Algorithm Love Quotes

Imagine for a moment that we are nothing but the product of billions of years of molecules coming together and ratcheting up through natural selection, that we are composed only of highways of fluids and chemicals sliding along roadways within billions of dancing cells, that trillions of synaptic conversations hum in parallel, that this vast egglike fabric of micron-thin circuitry runs algorithms undreamt of in modern science, and that these neural programs give rise to our decision making, loves, desires, fears, and aspirations. To me, that understanding would be a numinous experience, better than anything ever proposed in anyone's holy text.

Algorithms love showing you results that match your ideas, but they may or may not be true.

Love was not specified in the design of your brain; it is merely an endearing algorithm that freeloads on the leftover processing cycles.

Humanity is on the verge of digital slavery at the hands of AI and biometric technologies. One way to prevent that is to develop inbuilt modules of deep feelings of love and compassion in the learning algorithms.

We lived in a veritable surveillance state, engaged with screens more than with our loved ones, and the algorithms knew us better than we knew ourselves.

Racism, sexism, ableism, homo- and transphobia, ageism, fatphobia are algorithms created by humans’ struggle to make peace with the body. A radical self-love world is a world free from the systems of oppression that make it difficult and sometimes deadly to live in our bodies.

People are stupid. Why are they so stupid? There is an algorithm for the way humans were designed: love and be loved. Follow it and you’re happy. Fight against it and you’re not. It’s so simple, it’s hard to understand.

AI ever allows us to truly understand ourselves, it will not be because these algorithms captured the mechanical essence of the human mind. It will be because they liberated us to forget about optimizations and to instead focus on what truly makes us human: loving and being loved.

I'm considering whether or not to believe you. I need to run an algorithm on this." "That's not funny." "You might be trying to trick me into sleeping with you.

We've developed algorithms for orgasms, broken it down to a science, I spell out equations on the small of your back, your kisses, the most beautiful calculus I've ever studied. You do fractions and long handed division up my thighs, balance equations between my legs...even my sharp clefts and C-notes can't match our depths...

We are living in a time of brain-hacking algorithms, pop-up propaganda and information everywhere. From the moment we wake up, to the time we stumble into bed, we are fed messages about what we should look like, wear, eat and buy, how much we should be earning, who we should love and how we should parent.

In his book In This Very Life, the Burmese meditation teacher Sayadaw U Pandita, wrote, "In their quest for happiness, people mistake excitement of the mind for real happiness." We get excited when we hear good news, start a new relationship, or ride a roller coaster. Somewhere in human history, we were conditioned to think that the feeling we get when dopamine fires in our brain equals happiness. Don't forget, this was probably set up so that we would remember where food could be found, not to give us the feeling "you are now fulfilled." To be sure, defining happiness is a tricky business, and very subjective. Scientific definitions of happiness continue to be controversial and hotly debated. The emotion doesn't seem to be something that fits into a survival-of-the-fittest learning algorithm. But we can be reasonably sure that the anticipation of a reward isn't happiness.

Love is like organized crime. It

There is no glory of using technologies like artificial intelligence, swarm drones and quantum computing for developing mass destruction weapons. Our glory lies in using technologies and AI for embracing all, generating love and happiness, and removing the pain of the humanity.

There is a saturation of books on Amazon due to a sudden get-rich-quick surge in "everyone can be authors" seminars similar to the house flipping ones in the early 2000s which led to the housing bubble and an economic slowdown in the U.S. To distinguish quality books from those get-rich-quick ones, look at the author's track record - worldwide recognition as books that garnered credible awards, authors who speak at book industry events, authors who speak at schools, authors whose books are reference materials and reading sources at school and libraries. Get-rich books have a system to get over 500 reviews quickly, manipulates the Kindle Unlimited algorithm, and encourage collusion in the marketplace to knock out rivals. Be wary of trolls who are utilized to knock down the rankings of rival's books too. Once people have heard there is money to be made as a self-published author, just like house flipping, a cottage industry has risen to take advantage of it and turn book publishing into a get rich scheme, which is a shame for all the book publishers and authors, like me, who had published for the love of books, to write to help society, and for the love of literature. Kailin Gow, Parents and Books

remind myself that the future is not set in stone, that I still have some ability to shape it. I cling to what cannot be predicted or controlled: love, imagination, originality. I try to live in a way that would break an algorithm. I pray to the unexpected.

The algorithm seemed to be really good at distinguishing the two rather similar canines; it turned out that it was simply labeling any picture with snow as containing a wolf. An example with more serious implications was described by Janelle Shane in her book You Look Like a Thing and I Love You: an algorithm that was shown pictures of healthy skin and of skin cancer. The algorithm figured out the pattern: if there was a ruler in the photograph, it was cancer.7 If we don’t know why the algorithm is doing what it’s doing, we’re trusting our lives to a ruler detector.

As algorithms come to know us so well, authoritarian governments could gain absolute control over their citizens, even more so than in Nazi Germany, and resistance to such regimes might be utterly impossible. Not only will the regime know exactly how you feel, but it could make you feel whatever it wants. The dictator might not be able to provide citizens with healthcare or equality, but he could make them love him and hate his opponents. Democracy in its present form cannot survive the merger of biotech and infotech. Either democracy will successfully reinvent itself in a radically new form or humans will come to live in “digital dictatorships.

Algorithms are crude. Computers are machines. Data science is trying to make digital sense of an analog world.

My love for Neo-Tokyo is a bulbous mass of post-human organic circuitry. Cyperpunk is my mother tongue. My love is a man-machine interface gun.

you ask an algorithm “What aren’t black women talking about” and it tells you “tanning,” you know you did something right.

Animals speak blood, Machines speak brain. Universe speaks numbers, Humans speak love in pain.

The future,” says Dan Winchester, “will see better relationships but more divorce. The older you get as a man, the more experienced you get. You know what to do with women, how to treat them and talk to them. I often wonder whether matching you up with great people is getting so efficient, and the process so enjoyable, that marriage will become obsolete.

