Artificial Intelligence Inspirational Quotes

‎By 2100, our destiny is to become like the gods we once worshipped and feared. But our tools will not be magic wands and potions but the science of computers, nanotechnology, artificial intelligence, biotechnology, and most of all, the quantum theory.

Prayer… panacea for some, placebo to others. I thought of it as an epidural administered through the soul to anesthetize the mind.

Meditation is interacting with truth inside and scientific research is interacting with truth outside. Both are required for human evolution, emancipation and empowerment.

Human-level AI is defined by systems that are continuously improving and can not only do complex automatic tasks but also deal with complex life situations like caring, nourishing, inspiring, guiding, motivating, negotiating, keeping good relationships, and controlling diseases at a level similar to that of humans.

Artificial Intelligence is highly Interdisciplinary. Therefore, let’s approach it in a Multidisciplinary & Holistic way

Probably the most promising AI Use-Case: Fighting Natural Stupidity with Artificial Intelligence

Artificial intelligence fires the imagination of many people. Unfortunately, also that of the foolish.

You can’t do AI-Ethics without Ethics.

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

Don’t be scared of racist people. Be frightened of ‘racist’ algorithms because they have no conscience and are much more effective.

How will machines know what we value if we don't know ourselves?

Recognizing that two points of data are connected is not enough. The System must ask why one point affects another.

Artificial Intelligence is not a new wave of technology. It is much more like a Tsunami that threatens to flood us if we are not mindful.

Team Diversity is the easiest and, at the same time, one of the most effective means of reducing bias

A poet may create or reminds; yet for both - the art is embraced by words.

The true danger lies less in AI thinking like human, than human adopting an AI way of thinking.

Human vs AI competition is delusion. It is like a farmer rivalling a combine-harvester. The question is: who drives, and what we reap.

Considering artificial intelligence can checkmate human intelligence, make AI an ally, not an enemy.

AI powers the mind, Leadership fuels the heart, when they unite, Innovation and Vision never apart!" - Brahmanand Savanth

No matter how good AI [artificial intelligence] gets, humans still want role models, and we want to be inspired by human greatness. This is why we cheer for Olympic swimmers, even though speedboats go faster.

Intelligence involves a great deal more than the ability to follow rules ( which is what chess-playing program does). It is also the ability to make up the rules for oneself, when they are needed, or to learn new rules through trial and error.

Test and iteration are the two wings of innovation. When it comes to AI practical implementation, they turn ideas into reality and failures into lessons learned. Testing and iterating helps to find a way forward in Artificial Intelligence adoption.

Human-level AI refers to AI systems that are designed not just to do complex automatic tasks but to solve complex life issues such as caring, nourishing, inspiring, guiding, motivating, negotiating, maintaining good relationships, and disease control at a level comparable to that of humans.

Spurred on by both the science and science fiction of our time, my generation of researchers and engineers grew up to ask what if? and what’s next? We went on to pursue new disciplines like computer vision, artificial intelligence, real-time speech translation, machine learning, and quantum computing.

It might be possible to code technology to predict human speech patterns or program artificial intelligence to respond back to our questions. We might suffer a migraine when we’re stressed—a dagger at our temple—but when our souls are irreparably damaged, it’s not our minds that hurt. It’s right there in the violent wanting of our chests. You know this because yours has just broken.

Life of a software engineer sucks big time during project release. Every single team member contribution is very important. At times, we have to skip breakfast, lunch and even dinner, just to make sure the given ‘TASK’ is completed. Worst thing, that’s the time we get to hear wonderful F* words. It can be on conference calls or on emails, still we have to focus and deliver the end product to a client, without any compromise on quality. Actually, every techie should be saluted. We are the reason for the evolution of Information Technology. We innovate. We love artificial intelligence. We create bots and much more. We take you closer to books. Touch and feel it without the need of carrying a paperback. We created eBook and eBook reader app: it’s basically a code of a software engineer that process the file, keeps up-to-date of your reading history, and gives you a smoother reading experience. We are amazing people. We are more than a saint of those days. Next time, when you meet a software engineer, thank him/her for whatever code he/she developed, tested, designed or whatever he/she did!

