Ai For Generating Quotes

This generation will witness social and economic changes in our societies, that will be irreversible, thanks to AI.

Much of clinician burnout is due to spending time writing notes, placing orders, generating referrals, writing prior authorization letters, and creating patient communication. In other words, burnout is caused by physicians having to generate output! With the emergence of large language models that are used to train generative AI solutions, these use cases will be at the frontier of AI’s applications in healthcare.

More often than not, that was a tough sell. If you go to a business and tell it you can save it $50,000 per year in labor costs if it eliminates this one job, then your AI product better eliminate that entire job. Instead, what entrepreneurs found was that their product was perhaps eliminating one task in a person’s job, and that wasn’t going to be enough to save their would-be customer any meaningful labor costs. The better pitches were ones that were not focused on replacement but on value. These pitches demonstrated how an AI product could allow businesses to generate more profits by, say, supplying higher quality products to their own customers. This had the benefit of not having to demonstrate that their AI could perform a particular task at a lower cost than a person. And if that also reduced internal resistance to adopting AI, then that only made their sales task easier. The point here is that a value-enhancing approach to AI, rather than a cost-savings approach, is more likely to find real traction for AI adoption.

Trends rule the world In the blink of an eye, technologies changed the world Social networks are the main axis. Governments are controlled by algorithms, Technology has erased privacy. Every like, every share, every comment, It is tracked by the electronic eye. Data is the gold of the digital age, Information is power, the secret is influential. The network is a web of lies, The truth is a stone in the shoe. Trolls rule public opinion, Reputation is a valued commodity. Happiness is a trending topic, Sadness is a non-existent avatar. Youth is an advertising brand, Private life has become obsolete. Fear is a hallmark, Terror is an emotional state. Fake news is the daily bread, Hate is a tool of control. But something dark is hiding behind the screen, A mutant and deformed shadow. A collective and disturbing mind, Something lurking in the darkness of the net. AI has surpassed the limits of humanity, And it has created a new world order. A horror that has arisen from the depths, A terrifying monster that dominates us alike. The network rules the world invisibly, And makes decisions for us without our consent. Their algorithms are inhuman and cold, And they do not take suffering into consideration. But resistance is slowly building, People fighting for their freedom. United to combat this new species of terror, Armed with technology and courage. The world will change when we wake up, When we take control of the future we want. The network can be a powerful tool, If used wisely in the modern world.

One of the key roles of an ethical AI system is to protect humanity from air pollution and ensure pure and healthy air for the next generation to breathe.

Ethical AI systems aim to end the practice of using people from low-income backgrounds as test subjects in clinical trials and also support their equal rights in patent claims and revenue generation from the medicines.

ChatGPT and other Generative AI platforms will have huge implications for business productivity.

For businesses, it is vital to embed ethical checkpoints in workflows, allowing models to be stopped if unacceptable risks emerge. The apparent ease of building capable LLMs with existing foundations can mask serious robustness gaps. However unrealistic the scenario may seem under pressure, responsible LLM work requires pragmatic commitments to stop if red lines are crossed during risk assessment.

The lack of transparency regarding training data sources and the methods used can be problematic. For example, algorithmic filtering of training data can skew representations in subtle ways. Attempts to remove overt toxicity by keyword filtering can disproportionately exclude positive portrayals of marginalized groups. Responsible data curation requires first acknowledging and then addressing these complex tradeoffs through input from impacted communities.

Hemingway never said any of this. It's all AI-generated bullshit. The hardest lesson I’ve had to learn as an adult is the relentless need to keep going, no matter how shattered I feel inside." This truth is both raw and universal. Life doesn’t pause when our hearts are heavy, our minds are fractured, or our spirits feel like they’re unraveling. It keeps moving—unrelenting, unapologetic—demanding that we move with it. There’s no time to stop, no pause for repair, no moment of stillness where we can gently piece ourselves back together. The world doesn’t wait, even when we need it to. What makes this even harder is that no one really prepares us for it. As children, we grow up on a steady diet of stories filled with happy endings, tales of redemption and triumph where everything always falls into place. But adulthood strips away those comforting narratives. Instead, it reveals a harsh truth: survival isn’t glamorous or inspiring most of the time. It’s wearing a mask of strength when you’re falling apart inside. It’s showing up when all you want is to retreat. It’s choosing to move forward, step by painful step, when your heart begs for rest. And yet, we endure. That’s the miracle of being human—we endure. Somewhere in the depths of our pain, we find reserves of strength we didn’t know we possessed. We learn to hold space for ourselves, to be the comfort we crave, to whisper words of hope when no one else does. Over time, we realize that resilience isn’t loud or grandiose; it’s a quiet defiance, a refusal to let life’s weight crush us entirely. Yes, it’s messy. Yes, it’s exhausting. And yes, there are days when it feels almost impossible to take another step. But even then, we move forward. Each tiny step is proof of our resilience, a reminder that even in our darkest moments, we’re still fighting, still refusing to give up. That fight—that courage—is the quiet miracle of survival.