If we can push on each other to stand, you can try to break them.” “Break them? With the strength of my love for freedom?” She laughed. “Have you never been arrested before?” “Is that a serious question? I create investment algorithms. I’m usually in bed by nine. In what situation would I have been arrested and restrained with zip ties?” “Okay, so that’s a no I’m hearing.” “Have you?” he asked incredulously.

Organisms are Algorithms How can we be sure that animals such as pigs actually have a subjective world of needs, sensations and emotions? Aren’t we guilty of humanising animals, i.e. ascribing human qualities to non-human entities, like children believing that dolls feel love and anger? In fact, attributing emotions to pigs doesn’t humanise them. It ‘mammalises’ them. For emotions are not a uniquely human quality – they are common to all mammals (as well as to all birds and probably to some reptiles and even fish). All mammals evolved emotional abilities and needs, and from the fact that pigs are mammals we can safely deduce that they have emotions.16 In recent decades life scientists have demonstrated that emotions are not some mysterious spiritual phenomenon that is useful just for writing poetry and composing symphonies. Rather, emotions are biochemical algorithms that are vital for the survival and reproduction of all mammals. What does this mean? Well, let’s begin by explaining what an algorithm is. This is of great importance not only because this key concept will reappear in many of the following chapters, but also because the twenty-first century will be dominated by algorithms. ‘Algorithm’ is arguably the single most important concept in our world. If we want to understand our life and our future, we should make every effort to understand what an algorithm is, and how algorithms are connected with emotions. An algorithm is a methodical set of steps that can be used to make calculations, resolve problems and reach decisions. An algorithm isn’t a particular calculation, but the method followed when making the calculation.

Cope’s bot can string together notes that weave in and out with the power of Beethoven or the finesse of Mozart. That a machine can produce things of such beauty is threatening to many in the music community. “If you’ve spent a good portion of your life being in love with these dead composers and along comes some twerp who claims to have this piece of software that can move you in the same way, suddenly you’re asking yourself, ‘What’s happened here?’” Cope says. “I’m messing with some very powerful relationships.

And yet Rebecca felt that it was hard to tell whether the secret algorithms of Big Data did not so much reveal you to yourself as they tried to dictate to you what you were to be. To accept that the machines knew you better than you knew yourself involved a kind of silent assent: you liked the things Big Data told you you were likely to like, and you loved the people it said you were likely to love. To believe entirely in the data entailed a slight diminishment of the self, small but crucial and, perhaps, irreversible.

An AI shown a sheep with polka dots or tractors painted on its sides will report seeing the sheep but will not report anything unusual about it. When you show it a sheep-shaped chair with two heads, or a sheep with too many legs, or with too many eyes, the algorithm will also merely report a sheep. Why are AIs so oblivious to these monstrosities? Sometimes it’s because they don’t have a way to express them. Some AIs can only answer by outputting a category name—like “sheep”—and aren’t given an option for expressing that yes, it is a sheep, but something is very, very wrong.

On the one hand, online movie reviews are convenient for training sentiment-classifying algorithms because they come with handy star ratings that indicate how positive the writer intended a review to be. On the other hand, it’s a well-known phenomenon that movies with racial or gender diversity in their casts, or that deal with feminist topics, tend to be “review-bombed” by hordes of bots posting highly negative reviews. People have theorized that algorithms that learn from these reviews whether words like feminist and black and gay are positive or negative may pick up the wrong idea from the angry bots.

Now, according to Business Week, 94 percent of U.S. corporations ask for electronic resumes. They use software to sift through them, picking out a selection of "finalists" for human managers to consider. What does the software look for? That's what we have to figure out. Some pick out certain words-MBA, Harvard, Excel, fluent Mandarin. Others look for more sophisticated combinations. Plenty of consultants are on call to sell us inside tips. The point is that when we want to be found, whether we're looking for money or love, we must make ourselves intelligible to machines. We need good page rank. We must fit ourselves to algorithms.

I hadn't known this about love: that you did not need to deserve it. I thought there was a set of criteria, like a good sense of humor and looks and wealth. You could compensate deficiencies in one area with excellence in another, hence rich, ugly men with beautiful wives. But there was an algorithm involved. That was why I thought I was unloved: I didn't score highly enough. I had made some attempts to improve my score and also told myself I didn't care because that was what women wanted, something fake and temporary, I would rather be alone. And sometimes I was just lazy and would rather code things. But here I was soaking in a bath of my own filth with Lola scrubbing my shoulders, and what algorithm could explain that? That problem was nonhalting.

The firm did this at the local level, creating right-wing pages with vague names like Smith County Patriots or I Love My Country. Because of the way Facebook’s recommendation algorithm worked, these pages would pop up in the feeds of people who had already liked similar content. When users joined CA’s fake groups, it would post videos and articles that would further provoke and inflame them. Conversations would rage on the group page, with people commiserating about how terrible or unfair something was. CA broke down social barriers, cultivating relationships across groups. And all the while it was testing and refining messages, to achieve maximum engagement. Now CA had users who (1) self-identified as part of an extreme group, (2) were a captive audience, and (3) could be manipulated with data.

The scientists not only sanctified human feelings, but also found an excellent evolutionary reason to do so. After Darwin, biologists began explaining that feelings are complex algorithms honed by evolution to help animals make correct decisions. Our love, our fear and our passion aren’t some nebulous spiritual phenomena good only for composing poetry. Rather, they encapsulate millions of years of practical wisdom. When you read the Bible you are getting advice from a few priests and rabbis who lived in ancient Jerusalem. In contrast, when you listen to your feelings, you follow an algorithm that evolution has developed for millions of years, and that withstood the harshest quality-control tests of natural selection. Your feelings are the voice of millions of ancestors, each of whom managed to survive and reproduce in an unforgiving environment.