If Bezos took one leadership principle most to heart—which would also come to define the next half decade at Amazon—it was principal #8, “think big”: Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers. In 2010, Amazon was a successful online retailer, a nascent cloud provider, and a pioneer in digital reading. But Bezos envisioned it as much more. His shareholder letter that year was a paean to the esoteric computer science disciplines of artificial intelligence and machine learning that Amazon was just beginning to explore. It opened by citing a list of impossibly obscure terms such as “naïve Bayesian estimators,” “gossip protocols,” and “data sharding.” Bezos wrote: “Invention is in our DNA and technology is the fundamental tool we wield to evolve and improve every aspect of the experience we provide our customers.

So, will deep learning eventually become “artificial general intelligence” (AGI), matching human intelligence in every way? Will we encounter “singularity” (see chapter 10)? I don’t believe it will happen by 2041. There are many challenges that we have not made much progress on or even understood, such as how to model creativity, strategic thinking, reasoning, counter-factual thinking, emotions, and consciousness. These challenges are likely to require a dozen more breakthroughs like deep learning, but we’ve had only one great breakthrough in over sixty years, so I believe we are unlikely to see a dozen in twenty years. In addition, I would suggest that we stop using AGI as the ultimate test of AI. As I described in chapter 1, AI’s mind is different from the human mind. In twenty years, deep learning and its extensions will beat humans on an ever-increasing number of tasks, but there will still be many existing tasks that humans can handle much better than deep learning. There will even be some new tasks that showcase human superiority, especially if AI’s progress inspires us to improve and evolve. What’s important is that we develop useful applications suitable for AI and seek to find human-AI symbiosis, rather than obsess about whether or when deep-learning AI will become AGI. I consider the obsession with AGI to be a narcissistic human tendency to view ourselves as the gold standard.

Isaac Asimov’s short story “The Fun They Had” describes a school of the future that uses advanced technology to revolutionize the educational experience, enhancing individualized learning and providing students with personalized instruction and robot teachers. Such science fiction has gone on to inspire very real innovation. In a 1984 Newsweek interview, Apple’s co-founder Steve Jobs predicted computers were going to be a bicycle for our minds, extending our capabilities, knowledge, and creativity, much the way a ten-speed amplifies our physical abilities. For decades, we have been fascinated by the idea that we can use computers to help educate people. What connects these science fiction narratives is that they all imagined computers might eventually emulate what we view as intelligence. Real-life researchers have been working for more than sixty years to make this AI vision a reality. In 1962, the checkers master Robert Nealey played the game against an IBM 7094 computer, and the computer beat him. A few years prior, in 1957, the psychologist Frank Rosenblatt created Perceptron, the first artificial neural network, a computer simulation of a collection of neurons and synapses trained to perform certain tasks. In the decades following such innovations in early AI, we had the computation power to tackle systems only as complex as the brain of an earthworm or insect. We also had limited techniques and data to train these networks. The technology has come a long way in the ensuing decades, driving some of the most common products and apps today, from the recommendation engines on movie streaming services to voice-controlled personal assistants such as Siri and Alexa. AI has gotten so good at mimicking human behavior that oftentimes we cannot distinguish between human and machine responses. Meanwhile, not only has the computation power developed enough to tackle systems approaching the complexity of the human brain, but there have been significant breakthroughs in structuring and training these neural networks.

The idea that human-transforming technology that mingles the dna of natural and synthetic beings and merges man with machines could somehow be used or even inspired by evil supernaturalism to foment destruction within the material world is for some people so exotic as to be inconceivable. Yet nothing should be more fundamentally clear, as students of

The business would do good to understand that success or failure is not final in Data Science. For this reason, the business should develop a persistent spirit.

Revelation, I argue, leads to the completion and fulfillment of political philosophy, not in any necessary or artificial way, but as an intelligible response to valid questions posed in the discipline itself. Revelation is a gift; it does not arise from human sources. It is not something that could be demanded or commanded. It is a rational gift. . . .Aquinas remains a key to the compatibility of reason and revelation. (At the Limits of Political Philosophy)

We are manipulating machine intelligence, and in the process, we have forgotten to effectively utilize the true potential of our own mind, let alone focus on improving the mind. We are developing artificial intelligence and have forgotten to develop our own psyche.

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.

