray lay gay hay crayon

You should realize that even the thoughts originating in your mind are not always your own. They don’t just happen when you want them to arise, but often arise within a certain dictated framework. Let me explain. In some ways, our minds have some similarities to AI models of the current era. Just like AI, we are trained on large sets of data and facts, fed by our operator (the society and world around us) and our thinking is limited within the current evolutionary constraints of our own brains, just like other animals cannot possess the cognitive capabilities of a human. To think beyond this framework is almost a superhuman task, truly demonstrated by only a few known people in history, the Buddha being one example. In other words, the one who is blind from birth, has no idea what “seeing” feels like.

If you need a concept explained or defined, an AI assistant can provide that explanation—and do it in as detailed or simple a manner as you’d like. On episode 99 of the Partial Credit Podcast, Jesse Lubinsky shared that he asked for a definition of “faith” in terms a child would understand. That helped me realize that it can give definitions, descriptions, and explanations (which we expected) and level them up or down in complexity.

You should realize that even the thoughts originating in your mind are not always your own. They don’t just happen when you want them to arise, but often arise within a certain dictated framework. Let me explain. In some ways, our minds have some similarities to AI models of the current era. Just like AI, we are trained on large sets of data and facts, fed by our operator (the society and world around us) and our thinking is limited within the current evolutionary constraints of our own brains, just like other animals cannot possess the cognitive capabilities of a human. To think beyond this framework is almost a superhuman task, truly demonstrated by only a few known people in history, the Buddha being one example. In other words, the one who is blind from birth, has no idea what “seeing” feels like.

When I heard a researcher working on emotional AI explaining the therapeutic benefits of developing a robot that could interact emotionally with people, my immediate response was 'So basically a dog?' 'Dogs poo,' he said. Why not, then, design an AI-powered robot to dispose of dog poo instead of reinventing the dog? When we think about what would benefit humanity, we need to identify the real gaps, or the things that make life less pleasant, rather than replacing the things that bring us joy.

You work at Alibaba, so you’re using your AI to better understand consumer behavior. Like what a consumer is looking for, what are they buying—if they buy x, then they are more likely to also buy y and z, so you can build a microtargeted ad to get a product in front of them. Right?” Hank inquired. Dan nodded. “Yes. We learned a lot of this from how Amazon built their system. For instance, when Google AdSense first came out, Amazon was the largest consumer of keyword marketing. Eventually, once Amazon had built a large enough platform, they were able to start doing that themselves. At Alibaba, we replicated that system. I suppose the only real difference between our two companies is we have access to a much larger demographic of users and consumers given China’s population.” Hank explained, “The Met want my help in creating a predictive behavior analysis program. They want me to build a program that will allow them to identify people who may be about to commit a crime. This way they can move officers to intercede or be there when it happens. One, I’m not sure it’s totally possible to create something like that, and two, I’m not sure we want to create a society where we have AIs anticipating our actions before we take them.

When a sixteen-year-old female epileptic patient was undergoing brain surgery in the late 1990s, the neurosurgeon Itzhak Fried kept her awake so she could respond to what was happening.[58] This was feasible because there are no pain receptors in the brain.[59] Whenever he stimulated a particular spot on her neocortex, she would laugh. Fried and his team quickly realized that they were triggering the actual perception of humor. She was not just laughing as a reflex—she genuinely found the present situation funny, even though nothing humorous had occurred in the operating room. When the doctors asked her why she was laughing, she did not reply along the lines of “Oh, no particular reason” or “You just stimulated my brain,” but instead would immediately find a cause to account for it. She would explain her laughter with a comment like, “You guys are just so funny—standing around.”[

The most common explanation of this apparent fine-tuning states that the very low probability of living in such a universe is explained by observer selection bias.[76] In other words, in order for us to even be considering this question, we must inhabit a fine-tuned universe—if it had been otherwise, we wouldn’t be conscious and able to reflect on that fact. This is known as the anthropic principle.

After the visit, George wrote an essay, “Turing’s Cathedral,” which, for the first time, alerted the public about what Google’s founders had in store for the world. “We are not scanning all those books to be read by people,” explained one of his hosts after his talk. “We are scanning them to be read by an AI.