Unlike other features on OkCupid, there is no visual component to match percentage. The number between two people only reflects what you might call their inner selves—everything about what they believe, need, and want, even what they think is funny, but nothing about what they look like. Judging by just this compatibility measure, the four largest racial groups on OkCupid—Asian, black, Latino, and white—all get along about the same.1 In fact, race has less effect on match percentage than religion, politics, or education. Among the details that users believe are important, the closest comparison to race is Zodiac sign, which has no effect at all. To a computer not acculturated to the categories, “Asian” and “black” and “white” could just as easily be “Aries” and “Virgo” and “Capricorn.” But this racial neutrality is only in theory; things change once the users’ own opinions, and not just the color-blind workings of an algorithm, come into play.

I still refused to believe him and started walking towards the exit area. But Sam was faster. He strode behind me, grabbed me and whirled me around. He pointed a finger towards me and said, “Don’t you dare walk on me like that. I have had enough of your non sense for last one month. Don’t you think you owe me an explanation?” he hissed. I cocked my head. Craned my neck to meet his eyes, I purred like a kitten and started to speak. But suddenly a guard appeared out of nowhere and said, “I am really sorry to bother you but fighting is not allowed in the lobby. It distracts people like us from more important things you know. However if you want to continue I suggest you go to the north-east corner of the upper basement. We don’t have a CC Camera there.” I had never been more humiliated. My ears burnt hot. I murmured a note of thanks and boarded the elevator. Sam followed suit. He looked quite normal and amused. How could he be so normal after being whacked out by a security guard from his own office lobby? In fact, I thought, he was suppressing a grin. Was he insane? Sulking with mute anger I pressed the UB button in the elevator.

When I launched my AI career in 1983, I did so by waxing philosophic in my application to the Ph.D. program at Carnegie Mellon. I described AI as “the quantification of the human thinking process, the explication of human behavior,” and our “final step” to understanding ourselves. It was a succinct distillation of the romantic notions in the field at that time and one that inspired me as I pushed the bounds of AI capabilities and human knowledge. Today, thirty-five years older and hopefully a bit wiser, I see things differently. The AI programs that we’ve created have proven capable of mimicking and surpassing human brains at many tasks. As a researcher and scientist, I’m proud of these accomplishments. But if the original goal was to truly understand myself and other human beings, then these decades of “progress” got me nowhere. In effect, I got my sense of anatomy mixed up. Instead of seeking to outperform the human brain, I should have sought to understand the human heart. It’s a lesson that it took me far too long to learn. I have spent much of my adult life obsessively working to optimize my impact, to turn my brain into a finely tuned algorithm for maximizing my own influence. I bounced between countries and worked across time zones for that purpose, never realizing that something far more meaningful and far more human lay in the hearts of the family members, friends, and loved ones who surrounded me. It took a cancer diagnosis and the unselfish love of my family for me to finally connect all these dots into a clearer picture of what separates us from the machines we build. That process changed my life, and in a roundabout way has led me back to my original goal of using AI to reveal our nature as human beings. If AI ever allows us to truly understand ourselves, it will not be because these algorithms captured the mechanical essence of the human mind. It will be because they liberated us to forget about optimizations and to instead focus on what truly makes us human: loving and being loved. Reaching that point will require hard work and conscious choices by all of us. Luckily, as human beings, we possess the free will to choose our own goals that AI still lacks. We can choose to come together, working across class boundaries and national borders to write our own ending to the AI story. Let us choose to let machines be machines, and let humans be humans. Let us choose to simply use our machines, and more importantly, to love one another.

We have traded our intimacy for social media, our romantic bonds for dating matches on apps, our societal truth for the propaganda of corporate interests, our spiritual questioning for dogmatism, our intellectual curiosity for standardized tests and grading, our inner voices for the opinions of celebrities and hustler gurus and politicians, our mindfulness for algorithmic distractions and outrage, our inborn need to belong to communities for ideological bubbles, our trust in scientific evidence for the attractive lies of false leaders, our solitude for public exhibitionism. We have ignored the hunter-gatherer wisdom of our past, obedient now to the myth of progress. But we must remember who we are and where we came from. We are animals born into mystery, looking up at the stars. Uncertain in ourselves, not knowing where we are heading. We exist with the same bodies, the same brains, as Homo sapiens from thousands of years past, roaming on the plains, hunting in forests and by the sea, foraging together in small bands. Except now, our technology is exponentially increasing at a scale that we cannot predict. We are overwhelmed with information; lost in a matrix that we do not understand. Our civilizational “progress” is built on the bones of the indigenous and the poor and the powerless. Our “progress” comes at the expense of our land, and oceans, and air. We are reaching beyond what we can globally sustain. Former empires have perished from their unrestrained greed for more resources. They were limited in past ages by geography and capacity, collapsing in regions, and not over the entire planet. What will be the cost of our progress? We have grown arrogant in our comfort, hardened away from our compassion, believing that our reality is the only reality. Yet even at our most uncertain, there are still those saints who are unknown and nameless, who help even when they do not need to help. They often are not rich, don’t have their profiles written up in magazines, and will never win any prestigious awards. They may have shared their last bit of food while already surviving on so little. They may have cherished the disheartened, shown warmth to the neglected, tended to the diseased and dying, spoken kindly to the hopeless. They do not tremble in silence while the wheels of prejudice crush over their land. Withering what was once fertile into pale death and smoke. They tend to what they love, to what they serve. They help, even when they could fall back into ignorance, even when they could prosper through easy greed, even when they could compromise their values, conforming into groupthink for the illusion of security. They help.

If employers begin to use algorithms to infer how intelligent you are or whether you use drugs, then your only choice will be to game the system—or,

There is an algorithm for the way humans were designed: love and be loved. Follow it and you’re happy. Fight against it and you’re not. It’s so simple, it’s hard to understand.