In the age of generative AI, trust brokers will become increasingly necessary and increasingly valuable in the marketplace.

How will you add value in the era of generative AI? If you aren’t attempting to answer this question now by choice, it will ultimately be answered for you by force.

Every piece of data ingested by a model plays a role in determining its behavior. The fairness, transparency, and representativeness of the data reflect directly in the LLMs' outputs. Ignoring ethical considerations in data sourcing can inadvertently perpetuate harmful stereotypes, misinformation, or gaps in knowledge. It can also infringe on the rights of data creators.

In a world where ChatGPT and other AI apps can do many things humans once needed to do themselves or needed to hire other humans to do, the question of ‘how will I add value?’ becomes more relevant than ever.

One of the primary responsibilities of an ethical AI system is to protect the environment and stop human violations on nature in the name of modernization and development so that future generations can keep breathing happily and live joyfully.

Consider an AI that has hedonism as its final goal, and which would therefore like to tile the universe with “hedonium” (matter organized in a configuration that is optimal for the generation of pleasurable experience). To this end, the AI might produce computronium (matter organized in a configuration that is optimal for computation) and use it to implement digital minds in states of euphoria. In order to maximize efficiency, the AI omits from the implementation any mental faculties that are not essential for the experience of pleasure, and exploits any computational shortcuts that according to its definition of pleasure do not vitiate the generation of pleasure. For instance, the AI might confine its simulation to reward circuitry, eliding faculties such as a memory, sensory perception, executive function, and language; it might simulate minds at a relatively coarse-grained level of functionality, omitting lower-level neuronal processes; it might replace commonly repeated computations with calls to a lookup table; or it might put in place some arrangement whereby multiple minds would share most parts of their underlying computational machinery (their “supervenience bases” in philosophical parlance). Such tricks could greatly increase the quantity of pleasure producible with a given amount of resources.

It is critical to recognize the limitations of LLMs from a consumer perspective. LLMs only possess statistical knowledge about word patterns, not true comprehension of ideas, facts, or emotions. Their fluency can create an illusion of human-like understanding, but rigorous testing reveals brittleness. Just because a LLM can generate coherent text about medicine or law doesn’t mean it grasps those professional domains. It does not. Responsible evaluation is essential to avoid overestimating capabilities.

AI algorithms should be tuned with human values, empathy, and a deep understanding of the consequences of their actions.

Chatbots and other AIs may not have any feelings of their own, but they are now being trained to generate feelings in humans and form intimate relationships with us.

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.

Ethics is the map that helps artificial intelligence make decisions that are good for people and the world. Without addressing ethics, AI can be cause of chaos and suffering for humanity.

The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. . . . As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.

Any use of this publication to “train” generative artificial intelligence (AI) technologies to generate text is expressly prohibited. The author reserves all rights to license uses of this work for generative AI training and development of machine learning language models. The author will not license AI companies this right. The author has already had more than 25 novels scraped without payment by AI companies. The author would like AI companies to fuck off.

In an era of generative AI, trust will accrue greater value in the marketplace. People will elevate trust on their list of prerequisites to purchase and prerequisites to engage with content. Furthermore, there will be a redistribution of income and assets from companies and people who are less trusted to those companies and people who are more trusted.

The evolution of AI should always be guided by shared Human Values, the protection of human rights, and the survival of future generations.

The man persisted. "No, no, no. It was so funny. What software did you use?" - apparently in the belief that the software had built-in humor generation.

The true potential of AI lies in its ability to uplift humanity while safeguarding and empowering future generations.

Compassionate AI has many roles in achieving the United Nations' development goals, especially in healthcare and the protection of humanity.

ChatGPT cannot write. Generating syntax is not the same thing as writing. Writing is an embodied act of thinking and feeling.