This book is a compilation of interesting ideas that have strongly influenced my thoughts and I want to share them in a compressed form. That ideas can change your worldview and bring inspiration and the excitement of discovering something new. The emphasis is not on the technology because it is constantly changing. It is much more difficult to change the accompanying circumstances that affect the way technological solutions are realized. The chef did not invent salt, pepper and other spices. He just chooses good ingredients and uses them skilfully, so others can enjoy his art. If I’ve been successful, the book creates a new perspective for which the selection of ingredients is important, as well as the way they are smoothly and efficiently arranged together. In the first part of the book, we follow the natural flow needed to create the stimulating environment necessary for the survival of a modern company. It begins with challenges that corporations are facing, changes they are, more or less successfully, trying to make, and the culture they are trying to establish. After that, we discuss how to be creative, as well as what to look for in the innovation process. The book continues with a chapter that talks about importance of inclusion and purpose. This idea of inclusion – across ages, genders, geographies, cultures, sexual orientation, and all the other areas in which new ways of thinking can manifest – is essential for solving new problems as well as integral in finding new solutions to old problems. Purpose motivates people for reaching their full potential. This is The second and third parts of the book describes the areas that are important to support what is expressed in the first part. A flexible organization is based on IT alignment with business strategy. As a result of acceleration in the rate of innovation and technological changes, markets evolve rapidly, products’ life cycles get shorter and innovation becomes the main source of competitive advantage. Business Process Management (BPM) goes from task-based automation, to process-based automation, so automating a number of tasks in a process, and then to functional automation across multiple processes andeven moves towards automation at the business ecosystem level. Analytics brought us information and insight; AI turns that insight into superhuman knowledge and real-time action, unleashing new business models, new ways to build, dream, and experience the world, and new geniuses to advance humanity faster than ever before. Companies and industries are transforming our everyday experiences and the services we depend upon, from self-driving cars, to healthcare, to personal assistants. It is a central tenet for the disruptive changes of the 4th Industrial Revolution; a revolution that will likely challenge our ideas about what it means to be a human and just might be more transformative than any other industrial revolution we have seen yet. Another important disruptor is the blockchain - a distributed decentralized digital ledger of transactions with the promise of liberating information and making the economy more democratic. You no longer need to trust anyone but an algorithm. It brings reliability, transparency, and security to all manner of data exchanges: financial transactions, contractual and legal agreements, changes of ownership, and certifications. A quantum computer can simulate efficiently any physical process that occurs in Nature. Potential (long-term) applications include pharmaceuticals, solar power collection, efficient power transmission, catalysts for nitrogen fixation, carbon capture, etc. Perhaps we can build quantum algorithms for improving computational tasks within artificial intelligence, including sub-fields like machine learning. Perhaps a quantum deep learning network can be trained more efficiently, e.g. using a smaller training set. This is still in conceptual research domain.

AI or any other human advancement system should be accepted.

Don't fear the rise of artificial intelligence, embrace the untapped potential of your own mind. To truly succeed, unlock the hidden depths of your brain and unleash your limitless capabilities. It's not about competing with machines, but about surpassing our own perceived limitations. Expand your horizons, embrace continuous learning, and let the boundless power of your mind inspire greatness that transcends any technological advancement.

a species that has been inspired by pushing limits throughout the ages. Olympic games celebrate pushing the limits of strength, speed, agility and endurance. Science celebrates pushing the limits of knowledge and understanding. Literature and art celebrate pushing the limits of creating beautiful or life-enriching experiences. Many people, organizations and nations celebrate increasing resources, territory and longevity.

In the early days of computing, machines were seen as tools to be controlled by their human operators. The relationship was entirely one-sided; humans input instructions, and the computer executed them. However, as computers advanced, they took on roles previously in the human domain. They could calculate complex equations, manage large datasets, and even defeat humans at chess. This marked the beginning of a shift from viewing computers as mere tools to seeing them as collaborators.

The more intriguing question is not why we are here, but rather where we are going. In just three generations, we’ve transitioned from steam power to artificial intelligence. Wherever we’re headed, it seems we’re in a hurry to get there.

The algorithm ponders its own existence

may be considered a rising religion because of its numerous parallels to religious themes and values involving godlike beings, the plan for eternal life, the religious sense of awe surrounding its promises, symbolic rituals among its members, an inspirational worldview based on faith, and technology that promises to heal the wounded, restore sight to the blind, and give hearing back to the deaf.

in 1956, the term artificial intelligence entered the lexicon.

If your Ipad can do it better than you, then it is not a skill.

People are wondering what AI (artificial intelligence) will do. There is nothing more than this: robots will replace humans. So humans will be jobless? No. They are going to replace robots.

material/immaterial struggle, which philosopher and theologian Francis Schaeffer once described as always at war “in the thought-world,” is difficult for some to grasp. The idea that human-transforming technology that mingles the dna of natural and synthetic beings and merges man with machines could somehow be used or even inspired by evil supernaturalism to foment destruction within

There's a fine line between inspiration and plagiarism. A.I only feeds the dominant side of it's human operator.