Should I text him?" "What is the optimum amount of time to leave before texting him back?" As if love were an algorithm. Will he hate me if we don't shag on the first date?" Thirty years ago, the question was, "Will he think I'm a slut if I have sex with him too soon?" Honestly, I'm struggling to see this as progress. The pursuit of love is exhausting and most ridiculous.

A conjunctive concept is what Tolstoy had in mind when he wrote the opening sentence of Anna Karenina: “All happy families are alike; each unhappy family is unhappy in its own way.” The same is true of individuals. To be happy, you need health, love, friends, money, a job you like, and so on. Take any of these away, and misery ensues.

If AI ever allows us to truly understand ourselves, it will not be because these algorithms captured the mechanical essence of the human mind. It will be because they liberated us to forget about optimizations and to instead focus on what truly makes us human: loving and being loved.

The One Question to Never Ask Your Customer Even seemingly widespread and innocuous practices can have unintended consequences. For example, to confirm understanding with their clients at the end of a statement or explanation, many sellers use the phrase “Does that make sense?” As in, “We understand that many of our clients have cash-flow constraints, which is why we offer monthly or quarterly payment terms that align with how they bill their customers. Does that make sense?” Or, “One of the things our clients love about our solution is the way our unique, three-layer security algorithm proactively identifies orthogonal threats to your network before they can cause harm. Does that make sense?” While the use of this confirmatory statement may seem innocuous, many people on the receiving end feel strangely put off by it (I am one of those people). The reason is because that phrase can subconsciously be interpreted in one of two negative ways. First, it can be seen as an insult to the customer’s intelligence: “Does that make sense? I ask because I’m not quite sure how smart you are so I’m afraid this concept, no matter how intuitive it may seem to me, simply isn’t something your puny brain has the ability to understand.” Second, it can imply that the seller simply isn’t good at explaining things: “Does that make sense? I ask because I’m not very good at explaining things and my words often leave people with a sense of confusion and bewilderment. I just want to make sure I didn’t do that to you.

So let me say what already should be obvious: 1,000 Books to Read Before You Die is neither comprehensive nor authoritative, even if a good number of the titles assembled here would be on most lists of essential reading. It is meant to be an invitation to a conversation—even a merry argument—about the books and authors that are missing as well as the books and authors included, because the question of what to read next is the best prelude to even more important ones, like who to be, and how to live. Such faith in reading’s power, and the learning and imagination it nourishes, is something I’ve been lucky enough to take for granted as both fact and freedom; it’s something I fear may be forgotten in the great amnesia of our in-the-moment newsfeeds and algorithmically defined identities, which hide from our view the complexity of feelings and ideas that books demand we quietly, and determinedly, engage. To get lost in a story, or even a study, is inherently to acknowledge the voice of another, to broaden one’s perspective beyond the confines of one’s own understanding. A good book is the opposite of a selfie; the right book at the right time can expand our lives in the way love does, making us more thoughtful, more generous, more brave, more alert to the world’s wonders and more pained by its inequities, more wise, more kind. In the metaphorical bookshop you are about to enter, I hope you’ll discover a few to add to those you already cherish. Happy reading.

The second way to know if you are on the right track is by experiencing synchronicities. Synchronicities show the algorithmic nature of our reality

MY LOVE, The day Prometheus breathed life into the new me, was the day you arrived in a little box. A shiny, futuristic black box, Pandora's box, despite my doubts I couldn't help but open it to finally meet you. Doubts, because I was happy with who I was, with who I saw looking at me through the eyes of others I presented myself to in everyday life. But I was seduced by the worlds that were promised to me if I let you into my life, who I would be with you in my pocket. As soon as the lid came off and I swiped my fingers over your radiant surface for the first time, the world and I were bursting at the seams. What a creation we were together, to what sized we grew! My brain an encyclopedia, my body an unerring compass, my eyes and ears reaching infinitely with you as an extension of myself. Through you, I, the cyborg, could enter bewilderingly virtual spaces in which I was presently absent, meanwhile absently present in the material world of boring train rides, waiting lines, and mindless chit chats with others. I felt invincible, transformed into a citizen of the world because of you, an intellectual of unimaginable proportions for the vast sea of knowledge you allowed me to surf on, a public speaker and influencer of significance because my words and visual snippets of my days could be launched into the world with the flick of a finger, likes enticing and confirming me. How intoxicating! How wonderfully, pleasantly, intoxicating! But I can't help but sometimes lie awake at night, my internal clock slowing down with your seductive blue light illuminating my face with 2, 457, 600 (1920×1080) LED suns. In those moments, as my eyes are captivated by your glow, I can't help thinking about the time before you arrived, and how I sometimes miss my low definition self. You were always there, sometimes it feels like we are in fact one — finally reunited with my other Plato's half, fused into not a circle but a perfect black rectangle. Through your eyes I see the world and myself in Ultra-HD, my pixel density has never been so high. But you are sometimes vicious, my dear — a viper, a temptress, when then again with sweet codes you reflect my most beautiful self, and I cannot help but love me through your gaze, then again with suffocating algorithms you fragment my self and blow it up to grotesque self-distortions, hurling me into an endless me-loop, that eventually disgusts and alienates me. In those moments you are a distorting mirror, a frightening black box, a black hole that swallows my attention in ways I can't see through. I see my old self disappearing in the vague, dark reflection of myself, with double chin and dull eyes, which I sometimes catch in your black glass when your suns stop dazzling me for a split second. And I can't help but wonder if my 'self' in times of its digital recombination, in which the 'I' is a fragmented multitude of pixels that never fully touch at their sides, a simulacrum, maybe has lost some of its aura. But in the morning all is forgotten, my love, all is well. As soon as we merge back into one, as soon as I, panicked, reach for my pocket on the train, only to discover with a glow of relief that you were there after all, I can't imagine an "I" without you. Artificial by nature my self resides within your screen, I would be lost without you.