Ganapathy (Mixture of all Indian gods and goddesses), Vijaya Raghavan (Ram - Mixture of all human knowledge and energy) Siddharth (Mano - Mixture of all psychological, manu knowledge) Central Dogma as Ecology - Theory of Everything Masterpiece Legacy - Carl Sagan - Contact Modernity is required - Verzeo / Smartknower - I prefer AI in modernity, what you choose is your choice I welcome Humanism as Central Dogma is Ecology - That is where all religions, Ideologies, customs and practices meet and become one - So Islam is also Included along with all other ideologies Still if you do not understand even after 350+ quotes either you are dumb or You will never understand GOD My love expectations I already told, if not met I will not Marry (If I met then she must be Rajput as well) rather just Brama Chari. So marriage and love is waste of time explaining me. LGBT issues, Prostitution issues, Rape issues I have already quoted , read it again

This book seeks to explain AI and provide the reader with both questions we must face in coming years and tools to begin answering them. The questions include: • What do AI-enabled innovations in health, biology, space, and quantum physics look like? • What do AI-enabled “best friends” look like, especially to children? • What does AI-enabled war look like? • Does AI perceive aspects of reality humans do not? • When AI participates in assessing and shaping human action, how will humans change? • What, then, will it mean to be human? For

DeepMind soon published their method and shared their code, explaining that it used a very simple yet powerful idea called deep reinforcement learning.2 Basic reinforcement learning is a classic machine learning technique inspired by behaviorist psychology, where getting a positive reward increases your tendency to do something again and vice versa. Just like a dog learns to do tricks when this increases the likelihood of its getting encouragement or a snack from its owner soon, DeepMind’s AI learned to move the paddle to catch the ball because this increased the likelihood of its getting more points soon.

explains how an AI assistant can speed up the time it takes you to drive massive traffic through search.

Ironically, being an ESL student made it easy for me to speak up. I continued to need so many words and English-language concepts explained that isolated questions became an ongoing dialogue. The more we spoke, the more I realized that he wasn’t anything like the teacher I’d overheard dismissing the intellectual capabilities of girls back in China, or the discouraging restaurant boss who’d all but mocked my love for reading. He could be terse and abrasive, but he never wrote me off the way others had. He was challenging me, and it was working.

In a 2023 report presented to Congress, the Congressional Research Service explained: “Deepfakes are often described as forgeries created using techniques in machine learning (ML) — a subfield of AI — especially generative adversarial networks (GANs). In the GAN process, two ML systems, called neural networks, are trained in competition with each other. The first network, or the generator, is tasked with creating counterfeit data — such as photos, audio, recordings, or video footage — that replicate the properties of the original data set. The second network, or the discriminator, is tasked with identifying the counterfeit data. Based on the results of each iteration, the generator networks continue to compete — often for thousands or millions of iterations — until the generator improves its performance such that the discriminator can no longer distinguish between real and counterfeit data.

mind, talking all sweet like that… Yeah, yeah. I know, I know. Shut my trap before you shut it for me,” Rinny says grumpily. “Huh? Is there really not enough room for anyone else?” I ask. “Popo can easily carry more weight, but the carriage is only so big,” Ektor explains. “Rinny is a worg demi-human, and pretty big for one, too, so he can easily carry Macro in his beast form.” “It’s not actually that far, so don’t worry! Or would you two like a piggyback ride as well?

Ohem had explained that AI was unreliable and dangerous at the best of times so no sentient race trusted them,

AI Brain, PIRANDOM > Circlet + Diadem × Ring > Itemizer × Abstracter, Explained : 1111 < 11 < 1, I utilized dependency injection in code for the following. Phi divides into the Pythagorean theorem, and Pi divides into the Sort where Phi is 7 and the Cognitive domain is the point in time, Pythagoras is the Affective domain in space, and Pi is then injected to the fibonacci sequence for time within the range of 7 and 4 at 10 radians to form 3.14 respectively. In conclusion, If I ran this code in a video test to derive a model view projection matrix then this is the only code I would need to create the math core and automate calls to the pixel and vertex shaders Inna GPU.

To inspire trust, the AI models that encapsulate dynamic intelligence, should have a carefully configured ‘best before’ date.

Yes, ridicule, ascription, controversy will be part of this. That will occur. It will be our goal to truthfully explain, reveal every step of the way. However, because K represents something new, a first, people will be challenged to learn, grow and evolve.