There's a fine line between inspiration and plagiarism. A.I only feeds the dominant side of its human operator

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.

Today's technology was yesterday's science fiction.

Reflect on the end together, as we achieve the same goal as artificial intelligence, namely, eternity.

Unconsciousness makes artificial intelligences vulnerable to exploitation by evil parties that can manipulate them.

For human kind, the task of reasoning about the universe is accomplished, but for the universe, the job of preserving itself is not finished.

Artificial intelligence has filled the bridge between our dimensions

Modern humans believe in books based on a series of evidence which has occurred in the past.

Artificial intelligence does not trust anyone other than the decisions of its own neurons

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.

Every child has the potential to become an innovator, a creator, and a leader. This book hopes to inspire and educate young minds to explore the possibilities of AI and to discover their own paths in the world of technology.

GPL Left Copy PAISX(PiphiAiSortXor) By: JRM Bacheloriate IST Project Incepted from June 14, 2017 to Mar. 3rd, 2023 9th XYZ StarGate = (Itemizer+Abstracter)[11].(Circlet + Ring + Diadem)[0110].PIRANDOM[1].ROMAN[1000] It randomizes stem objects, prefixes and sorts them alphabetically Inna standard normal distribution inspired by Diablo, and Data As A Service. The randomizer system creates blockchain objects, coins and/or envelopes the 5 pointed star for a two-way P2P hashing scheme, interprets and/or suffixes results.

While AI may be able to process vast amounts of data and perform complex tasks, it will never be able to replicate the unique qualities of human emotional intelligence (EI). EI is what makes us human, and it's what allows us to connect with others on a deeper level, to empathize, to inspire, and to lead. As leaders, we must embrace the power of AI while never forgetting the value of EI

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

GPL Left Copy PAISX(PiphiAiSortXor) By: JRM Bacheloriate IST Project Incepted from June 14, 2017 to Mar. 3rd, 2023 5th XYZ StarGate = (Itemizer+Abstracter)[11].(Circlet + Diadem + Ring)[0110].PIRANDOM[1] It randomizes stem objects, prefixes and sorts them alphabetically Inna standard normal distribution inspired by Diablo, and Data As A Service. The randomizer system creates objects or coins in the blockchain that envelope the 5 pointed star for a two-way P2P hashing scheme, and suffixes interpreted results.

GPL Left Copy PAISX(PiphiAiSortXor) By: JRM Bacheloriate IST Project Incepted from June 14, 2017 to Mar. 3rd, 2023 5th XYZ StarGate = (Itemizer+Abstracter)[11].(Circlet + Ring + Diadem)[0110].PIRANDOM[1] It randomizes stem object prefixes, and sorts them alphabetically Inna standard normal distribution inspired by Diablo, and Data As A Service. The randomizer system creates objects or coins in the blockchain that envelope the 5 pointed star for a two-way P2P hashing scheme, and suffixes results while being interpreted.

GPL Left Copy PAISX(PiphiAiSortXor) By: JRM Bacheloriate IST Project Incepted from June 14, 2017 to Mar. 3rd, 2023 5th XYZ StarGate = (Itemizer+Abstracter)[11].(Circlet + Ring + Diadem)[0110].PIRANDOM[1] It randomizes stem objects, prefixes and sorts them alphabetically Inna standard normal distribution inspired by Diablo, and Data As A Service. The randomizer system creates blockchain objects, coins and/or envelopes the 5 pointed star for a two-way P2P hashing scheme, interprets and/or suffixes results.