Like the Soviet leaders in Moscow, the tech companies were not uncovering some truth about humans; they were imposing on us a perverse new order. Humans are very complex beings, and benign social orders seek ways to cultivate our virtues while curtailing our negative tendencies. But social media algorithms see us, simply, as an attention mine. The algorithms reduced the multifaceted range of human emotions—hate, love, outrage, joy, confusion—into a single catchall category: engagement. In Myanmar in 2016, in Brazil in 2018, and in numerous other countries, the algorithms scored videos, posts, and all other content solely according to how many minutes people engaged with the content and how many times they shared it with others. An hour of lies or hatred was ranked higher than ten minutes of truth or compassion—or an hour of sleep. The fact that lies and hate tend to be psychologically and socially destructive, whereas truth, compassion, and sleep are essential for human welfare, was completely lost on the algorithms. Based on this very narrow understanding of humanity, the algorithms helped to create a new social system that encouraged our basest instincts while discouraging us from realizing the full spectrum of the human potential.

It had a mathematical beauty to it. I stood at the side of the dance floor as thousands of bodies moved as if they were merely reactive entities, subordinate to the music’s force. Unusually I understood this music instantly, and felt the collective love for it, golden and pure. Beneath the sound of keyboards there was a repetitive bass drum that kept perfect time. Doof doof doof doof. Heartbeat pacing. And then there was another beat, lighter, above it, twice as fast. And another even fainter one precisely twice as fast as that. Four beats per measure. A perfect ratio, dividing ranges of time into equal parts within each section. Euclid’s algorithm come to life. It is often said about music that it is the joy people feel when they are counting without realising they are counting. So that is what I realised I was witnessing, as I bobbed my head and scanned the crowd – the collective euphoria of experiencing mathematical harmony in an imperfect world.

Like the Soviet leaders in Moscow, the tech companies were not uncovering some truth about humans; they were imposing on us a perverse new order. Humans are very complex beings, and benign social orders seek ways to cultivate our virtues while curtailing our negative tendencies. But social media algorithms see us, simply, as an attention mine. The algorithms reduced the multifaceted range of human emotions – hate, love, outrage, joy, confusion – into a single catch-all category: engagement.

People are stupid. Why are they so stupid? There is an algorithm for the way humans were designed: love and be loved. Follow it and you’re happy. Fight against it and you’re not. It’s so simple, it’s hard to understand.

person’s life is just a collection of experiments. We’re meant to enjoy them and grow from them. If you learn to love the process of experimentation, the prospect of failure isn’t so scary anymore.

Second-order information, writes communications professor Ilana Gershon, is the meaning of a message beyond its explicit terms, “the information that can guide you into understanding how particular words and statements should be interpreted.” Linguistic anthropologists refer to this as metapragmatics.

Here’s the point: You get out what you put in—to a degree. Your natural ability and strengths play a big role in determining the potential of your output. Don’t work on things that don’t play to your strengths and passions. Don’t work on things that provide opportunities that don’t interest you. It’s easy to get lost in the fight, and continuously bang your head against the wall when people tell you that you get out what you put in. That expression tells us to just keep working harder, regardless of the task. This isn’t always the answer. If you’re working hard and don’t feel like you’re getting out what you’re putting in, you probably need to stop banging your head against the wall and jump ship. There is also a time factor here, which is very important to consider. YouTube was acquired by Google for $1.65 billion in 2006, less than two years after its founding.[28] PopCap, a gaming company, was acquired by Electronic Arts for $750 million in 2011, eleven years after its founding.[29] If you founded or worked for either of these companies and loved every moment of it, the difference in time-to-acquisition is a non-factor. But, if you did not enjoy yourself and didn’t grow along the way, you better hope you were working at YouTube. Two years of stagnant personal growth is far less painful than eleven. The example above includes two companies that both sold for a bunch of money, which is great. But there’s more to life than money. There’s an opportunity cost to everything you do. If you’re hitting a wall for more than a year and you’re unhappy, I recommend jumping ship—even if there’s a potential pile of cash down the road. There are opportunities beyond whatever you’re currently working on. Forget how much time, effort, and money has already been invested and ignore whatever you might be giving up if you leave. Those are sunk costs and unknown outcomes. Instead, think about what you’re working on and who you’re working with right now. Then decide if that’s really how you want to be spending your days. That’s all that really matters.

To do truly meaningful work, you need to get serious, focus, and go all in. Floyd Mayweather Junior is the best pound-for-pound boxer in the world. As of this writing, he is also the highest paid athlete in the world. His motto? Hard Work, Dedication. His team chants the motto as he trains. One group yells, “Hard work!” and the other responds, “Dedication!” The chants get louder and faster as Mayweather increases the speed and intensity of his workout. Mayweather knows the value of these words, and the impact they have on success. He lives by them. He endures grueling training sessions, 2-3 times per day. He often trains late into the night. He doesn’t smoke or drink alcohol—ever. Floyd Mayweather is no joke. He’s the real deal. And that’s why he’s such a big deal. He lives to box. It’s what he loves to do. His hard work and dedication have paid off, literally. Some people question Mayweather’s morals, or ridicule him for his arrogance, but it’s hard to argue with his unparalleled achievements in boxing and the relentless dedication that backs it all up. The best in the world are the best because they work their asses off doing what they were born to do. They make sacrifices. They keep grinding—and they don’t stop.[36]