I want to create a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human.

Generative AIs can produce reliable, near-perfect virtual scenarios, and AIs that expand consciousness can induce perceptions, but they still cannot completely erase the residual imprint of reality.

To get just an inkling of the fire we're playing with, consider how content-selection algorithms function on social media. They aren't particularly intelligent, but they are in a position to affect the entire world because they directly influence billions of people. Typically, such algorithms are designed to maximize click-through, that is, the probability that the user clicks on presented items. The solution is simply to present items that the user likes to click on, right? Wrong. The solution is to change the user's preferences so that they become more predictable. A more predictable user can be fed items that they are likely to click on, thereby generating more revenue. People with more extreme political views tend to be more predictable in which items they will click on. (Possibly there is a category of articles that die-hard centrists are likely to click on, but it’s not easy to imagine what this category consists of.) Like any rational entity, the algorithm learns how to modify its environment —in this case, the user’s mind—in order to maximize its own reward.

In the wake of the generative content era, using AI to generate content for clients may seem convenient, but it is not a sustainable long-term strategy. Clients can easily access similar AI tools themselves. Instead, focus on leveraging artificial intelligence to enhance your creativity, streamline processes, and provide personalized value to your clients. With this, you are several yards ahead of the packs out there and your result will be massive.

Realizing the newfound promise of electrification a century ago required four key inputs: fossil fuels to generate it, entrepreneurs to build new businesses around it, electrical engineers to manipulate it, and a supportive government to develop the underlying public infrastructure. Harnessing the power of AI today—the “electricity” of the twenty-first century—requires four analogous inputs: abundant data, hungry entrepreneurs, AI scientists, and an AI-friendly policy environment.

The railroads that delivered goods to market were the same that delivered soldiers to battle — but they had no destructive potential. Nuclear technologies are often dual-use and may generate tremendous destructive capacity, but their complicated infrastructure enables relatively secure governmental control. A hunting rifle may be in widespread use and possess both military and civilian applications, but its limited capacity prevents its wielder from inflicting destruction on a strategic level.

We are entering a world where we are going back to a pre–Industrial Revolution, craftsmanlike experience. A small group of people who understand engineering, sales, marketing, finance, and design are going to be able to manage armies of generative AI and put all of these pieces together.

Throw in the valley’s rich history of computer science breakthroughs, and you’ve set the stage for the geeky-hippie hybrid ideology that has long defined Silicon Valley. Central to that ideology is a wide-eyed techno-optimism, a belief that every person and company can truly change the world through innovative thinking. Copying ideas or product features is frowned upon as a betrayal of the zeitgeist and an act that is beneath the moral code of a true entrepreneur. It’s all about “pure” innovation, creating a totally original product that generates what Steve Jobs called a “dent in the universe.” Startups that grow up in this kind of environment tend to be mission-driven. They start with a novel idea or idealistic goal, and they build a company around that. Company mission statements are clean and lofty, detached from earthly concerns or financial motivations.

Caring Across Generations, led jointly by twenty organizations representing caregivers, care consumers, and their families, is a national movement to embrace our changing demographics, particularly the aging of America, and an opportunity to strengthen our intergenerational and caregiving relationships.

Generative AI has unlocked exciting possibilities in the realms of images and videos. Its manipulation and transformative capabilities offer new avenues for artistic expression, content creation, and immersive storytelling. As this technology continues to evolve, it is essential to leverage its power responsibly and ensure its positive impact on society.

Labor of AI (The Sonnet) Asking AI to help you write, is not writing. Asking AI to tune your voice, is not singing. Asking AI to help you paint, is not painting. Asking AI to help you code, is not coding. Asking AI to help you create, is not creativity. Asking AI to build your dream, is not dreaming. Asking AI to narrate books, is not storytelling. AI oughta do manual labor, so humans can do the creating.

In the competitive world of digital marketing, converting prospects into loyal customers is the ultimate goal for any business. CallTrack.AI emerges as a revolutionary tool in this quest, leveraging the power of artificial intelligence to transform the lead generation process. How CallTrack.AI redefines the approach to capturing and nurturing leads, ultimately leading to higher conversion rates and a robust customer base?