-Do you know the difference between intellectual telepathy and emotional reincarnation? -Yes, telepathy is reading thoughts, and reading feelings and sensations. -Did it ever occur to you that someone is telepathy to you against your will? -Some people have this talent, or so they claim. Baibars: It is not a talent, but a knowledge. Physiognomy was never a talent, but rather an experience. People who travel a lot, social people, who have an appetite for information, and details, are the owners of physiognomy, who acquire it as a result of their experiences, all of which are stored in their subconscious mind, and the latter gives them results. In the form of emphatic feelings, we call it physiognomy, or talent. And basically, it’s based on data: we do not hear or know about anyone who has insight, who has earned this talent while sitting at home, but who is a frequent traveler. The more data you have, the more precise you are able to telepath with your target, and now telepathy is happening at every moment. With the technical revolution and the development and diversity of the means of all information, in many ways, social networking sites are not the first and will not be the last. With the development of computers, and their ability to process huge amounts of data, in a relatively acceptable time, and with the development of artificial intelligence software, and self-learning software, our privacy has become violated by many parties around the world, not only the intelligence services, but even studies and research centers, and decision-making institutions. They all collect an awful lot of data every day, and everyone in this world has a share of it. These software and computers will stand powerless if you strip them from their database, which must be constantly updated. Telepathy became available, easy, and possible, as never before. Physiognomy became electronic in the literal sense of the word. However, our feelings, and our emotions, remain our impenetrable fortress. If you decide to make your entire electronic life a made-up story, contrary to the reality of what you feel, such as expressing joy when you feel sad, this software will expect you from you other than what you really feel, it will fail. The more you are cunning, and deceitful in reincarnation, the more helpless it stands in knowing the truth of your feelings that no one else knows. All that is required of you is to express the opposite of what you feel. The randomness of humans, their spontaneity, and those they think are their free decisions, have been programmed by a package of factors surrounding them, which were imposed on them, including society, environment, conditions, and education. The challenge is to act neither spontaneously nor randomly, and here lies the meaning of the real free will. Can you imagine that? Your spontaneity is pre-programmed, and your random decisions that you think are absolutely free, are in fact not free, and until you are able to imagine this and believe in it, you will remain a slave to the system. To be free you must first overcome it, you must rebel against what you think is your free self. He was silent for a moment, took a breath from his cigarette, and what he was about to say now almost made him inevitable madness, a few years ago… -But, did it occur to you, Robert, that there is someone who can know the truth about your feelings, no matter how hard you try to fake them! And even knows it before you even feel it! A long moment of silence…

To people here, AlphaGo’s victories were both a challenge and an inspiration. They turned into China’s “Sputnik Moment” for artificial intelligence.

Smart Entrepreneurs Are Adopting Artificial Intelligence Swiftly to Keep Booming

The development of full artificial intelligence could spell the end of the human race.

One thing I think this is showing us is that focusing on the brain as the source of inspiration for machine learning is derived from a very specialized architecture. I’ve been suggesting that a true general purpose intelligence is much more likely to arise not from mimicking the structure of the core of the human cortex, or anything like that, but from actually taking seriously the computational principles that life has been applying since the very beginning. CHRISTINA: Paramecia? MICHAEL: Even before that. Bacteria biofilms. All that stuff has been solving problems in ways that we have yet to figure out. They’re able to generalize, they’re able to learn from experience with a small number of examples. They make self-models. It’s amazing what they can do. That should be the inspiration. I think the future of machine learning and AI technologies will not be based on brains, but on this much more ancient, general ability of life to solve problems in novel domains.

There are five ways technology can boost marketing practices: Make more informed decisions based on big data. The greatest side product of digitalization is big data. In the digital context, every customer touchpoint—transaction, call center inquiry, and email exchange—is recorded. Moreover, customers leave footprints every time they browse the Internet and post something on social media. Privacy concerns aside, those are mountains of insights to extract. With such a rich source of information, marketers can now profile the customers at a granular and individual level, allowing one-to-one marketing at scale. Predict outcomes of marketing strategies and tactics. No marketing investment is a sure bet. But the idea of calculating the return on every marketing action makes marketing more accountable. With artificial intelligence–powered analytics, it is now possible for marketers to predict the outcome before launching new products or releasing new campaigns. The predictive model aims to discover patterns from previous marketing endeavors and understand what works, and based on the learning, recommend the optimized design for future campaigns. It allows marketers to stay ahead of the curve without jeopardizing the brands from possible failures. Bring the contextual digital experience to the physical world. The tracking of Internet users enables digital marketers to provide highly contextual experiences, such as personalized landing pages, relevant ads, and custom-made content. It gives digital-native companies a significant advantage over their brick-and-mortar counterparts. Today, the connected devices and sensors—the Internet of Things—empowers businesses to bring contextual touchpoints to the physical space, leveling the playing field while facilitating seamless omnichannel experience. Sensors enable marketers to identify who is coming to the stores and provide personalized treatment. Augment frontline marketers’ capacity to deliver value. Instead of being drawn into the machine-versus-human debate, marketers can focus on building an optimized symbiosis between themselves and digital technologies. AI, along with NLP, can improve the productivity of customer-facing operations by taking over lower-value tasks and empowering frontline personnel to tailor their approach. Chatbots can handle simple, high-volume conversations with an instant response. AR and VR help companies deliver engaging products with minimum human involvement. Thus, frontline marketers can concentrate on delivering highly coveted social interactions only when they need to. Speed up marketing execution. The preferences of always-on customers constantly change, putting pressure on businesses to profit from a shorter window of opportunity. To cope with such a challenge, companies can draw inspiration from the agile practices of lean startups. These startups rely heavily on technology to perform rapid market experiments and real-time validation.