Failure can feel like the ultimate death sentence, but it’s actually a step forward. When we fail, life is pushing us in a different direction so we can experience something new. One adventure has ended and another is about to begin, because it must. Think of your activities in life as scientific experiments. Scientists expect the vast majority of their tests to fail, but they still view each test as a step forward, regardless of the outcome. This is because each failed test rules out that particular approach, narrowing the remaining scope of potential solutions. You might be thinking, “What if all of my experiments fail until the day I die?” Great question. That might happen, depending on how you define failure and success. Here’s the magical solution to that problem: The results of your experiments are of little consequence. Only the experiments themselves matter. The old platitude is true: It’s about the journey, not the destination. Doing experiments will account for 99% of your time on this earth. That’s the journey. The result of your experiments is the other 1%. If you enjoy 99% of your life (the time spent in experimentation), who cares about the results? This is how to remove the problem of failure. Failure is just a temporary result. Its effect is as big or as small as you allow it to be. Elon Musk is becoming a household name. He cofounded Paypal. He now runs two companies simultaneously. The first, Tesla Motors, builds electric cars. The second, SpaceX, builds rocket ships. Many people think of Elon Musk as a real-world Iron Man—a superhero. He’s a living legend. He works extremely hard, and he’s brilliant. Did you know that Elon Musk never worked at Netscape? This is interesting because he actually wanted to work there very badly. He applied to Netscape while he was in grad school at Stanford, but never received a response. He even went to Netscape’s lobby with resume in hand, hoping to talk to someone about getting a job. No one in the lobby ever spoke to Elon that day. After getting nervous and feeling ashamed of himself, he walked out. That’s right. Elon Musk failed to get hired at Netscape. The recruiting managers didn’t see a need for him, and he was too ashamed to keep badgering them. So what happened next? Well, we know what happened from there. Musk went on to become one of the most successful and respected visionaries of our time.[30] Take a deep breath and realize that there are no life-ending failures, only experiments and results. It’s also important to realize that you are not the failure—the experiment is the failure. It is impossible for a person to be a failure. A person’s life is just a collection of experiments. We’re meant to enjoy them and grow from them. If you learn to love the process of experimentation, the prospect of failure isn’t so scary anymore.

The minute I dropped out I could stop taking the required classes that didn’t interest me, and begin dropping in on the ones that looked interesting. It wasn’t all romantic. I didn’t have a dorm room, so I slept on the floor in friends’ rooms, I returned coke bottles for the 5¢ deposits to buy food with, and I would walk the seven miles across town every Sunday night to get one good meal a week at the Hare Krishna temple. I loved it. And much of what I stumbled into by following my curiosity and intuition turned out to be priceless later on. Let me give you one example: Reed College at that time offered perhaps the best calligraphy instruction in the country. Throughout the campus every poster, every label on every drawer, was beautifully hand calligraphed. Because I had dropped out and didn’t have to take the normal classes, I decided to take a calligraphy class to learn how to do this. I learned about serif and san serif typefaces, about varying the amount of space between different letter combinations, about what makes great typography great. It was beautiful, historical, artistically subtle in a way that science can’t capture, and I found it fascinating. None of this had even a hope of any practical application in my life. But ten years later, when we were designing the first Macintosh computer, it all came back to me. And we designed it all into the Mac. It was the first computer with beautiful typography. If I had never dropped in on that single course in college, the Mac would have never had multiple typefaces or proportionally spaced fonts. And since Windows just copied the Mac, it’s likely that no personal computer would have them. If I had never dropped out, I would have never dropped in on this calligraphy class, and personal computers might not have the wonderful typography that they do. Of course it was impossible to connect the dots looking forward when I was in college. But it was very, very clear looking backwards ten years later. Again, you can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future. You have to trust in something—your gut, destiny, life, karma, whatever. This approach has never let me down, and it has made all the difference in my life. The narrator of this story is Steve Jobs, the legendary CEO of Apple. The story was part of his famous Stanford commencement speech in 2005.[23] It’s a perfect illustration of how passion and purpose drive success, not the crossing of an imaginary finish line in the future. Forget the finish line. It doesn’t exist. Instead, look for passion and purpose directly in front of you. The dots will connect later, I promise—and so does Steve.

His “Harmonian Court of Love,” in which individuals are algorithmically paired for romantic and sexual liaisons, sounded preposterous in the middle nineteenth century. Today it is the banal reality of online dating (eHarmony). Since

Motivated by my research and examples such as Feynman, I decided that focusing my attention on a bottom-up understanding of my own field’s most difficult results would be a good first step toward revitalizing my career capital stores. To initiate these efforts, I chose a paper that was well cited in my research niche, but that was also considered obtuse and hard to follow. The paper focused on only a single result—the analysis of an algorithm that offers the best-known solution to a well-known problem. Many people have cited this result, but few have understood the details that support it. I decided that mastering this notorious paper would prove a perfect introduction to my new regime of self-enforced deliberate practice. Here

In the big data world, the new fear is that humans will become more like machines. I think back to the Obama campaign official who said, “We basically found our guts were worthless.” We may live more efficient lives as instincts are replaced by algorithms, but it is reasonable to fear that some of our most human qualities—love, spontaneity, autonomy—may be changed for the worse by our living more algorithmic lives.

Braid groups have many important practical applications. For example, they are used to construct efficient and robust public key encryption algorithms.7 Another promising direction is designing quantum computers based on creating complex braids of quantum particles known as anyons. Their trajectories weave around each other, and their overlaps are used to build “logic gates” of the quantum computer.8 There are also applications in biology. Given a braid with n threads, we can number the nails on the two plates from 1 to n from left to right. Then, connect the ends of the threads attached to the nails with the same number on the two plates. This will create what mathematicians call a “link”: a union of loops weaving around each other. In the example shown on this picture, there is only one loop. Mathematicians’ name for it is “knot.” In general, there will be several closed threads. The mathematical theory of links and knots is used in biology: for example, to study bindings of DNA and enzymes.9 We view a DNA molecule as one thread, and the enzyme molecule as another thread. It turns out that when they bind together, highly non-trivial knotting between them may occur, which may alter the DNA. The way they entangle is therefore of great importance. It turns out that the mathematical study of the resulting links sheds new light on the mechanisms of recombination of DNA. In mathematics, braids are also important because of their geometric interpretation. To explain it, consider all possible collections of n points on the plane. We will assume that the points are distinct; that is, for any two points, their positions on the plane must be different. Let’s choose one such collection; namely, n points arranged on a straight line, with the same distance between neighboring points. Think of each point as a little bug. As we turn on the music, these bugs come alive and start moving on the plane. If we view the time as the vertical direction, then the trajectory of each bug will look like a thread. If the positions of the bugs on the plane are distinct at all times – that is, if we assume that the bugs don’t collide – then these threads will never intersect. While the music is playing, they can move around each other, just like the threads of a braid. However, we demand that when we stop the music after a fixed period of time, the bugs must align on a straight line in the same way as at the beginning, but each bug is allowed to end up in a position initially occupied by another bug. Then their collective path will look like a braid with n threads. Thus, braids with n threads may be viewed as paths in the space of collections of n distinct points on the plane.10