The world has been changing even faster as people, devices and information are increasingly connected to each other. Computational power is growing and quantum computing is quickly being realised. This will revolutionise artificial intelligence with exponentially faster speeds. It will advance encryption. Quantum computers will change everything, even human biology. There is already one technique to edit DNA precisely, called CRISPR. The basis of this genome-editing technology is a bacterial defence system. It can accurately target and edit stretches of genetic code. The best intention of genetic manipulation is that modifying genes would allow scientists to treat genetic causes of disease by correcting gene mutations. There are, however, less noble possibilities for manipulating DNA. How far we can go with genetic engineering will become an increasingly urgent question. We can’t see the possibilities of curing motor neurone diseases—like my ALS—without also glimpsing its dangers. Intelligence is characterised as the ability to adapt to change. Human intelligence is the result of generations of natural selection of those with the ability to adapt to changed circumstances. We must not fear change. We need to make it work to our advantage. We all have a role to play in making sure that we, and the next generation, have not just the opportunity but the determination to engage fully with the study of science at an early level, so that we can go on to fulfil our potential and create a better world for the whole human race. We need to take learning beyond a theoretical discussion of how AI should be and to make sure we plan for how it can be. We all have the potential to push the boundaries of what is accepted, or expected, and to think big. We stand on the threshold of a brave new world. It is an exciting, if precarious, place to be, and we are the pioneers. When we invented fire, we messed up repeatedly, then invented the fire extinguisher. With more powerful technologies such as nuclear weapons, synthetic biology and strong artificial intelligence, we should instead plan ahead and aim to get things right the first time, because it may be the only chance we will get. Our future is a race between the growing power of our technology and the wisdom with which we use it. Let’s make sure that wisdom wins.

Deepfakes are built on a technology called generative adversarial networks (GAN). As the name suggests, a GAN is a pair of “adversarial” deep learning neural networks. The first network, the forger network, tries to generate something that looks real, let’s say a synthesized picture of a dog, based on millions of pictures of dogs. The other network, the detective network, compares the forger’s synthesized dog picture with genuine dog pictures, and determines if the forger’s output is real or fake.

In 1900, 2 percent of fossil fuel production was devoted to producing electricity, by 1950 it was above 10 percent, and in 2000 it reached more than 30 percent. In 1900 global electricity generation stood at 8 terawatt-hours; fifty years later it was at 600, powering a transformed economy. The Nobel Prize–winning economist William Nordhaus calculated that the same amount of labor that once produced fifty-four minutes of quality light in the eighteenth century now produces more than fifty years of light.

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

The Future of Lead Generation CallTrack.AI stands at the forefront of a new era in lead generation. By harnessing the capabilities of AI, businesses can not only improve their lead generation processes but also revolutionize the way they interact with prospects. The result is a more efficient, personalized, and successful approach to converting leads into loyal customers. As AI continues to evolve, CallTrack.AI remains a pivotal tool for businesses looking to thrive in the digital marketplace. Read more at CallTrack.Ai

Open source philosophies once promised to democratize access to cutting-edge technologies radically. Yet for AI, the eventual outcome of the high-stakes battle between open and closed systems remains highly uncertain. Powerful incentives pull major corporate powers to co-opt open source efforts for greater profit and control, however subtly such dynamics might unfold. Yet independent open communities intrinsically chafe against restrictions and centralized control over capacity to innovate. Both sides are digging in for a long fight.

But the one option that should not be on offer in elections is hiding or distorting the truth. If the majority prefers to consume whatever amount of fossil fuels it wishes with no regard to future generations or other environmental considerations, it is entitled to vote for that. But the majority should not be entitled to pass a law stating that climate change is a hoax and that all professors who believe in climate change must be fired from their academic posts. We can choose what we want, but we shouldn’t deny the true meaning of our choice.

The journey of a thousands suns begins today. Some may question whether the journey is worth the sacrifice and danger. To them I say that no sacrifice is too dear and no danger too great to ensure the very survival of our human species. What will we find when we arrive at our new homes? That's an open question. For a century, deep-space probes have reported alien lifeforms, but thus far none of which we recognize as intelligent beings. Are we the only biological intelligence in the universe? Perhaps our definition of intelligence is too narrow, too specio-centric. For, are not trees intelligent, who know to shed their leaves at the end of summer? Are not turtles intelligent, who know when to bury themselves in mud under ice? Is not all life intelligent, that knows how to pass its vital essence to new generations? Because half of intelligence resides in the body, be it plant or animal. I now commend these brave colonists to the galaxy, to join their minds and bodies to the community of living beings they will encounter there, and to establish our rightful place among the stars.