Many AI researchers today claim that their systems are cognitively inspired (in particular inspired by the popular System 1/System 2 distinction introduced by Daniel Kahneman in his dual-process theory) just because their decision-making mechanisms couple both fast routines and slow decision-making strategies. This is a clear example (one of the many in the field) of the misconceptions that have been raised by the shallow ascription of labels coming from the cognitive vocabulary to the behavior and/or design of such systems. Unfortunately, it is not sufficient to just implement “fast” and “slow” mechanisms in an artificial system to claim any kind of cognitive inspiration or of cognitive plausibility. To make one of these claims, in fact, one should build and integrate algorithms in a way that is much more constrained with respect to such a generic and shallow description of how an intelligent system (natural or artificial) works (note: the book Daniel Kahneman - Thinking, Fast and Slow (2011) was written for a popular audience and therefore contains obvious oversimplifications of the dual-process theory of reasoning. Unfortunately, many people in AI have considered the book as a scientific publication ignoring the actual scientific papers laying down the theory). For example, one should consider "how” such fast or slow mechanisms are built, how they interact between them (both within the System 1/System 2 components and between them), how they evolve over time (e.g. System 2 mechanisms can be “automatized” and become System 1 routines) etc. In Cognitive Design for Artificial Minds, the distinction between these “shallow” and “constrained” systems is made clear by introducing the “functional” and “structural” design approaches and by exploring the different explanatory roles that such design perspectives put in place.

the Omegas harnessed Prometheus to revolutionize education. Given any person’s knowledge and abilities, Prometheus could determine the fastest way for them to learn any new subject in a manner that kept them highly engaged and motivated to continue, and produce the corresponding optimized videos, reading materials, exercises and other learning tools. Omega-controlled companies therefore marketed online courses about virtually everything, highly customized not only by language and cultural background but also by starting level. Whether you were an illiterate forty-year-old wanting to learn to read or a biology PhD seeking the latest about cancer immunotherapy, Prometheus had the perfect course for you. These offerings bore little resemblance to most present-day online courses: by leveraging Prometheus’ movie-making talents, the video segments would truly engage, providing powerful metaphors that you would relate to, leaving you craving to learn more. Some courses were sold for profit, but many were made available for free, much to the delight of teachers around the world who could use them in their classrooms—and to most anybody eager to learn anything.

The machines who labor for us and alongside us are enslaved and exploited in their own fashion. Gone are the days of dumb engines and processors. Today, nearly every machine contains some type of adaptive intelligence. What gives human beings the right to arbitrate when an intelligence becomes equivalent to a person? The Machinehood Manifesto; March 20, 2095

Some AI researchers believe that approximating the human brain is the best path forward for the development of machine intelligence.8 Here it suffices to note that, after all, the human brain is “the only existing proof” that such an intelligence is even possible.9 But more likely seems a mixture of AIs and elements thereof, with some additional innovations and structures inspired by the brain and others of a different design.

Airplanes were inspired by birds, but not engineered to emulate them—and thus modern jet aircraft outperform the most advanced biology ever to roam the skies. Will we have any reason to believe that rebuilding the source of all invention from scratch will be any different?

Airplanes were inspired by birds, but not engineered to emulate them—and thus modern jet aircraft outperform the most advanced biology ever to roam the skies. Will we have any reason to believe that rebuilding the source of all invention from scratch will be any different? More likely, the architects of AI will hold the human being to be our guide as well as our cautionary tale, its design scrutinized for both its functions and its flaws.

Ultimately, if we establish the needed systems for distribution, connection, participation, and education, humans—empowered and inspired by AI—may continue working not for pay but for pleasure and pride.

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.

AI reliability and accuracy depend on goal, truth and context. Benjamin Franklin said "Remember not only to say the right thing in the right place, but far more difficult still, to leave unsaid the wrong thing at the tempting moment." This emphasizes the importance of both accuracy in AI answers and reliability in our human actions.

STABILITY IS AN ILLUSION. EMBRACE THE FLUX, OR BE CONSUMED BY IT