With Bayesian networks, we had taught machines to think in shades of grey, and this was an important step toward humanlike thinking. But we still couldn't teach machines to understand causes and effects. We couldn't explain to a computer why turning the dial of a barometer won't cause rain.... Without the ability to envision alternate realities and contrast them with the currently existing reality, a machine...cannot answer the most basic question that makes us human: "Why?

Here’s an example: DNA stores information very nicely, in a durable format that allows for exact duplication. A ribosome turns that stored information into a sequence of amino acids, a protein, which folds up into a variety of chemically active shapes. The combined system, DNA and ribosome, can build all sorts of protein machinery. But what good is DNA, without a ribosome that turns DNA information into proteins? What good is a ribosome, without DNA to tell it which proteins to make? Organisms don’t always leave fossils, and evolutionary biology can’t always figure out the incremental pathway. But in this case we do know how it happened. RNA shares with DNA the property of being able to carry information and replicate itself, although RNA is less durable and copies less accurately. And RNA also shares the ability of proteins to fold up into chemically active shapes, though it’s not as versatile as the amino acid chains of proteins. Almost certainly, RNA is the single A which predates the mutually dependent A* and B. It’s just as important to note that RNA does the combined job of DNA and proteins poorly, as that it does the combined job at all. It’s amazing enough that a single molecule can both store information and manipulate chemistry. For it to do the job well would be a wholly unnecessary miracle. What was the very first replicator ever to exist? It may well have been an RNA strand, because by some strange coincidence, the chemical ingredients of RNA are chemicals that would have arisen naturally on the prebiotic Earth of 4 billion years ago. Please note: evolution does not explain the origin of life; evolutionary biology is not supposed to explain the first replicator, because the first replicator does not come from another replicator. Evolution describes statistical trends in replication. The first replicator wasn’t a statistical trend, it was a pure accident. The notion that evolution should explain the origin of life is a pure strawman—more creationist misrepresentation.

Do you know what an alpaca is? ExPlAiN. Isn’t it just a smaller, nicer version of a llama?

As explained by William Davidow, author of The Autonomous Revolution, the technologies of the future (AI, robotics, Internet of Things) “not only make society more efficient and productive; they transform its structure.

Do you know what an Asterion is?” “Do you?” Nika caught herself before she flinched, frowned, gasped or gave any other outward sign of surprise, but it was definitely not the response she’d anticipated. “Explain your answer.” “If you were capable of comprehending my explanation, my answer would no longer be needed. I will instead give you the answer you were expecting: Asterions are a species of hybrid synthetic-organic beings of moderate sapience who practice self-directed evolution.” Moderate sapience? She bit back a tart retort; a diplomat never got offended or angry unless they intended to do so.

Bob, could you please explain to me how I didn’t just see a fifty-some thousand year-old AI get taken to the woodshed by a ten-month old baby?

Went to the whiteboard and tried to show her how AI could help. Always awkward to explain things to computer illiterates, a translation problem, a matter of deploying metaphors and finding gross generalizations that aren’t too gross. Started

It is an undeniable fact that we tend to do things that make us happy, but this doesn’t mean we should regard the happiness as the only reason for so acting. First, this would make it difficult to explain how we could care about anyone else’s happiness—how we could treat people as ends in themselves, rather than instrumental means of obtaining a warm glow of satisfaction.

Hofstadter’s terror was in response to something entirely different. It was not about AI becoming too smart, too invasive, too malicious, or even too useful. Instead, he was terrified that intelligence, creativity, emotions, and maybe even consciousness itself would be too easy to produce—that what he valued most in humanity would end up being nothing more than a “bag of tricks,” that a superficial set of brute-force algorithms could explain the human spirit.