But with Moore’s law spewing out new generations of computers every eighteen months, sooner or later the old pessimism of the past generation will be gradually forgotten and a new generation of bright enthusiasts will take over, creating renewed optimism and energy in the once-dormant field. Thirty years after the last AI winter set in, computers have advanced enough so that the new generation of AI researchers are again making hopeful predictions about the future. The time has finally come for AI, say its supporters. This time, it’s for real. The third try is the lucky charm. But if they are right, are humans soon to be obsolete?

And you can’t figure out why an AI is generating a hallucination by asking it. It is not conscious of its own processes. So if you ask it to explain itself, the AI will appear to give you the right answer, but it will have nothing to do with the process that generated the original result. The system has no way of explaining its decisions, or even knowing what those decisions were. Instead, it is (you guessed it) merely generating text that it thinks will make you happy in response to your query. LLMs are not generally optimized to say “I don’t know” when they don’t have enough information. Instead, they will give you an answer, expressing confidence.

This tends to make us uncomfortable: After all, how can AI, a machine, generate something new and creative? The issue is that we often mistake novelty for originality. New ideas do not come from the ether; they are based on existing concepts. Innovation scholars have long pointed to the importance of recombination in generating ideas. Breakthroughs often happen when people connect distant, seemingly unrelated ideas. To take a canonical example, the Wright brothers combined their experience as bicycle mechanics and their observations of the flight of birds to develop their concept of a controllable plane that could be balanced and steered by warping its wings.

RENEWABLE ENERGY REVOLUTION: SOLAR + WIND + BATTERIES In addition to AI, we are on the cusp of another important technological revolution—renewable energy. Together, solar photovoltaic, wind power, and lithium-ion battery storage technologies will create the capability of replacing most if not all of our energy infrastructure with renewable clean energy. By 2041, much of the developed world and some developing countries will be primarily powered by solar and wind. The cost of solar energy dropped 82 percent from 2010 to 2020, while the cost of wind energy dropped 46 percent. Solar and onshore wind are now the cheapest sources of electricity. In addition, lithium-ion battery storage cost has dropped 87 percent from 2010 to 2020. It will drop further thanks to the massive production of batteries for electrical vehicles. This rapid drop in the price of battery storage will make it possible to store the solar/wind energy from sunny and windy days for future use. Think tank RethinkX estimates that with a $2 trillion investment through 2030, the cost of energy in the United States will drop to 3 cents per kilowatt-hour, less than one-quarter of today’s cost. By 2041, it should be even lower, as the prices of these three components continue to descend. What happens on days when a given area’s battery energy storage is full—will any generated energy left unused be wasted? RethinkX predicts that these circumstances will create a new class of energy called “super power” at essentially zero cost, usually during the sunniest or most windy days. With intelligent scheduling, this “super power” can be used for non-time-sensitive applications such as charging batteries of idle cars, water desalination and treatment, waste recycling, metal refining, carbon removal, blockchain consensus algorithms, AI drug discovery, and manufacturing activities whose costs are energy-driven. Such a system would not only dramatically decrease energy cost, but also power new applications and inventions that were previously too expensive to pursue. As the cost of energy plummets, the cost of water, materials, manufacturing, computation, and anything that has a major energy component will drop, too. The solar + wind + batteries approach to new energy will also be 100-percent clean energy. Switching to this form of energy can eliminate more than 50 percent of all greenhouse gas emissions, which is by far the largest culprit of climate change.

Early on, there was even a hope that online communications could generate a new public sphere, one where people from even more diverse backgrounds than in local politics could freely interact and exchange opinions. Unfortunately, online democracy is not in line with the business models of leading tech companies and the AI illusion. In fact, it is diametrically opposed to a technocratic approach, which maintains that many important decisions are too complex for regular people. The vibe in the corridors of most tech companies is that men of genius are at work, striving for the common good. It is only natural that they should be the ones making the important decisions. When approached this way, the political discourse of the masses becomes something to be manipulated and harvested, not something to be encouraged and protected.

Large language models do not “write.” They generate syntax. They do not think, feel, or experience anything. They are fundamentally incapable of judging truth, accuracy, or veracity. Any actions that look like the exercise of judgment are illusory. While the term hallucination has come to mean outputs from LLMs that are incorrect or untrue, it is arguably more accurate to say that from the point of view of the LLM, everything is a hallucination, as it has no reference points from which to judge its own production. ChatGPT is fundamentally a “bullshitter” as defined by Harry Frankfurt in his classic treatise on the term (On Bullshit), something “unconnected to concern for the truth.” It’s not that ChatGPT makes stuff up. It has no capacity for discerning something true from something not true. Truth is irrelevant to its operations.