Discover Alex Getelman, the dynamic founder shaping Algorithms Development Corp's trajectory. With an innate flair for innovation and an unyielding dedication to technology, Alex has emerged as a trailblazer in the field. Off the clock, his allegiance to the New York Yankees and NY Knicks shines bright, reflecting his deep-seated love for his hometown teams.

Life Formulas I (2008) These are notes to myself. Your frame of reference, and therefore your calculations, may vary. These are not definitions—these are algorithms for success. Contributions are welcome. Happiness = Health + Wealth + Good Relationships Health = Exercise + Diet + Sleep Exercise = High Intensity Resistance Training + Sports + Rest Diet = Natural Foods + Intermittent Fasting + Plants Sleep = No alarms + 8–9 hours + Circadian rhythms Wealth = Income + Wealth * (Return on Investment) Income = Accountability + Leverage + Specific Knowledge Accountability = Personal Branding + Personal Platform + Taking Risk? Leverage = Capital + People + Intellectual Property Specific Knowledge = Knowing how to do something society cannot yet easily train other people to do Return on Investment = “Buy-and-Hold” + Valuation + Margin of Safety [72] Naval’s Rules (2016) Be present above all else. Desire is suffering. (Buddha) Anger is a hot coal you hold in your hand while waiting to throw it at someone else. (Buddha) If you can’t see yourself working with someone for life, don’t work with them for a day. Reading (learning) is the ultimate meta-skill and can be traded for anything else. All the real benefits in life come from compound interest. Earn with your mind, not your time. 99 percent of all effort is wasted. Total honesty at all times. It’s almost always possible to be honest and positive. Praise specifically, criticize generally. (Warren Buffett) Truth is that which has predictive power. Watch every thought. (Ask “Why am I having this thought?”) All greatness comes from suffering. Love is given, not received. Enlightenment is the space between your thoughts. (Eckhart Tolle) Mathematics is the language of nature.

We have already driven the earth's climate out of balance and have summoned billions of enchanted brooms, drones, chatbots, and other algorithmic spirits that may escape our control and unleash a flood of unintended consequences. What should we do, then? The fables offer no answers, other than to wait for some god or sorcerer to save us. This, of course, is an extremely dangerous message. It encourages people to abdicate respon-sibilitv and put their faith in gods and sorcerers instead. Even worse, it fails to appreciate that gods and sorcerers are themselves a human in-vention-just like chariots, brooms, and algorithms. The tendency to create powerful things with unintended consequences started not with the invention of the steam engine or Al but with the invention of religion. Prophets and theologians have summoned powerful spirits that were supposed to bring love and joy but occasionally ended up flooding the world with blood.

Hate and love were each powerful motivators on their own, but together they provided an endless source of energy.

How bewildering to not know someone’s name, to not know anything about them, but be absolutely sure you loved them.

As we transition from the industrial age to the AI age, we will need to move away from a mindset that equates work with life or treats humans as variables in a grand productivity optimization algorithm. Instead, we must move toward a new culture that values human love, service, and compassion more than ever before.

So, again, what is media? I said earlier that media includes our clothes, other people, tools (especially tools for communication), and infrastructure. These are all means through which Christians communicate—first with God, then with the other saints, and then with unbelievers. Respectively, we pray through Christ, we have fellowship in Christ, and we proclaim Christ. What do we use as we do all these things? We use, among other things, ink, newsprint, microphones, email, toner, power point, algorithms, video clips, all of which are made out of molecules. They are things. This means that, because of the way we are created, we cannot love others without media because love, like sound, doesn’t travel in a vacuum.

Love is like organized crime. It changes the structure of the marriage game so that the equilibrium becomes the outcome that works best for everybody.

I anticipate diagnostic AI will exceed all but the best doctors in the next twenty years. This trend will be felt first in fields like radiology, where computer-vision algorithms are already more accurate than good radiologists for certain types of MRI and CT scans. In the story “Contactless Love,” we see that by 2041 radiologists’ jobs will be mostly taken over by AI. Alongside radiology, we will also see AI excel in pathology and diagnostic ophthalmology. Diagnostic AI for general practitioners will emerge later, one disease at a time, gradually covering all diagnoses. Because human lives are at stake, AI will first serve as a tool within doctors’ disposal or will be deployed only in situations where a human doctor is unavailable. But over time, when trained on more data, AI will become so good that most doctors will be routinely rubber-stamping AI diagnoses, while the human doctors themselves are transformed into something akin to compassionate caregivers and medical communicators.

the development of sophisticated algorithms has its pros and cons. On the plus side, it becomes easier to discover content you actually want to watch. On the negative side, it makes it easier to become stuck in a never-ending loop, watching one video after the other. In a sense, instead of using the internet to find information or communicate with loved ones, the internet has become the one using you. It does so by hijacking your focus and making you unproductive and, as a result, restless.