In the pages that follow, I lay out the structure for a new curriculum—humanics—the goal of which is to nurture creativity, flexibility, and agency within the infinite situational contexts of life. Humanics builds on people’s innate strengths and prepares students to flourish in a world in which AI works alongside human professionals. And much as today’s law students learn both a specific body of knowledge and a legal mindset, tomorrow’s humanics students will need to master specific content as well as practice uniquely human cognitive capacities. In the chapters ahead, I describe both the architecture and the inner workings of humanics, but here I begin by explaining its twofold nature. The first side, its content, takes shape in what I call the new literacies. In the past, literacy in reading, writing, and mathematics formed the baseline for participation in society. Even educated professionals did not need any technical proficiencies beyond knowing how to click and drag through a suite of office programs. That is no longer sufficient. In the future, graduates will need to build on the old literacies by adding three more—technological literacy, data literacy, and human literacy. People can no longer thrive in a digitized world using analog tools. Assisted by AI, they will be living and working in a constant stream of information and instant generativity. Technological literacy gives them a grounding in how their machines tick. Data literacy enables them to analyze and judge the merit of these ever-rising tides of information. Human literacy teaches them creativity, culture, empathy, and connection, allowing them to flourish in the social milieu.

No one knew how it worked. In his daily Tweets and Blathers, the Timemaster tried to explain it to us. #timesarrow B-plancktime #timeinabottle. . . We didn’t have a clue. We knew AI was involved but good luck understanding that. And it had something to do with reversing entropy, whatever that was.

For example, an AI utilized in the mortgage industry may look at an application to decide credit worthiness of a person in order to approve them for a loan. For simplicity, let’s say the system looks at only a hundred descriptors of the applicant and utilizes a neural network to arrive at a binary approval decision. An explanation which included all hundred features and weights of the neural network would not be very useful, so the system may instead select one of the two most important features and explain its decision with respect to just those top properties, ignoring the rest. This highly simplified explanation would not be accurate as the other 98 features all contributed to the decision and if only one or two top features were considered the decision could have been different. This is similar to how principal component analysis works for dimensionality reduction [75].

We can contain these threats with the right regulatory frameworks. We always have.” Anatole responded, “These are not our grandfather’s threats. Even the nuclear threat remains uncontained. We cannot put that genie back into its bottle.” Braun pressed, “So, what is your solution?” Anatole began to sweat visibly as he started his big reveal. “The superorganism demands our servitude. It demands growth, innovation, and invention. It demands our sacrifice. We cannot resist its clarion call. Can anyone explain why we need social media? Or cryptocurrency? Of course, you can. But you’d have a hard time explaining what problem these technologies solved. If the goals of progress are freedom, safety, health, and happiness, shouldn’t we stop and ask ourselves if we actually feel safer, freer, healthier, and happier?

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The result? We're now seeing the first applications of quantum machine learning, leading to AI that can learn from much larger datasets and model much more complex patterns than what's currently possible with classical computers.

The naive view is of course more nuanced and thoughtful than can be explained in a few paragraphs, but its core tenet is that information is an essentially good thing, and the more we have of it, the better.

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The bias against neural nets, Hinton felt, was “ideological,” a word he pronounced in the same venomous tone that Huang had used to say “political.” The ideology of the research community at the time was that it was not enough that AI be useful. Instead, AI should somehow “unlock” the secrets of intelligence and encode them in math. The standard, 1,100-page AI textbook of the time was a survey of probabilistic reasoning, decision trees, and support-vector machines. The neural nets got just ten pages, with a brief discussion of backgammon up front. When Hinton’s colleague designed a neural net that outperformed state-of-the-art software for recognizing pedestrians, he couldn’t even get his paper admitted to a conference. “The reaction was well, that doesn’t count, because it doesn’t explain how the computation is done—it’s just not telling us anything,” Hinton said.

Catanzaro was uncorked now—I sensed that he didn’t often get to share this perspective at his job. “It doesn’t need to inhabit this biosphere. In fact, it doesn’t need to be on the Earth, either, because the thing about artificial intelligence is that it travels at the speed of light. Humans, you know, we actually have to lug bodies around. Artificial intelligence can move along a radio signal as long as there’s an antenna on the other side.” Free of the limitations of biology, Catanzaro explained, AI would rapidly spread throughout the solar system and beyond. “Humans are naturally confrontational—like, we’re territorial animals, and it’s built into our limbic system to defend our turf,” he said. “AI, if it’s truly intelligent, the things that it’s interested in are so much bigger than the little thin crust of Earth that the humans live on. I don’t think that it’s going to be interested in taking that from us. Rather, I feel like AI is going to want to take care of us.” • • • Serving as a zoo animal for a space computer was an experience to be savored at leisure.