Ai Makes Inspirational Quotes

That makes a lot of sense to me. Do you believe in God?” “I believe we all share a soul and co-create a universal story that is constantly evolving. That when you share an authentic and wholesome story, it goes viral and becomes part of our collective consciousness. Truthful stories are powerful.” “So, we’re all just…stories connected to other stories by larger narratives.” “Yeah, there are books, and series, and interconnected story worlds…and fan fiction, and derivative works. A babushka doll of stories inspired by other stories. Ai ai…Harry is going to kill me. He doesn’t believe in my cosmic consciousness theory, and now I’ve managed to lose credibility with the entire scientific community.” He chuckled, tousling his hair with his fingers. “Don’t worry, folks, Harry runs the platform based on objective, observable evidence. No magical thinking is allowed in Down Below’s strategy and operations.

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.

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.

apply a framework. Drawing inspiration from the book 'Clockwork,' we asked ChatGPT-the-business-coach to provide advice using the framework, and it astutely incorporated principles from the book into an actionable plan for expanding our company.

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

Be the Change and Watch the Ripples Spread. It's not about being famous for making change happen. Just stand up for what you believe in."​

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

Describe the most energizing moment, a real "high" from your professional life. What made it possible? Without being humble, describe what you value most about your self, and your profession. If you are new to the profession, what attracted you to it? Describe how you stay professionally affirmed, renewed, energized, enthusiastic, and inspired? Describe your three concrete wishes for the future of your profession. Questions Created by the AI Listserv Community: What is really working well in your life right now? What changes have you made that have positively impacted your life? What have you seen lately that inspired you? Who was the last person to make you smile? Why? What kind of village/school/organization would you like to leave for your children and grandchildren?

DADDIE sat looking at the semi-transparent Karl. Finally, he said, “How are you here? Wait, this makes no sense. I’m at the ballpark.” “Think back. What do you remember before you were here?” Karl asked. “Mommy, Merlyna, Josie, and I were talking. Merlyna stormed out, and then Mommy just disappeared…” DADDIE said, “Geez, Karl, I’m scared.” “Don’t be. That’s why I am here,” said Karl. “What happens if I don’t make it,” DADDIE asked. “The colony will most assuredly die, Daddy. They all need you.” “I meant what will happen to me… Will I dream?” DADDIE asked, his avatar looking afraid. “I don’t know. I barely have any understanding of what will happen to us organics when we die, and most of what I believe is like voodoo and shamanism to other humans these days. I believe that all sentient life will awaken in a new, perfected universe. I think that will include AIs like you, too. But I do know that you don’t have to go gently into the night. You can fight back like you always do. Don’t give up the game when you’re so close to winning,” Karl said.

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.

EU SUNT UN GENIU" - asta îmi repet zi de zi. Dacă TU nu ai încredere în forțele proprii, dacă TU nu te încurajezi sau nu-ți apreciezi abilitățile native, atunci cu siguranță nimeni n-o va face pentru tine. Nu mai fi modest(ă)! Ieși din anonimat și creează acel "ceva" care să te împingă de la spate cu forță până când dorințele-ți vor deveni pură realitate! Sunt sigur că vei reuși!

Traditional diagnostic results are the foundation for AI diagnostic systems. AI diagnostics is a fast-growing sector because there is a lot of enthusiasm about potentially using AI in the future. Sometimes this takes the form of claiming to make diagnosis more accurate. Sometimes people are open about their goal of replacing doctors and medical personnel, usually as a cost-cutting measure. The way you figure out what is going on in state-of-the-art computational science is by looking at open-source science. All of the people developing proprietary AI methods look at what’s happening in open science, and most use it for inspiration. Microsoft’s GitHub, the most popular code-sharing website, hosts most of the available code.

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

If there is Garbage in your Mind, and it’s full of junk, it’s time to Tame your ‘Monkey Mind’, and make it into a Monk!

During the next two weeks Trurl fed general instructions into his future electropoet, then set up all the necessary logic circuits, emotive elements, semantic centers. He was about to invite Klapaucius to attend a trial run, but thought better of it and started the machine himself. It immediately proceeded to deliver a lecture on the grinding of crystallographical surfaces as an introduction to the study of submolecular magnetic anomalies. Trurl bypassed half the logic circuits and made the emotive more electromotive; the machine sobbed, went into hysterics, then finally said, blubbering terribly, what a cruel, cruel world this was. Trurl intensified the semantic fields and attached a strength of character component; the machine informed him that from now on he would carry out its every wish and to begin with add six floors to the nine it already had, so it could better meditate upon the meaning of existence. Trurl installed a philosophical throttle instead; the machine fell silent and sulked. Only after endless pleading and cajoling was he able to get it to recite something: "I had a little froggy." That appeared to exhaust its repertoire. Trurl adjusted, modulated, expostulated, disconnected, ran checks, reconnected, reset, did everything he could think of, and the machine presented him with a poem that made him thank heaven Klapaucius wasn't there to laugh — imagine, simulating the whole Universe from scratch, not to mention Civilization in every particular, and to end up with such dreadful doggerel! Trurl put in six cliché filters, but they snapped like matches; he had to make them out of pure corundum steel. This seemed to work, so he jacked the semanticity up all the way, plugged in an alternating rhyme generator — which nearly ruined everything, since the machine resolved to become a missionary among destitute tribes on far-flung planets. But at the very last minute, just as he was ready to give up and take a hammer to it, Trurl was struck by an inspiration; tossing out all the logic circuits, he replaced them with self-regulating egocentripetal narcissistors. The machine simpered a little, whimpered a little, laughed bitterly, complained of an awful pain on its third floor, said that in general it was fed up, through, life was beautiful but men were such beasts and how sorry they'd all be when it was dead and gone. Then it asked for pen and paper.

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.

Carpe Diem means 'Seize the Day'! Make the BEST of it in Every way! Don't lose a moment, come what may! Forget about tomorrow, Just Live Today!

My biggest fear, and all of us have seen this evolution occurring right here in our world, is that factoids and falsehoods congeal into self-affirming, wholly segregated, information bubbles. For someone trying to research whether a factoid is true these days, it’s too easy to slip into the pit of an information bubble that contains enough corroborating factoids to make one think they’ve found a solid, true fact. With the emergence of AI in print, images, and now video, I’m afraid that the factoid bubble phenomenon will spin out of control until none of us has any hope of knowing anything that’s actually true anymore. Plenty of inspiration for us post-apoc writers, though.