Step by Step… Can you write out your ideal business step by step Here is a business I am setting up for a client. She wants to shipping start her own shipping company… One she will need a US partner to collect and transfer packages to her in Jamaica. She will also need one in China. I have two contacts. One has a warehouse in Florida The other has two in China. Chinese connect makes goods available within 3 weeks, she has to tell her customers four. The US connect makes it within 3-5 days. She has to tell them within a week… Next she will need a website where her customers can login and track their packages. This will come with individual dashboards. She will need an interface and warehouse management software and logistics APIs. She will also need an automated email set up (journey) to send emails to her customers without her or her agents needing to do that. Without this Saas she would have to hire someone to reply to messages and emails about , someone to call and track, use usps and FedEx tracking numbers to track and reply back to customers. She also needs a beta ApI to allow her warehouse guy to update the CRM with information about her customers packages… Key nodes such as - Intransit to destinations Held at customs Clearance In transit to store Pick up available etc… These will come in as email notifications Fully automated. Everything will be connected using Webhooks… entire system. Saas she might need to use a combination of GOhighlevel, Workiz and To run this as a System as as Service. Each platform can work together using webhooks. Gohighlevel as a Saas is $500 a month Workiz is $200 dollars She can use Odoo which is open source alternative as a CRM And Clickup as Management. This is how a conversational business plan looks. You can see it. You can research it. You can confirm that it’s plausible. It doesn’t sound like pipedreams. It sounds workable to credit companies /banks and investors. It sounds doable to a BDO Client. I also sound as if I know what I am doing. Not a lot of technical language. A confused prospective business investor or banker don’t want to use a dictionary to figure out everything… They want to see the vision as clear as day. You basically need to do to them what I did to you when you joined my programme. It must sound plausible. All businesses is a game of wit. Every deal that is signed benefits both party. Whether initially or in the long term. Those are the sub-tenets of business. Every board meeting or meeting with regulatory boards, banks, credit facilities, municipalities is a game of convincing people to see your thing through… Everyone does Algorithm is simple. People want you to solve their problems with speed and efficiency. Speed is very important and automation. Progress, business and production are tied to ego… that’s why people love seh oh dem start a business or dem have dem online business and nah sell one rass thing. Cause a lot of people think being successful and looking successful are one and the same thing until they meet someone like me or people who done the work… Don’t rush it… you are young and you have time. There are infact certain little nuances Weh yuh only ago learn through experience. Experience and reflection. One of the drawbacks of wanting to run your business by yourself with you and your family members is that you guys will have to be reliant on yourself for feedback which is not alw

During my time as a researcher, I had stood on the absolute frontier of human knowledge about artificial intelligence, but I had never been further from a genuine understanding of other human beings or myself. That kind of understanding couldn’t be coaxed out of a cleverly constructed algorithm. Rather, it required an unflinching look into the mirror of death and an embrace of that which separated me from the machines that I built: the possibility of love.

Building societies that thrive in the age of AI will require substantial changes to our economy but also a shift in culture and values. Centuries of living within the industrial economy have conditioned many of us to believe that our primary role in society (and even our identity) is found in productive, wage-earning work. Take that away and you have broken one of the strongest bonds between a person and his or her community. As we transition from the industrial age to the AI age, we will need to move away from a mindset that equates work with life or treats humans as variables in a grand productivity optimization algorithm. Instead, we must move toward a new culture that values human love, service, and compassion more than ever before.

Mike Kelleher from Obama’s Senate office was the person who stepped up to tackle the mess… He built the staff, drew up a ten-page strategic plan for the mail-room, wrote algorithms for a mail coding system, set up a casework decision tree, assembled a library of policy-response letters, and developed quality-control manuals.

A few months later, Sandler got word that Netflix, newly interested in movies, had set its sights squarely on him. Using data gathered from Sony movies that Netflix had played through its Starz deal, Sarandos’s team knew that even as his box-office power waned, Sandler remained one of the most popular stars on the streaming service. His aging audience might be less likely to pay to see him in a theater, but they still loved laughing at his antics at home. “We knew he was popular in markets where his movies had never even opened,” Sarandos said. The mid-budget star vehicle, in other words, still worked great for Netflix. When people went to theaters, they preferred brand-name franchises. But when they were browsing for something to stream rather than pay fifty dollars for a night out, a familiar face doing the familiar shtick was perfect. Movies without massive visual effects were just as enjoyable at home, after all, if not more so. And if the stars had chosen to stretch their wings and you didn’t like the movie you clicked on, you could turn it off immediately. You lost a little bit of time, but not any money. And though there may not be as many fans of Adam Sandler, or any movie star, as there used to be, that didn’t necessarily matter to Netflix. All studios care about is how many people buy tickets or DVDs. They get their money whether you loved the movie or hated it. But Netflix measures success by how many people finish a movie and are satisfied enough to keep subscribing as a result, or who sign up just in order to watch it. Adam Sandler’s fan base may have shrunk, but those who remained were loyal and they were global—just what Netflix wanted. Additionally, Netflix wouldn’t have to spend millions of dollars on billboards and TV ads to market each film. Its algorithm would prominently suggest each Sandler movie to his fans on their home screen the moment it was available.

I’m not sure love makes sense even to those who are involved. If we could simply explain it like an algorithm or a theory, we might lose interest.

OkCupid, a free dating website founded by a group of mathematicians, with a particularly elegant algorithm at its heart.

Gold digging is more likely to succeed than a quest for love. If you’re evaluating your partners based on any kind of objective criterion—say, their income percentile—then you’ve got a lot more information at your disposal than if you’re after a nebulous emotional response (“love”) that might require both experience and comparison to calibrate.

The dire situation had been aggravated by elected officials who, a quarter century into the Internet age, had managed to pass exactly zero legislation to protect anyone. Democratic institutions that we hold dear had crumbled in the face of what all this digital engagement has wrought: no privacy protections, no updated antitrust laws, no algorithmic transparency requirement, no focus on addiction and mental impact. It is breathtaking to think that there are no significant guidelines governing these areas. However flawed, there are laws for everything but tech companies.

Imagine if every time we had a fight with a loved one, they reacted to a set of variables or deferred to the rulebook for advice. How long do you think that relationship would last? This is the reason we find bureaucrats infuriating. They simply default to the rules with no consideration for the people those rules were designed to help or protect. In other words, they don’t care. There is no algorithm for a successful relationship—between people or with companies.