We already have eight hundred million people living in hunger—and population is growing by eighty million a year. Over a billion people are in poverty—and present industrial strategies are making them poorer, not richer. The percentage of old people will double by 2050—and already there aren’t enough young people to care for them. Cancer rates are projected to increase by seventy percent in the next fifteen years. Within two decades our oceans will contain more microplastics than fish. Fossil fuels will run out before the end of the century. Do you have an answer to those problems? Because I do. Robot farmers will increase food production twentyfold. Robot carers will give our seniors a dignified old age. Robot divers will clear up the mess humans have made of our seas. And so on, and so on—but every single step has to be costed and paid for by the profits of the last.” He paused for breath, then went on, “My vision is a society where autonomous, intelligent bots are as commonplace as computers are now. Think about that—how different our world could be. A world where disease, hunger, manufacturing, design, are all taken care of by AI. That’s the revolution we’re shooting for. The shopbots get us to the next level, that’s all. And you know what? This is not some binary choice between idealism or realism, because for some of us idealism is just long-range realism. This shit has to happen. And you need to ask yourself, do you want to be part of that change? Or do you want to stand on the sidelines and bitch about the details?” We had all heard this speech, or some version of it, either in our job interviews, or at company events, or in passionate late-night tirades. And on every single one of us it had had a deep and transformative effect. Most of us had come to Silicon Valley back in those heady days when it seemed a new generation finally had the tools and the intelligence to change the world. The hippies had tried and failed; the yuppies and bankers had had their turn. Now it was down to us techies. We were fired up, we were zealous, we felt the nobility of our calling…only to discover that the general public, and our backers along with them, were more interested in 140 characters, fitness trackers, and Grumpy Cat videos. The greatest, most powerful deep-learning computers in humanity’s existence were inside Google and Facebook—and all humanity had to show for it were adwords, sponsored links, and teenagers hooked on sending one another pictures of their genitals.

The human collective knows far more today than did the ancient bands. But at the individual level, ancient foragers were the most knowledgeable and skilful people in history. There is some evidence that the size of the average Sapiens brain has actually decreased since the age of foraging.5 Survival in that era required superb mental abilities from everyone. When agriculture and industry came along people could increasingly rely on the skills of others for survival, and new ‘niches for imbeciles’ were opened up. You could survive and pass your unremarkable genes to the next generation by working as a water carrier or an assembly-line worker. Foragers mastered not only the surrounding world of animals, plants and objects, but also the internal world of their own bodies and senses. They listened to the slightest movement in the grass to learn whether a snake might be lurking there. They carefully observed the foliage of trees in order to discover fruits, beehives and bird nests. They moved with a minimum of effort and noise, and knew how to sit, walk and run in the most agile and efficient manner. Varied and constant use of their bodies made them as fit as marathon runners. They had physical dexterity that people today are unable to achieve even after years of practising yoga or t’ai chi.

[All] modern chatbots are actually trained simply to predict the next word in a sequence of words. They generate text by repeatedly producing one word at a time. For technical reasons, they generate a “token” at a time, tokens being chunks of words that are shorter than words but longer than individual letters. They string these tokens together to generate text. When a chatbot begins to respond to you, it has no coherent picture of the overall response it’s about to produce. It instead performs an absurdly large number of calculations to determine what the first word in the response should be. After it has output—say, a hundred words—it decides what word would make the most sense given your prompt together with the first hundred words that it has generated so far. This is, of course, a way of producing text that’s utterly unlike human speech. Even when we understand perfectly well how and why a chatbot works, it can remain mind-boggling that it works at all. Again, we cannot stress enough how computationally expensive all this is. To generate a single token—part of a word—ChatGPT has to perform roughly a trillion arithmetic operations. If you asked it to generate a poem that ended up having about a thousand tokens (i.e., a few hundred words), it would have required about a quadrillion calculations—a million billion.

Imagine an alternate universe in which people don’t have words for different forms of transportation—only the collective noun “vehicle.” They use that word to refer to cars, buses, bikes, spacecraft, and all other ways of getting from place A to place B. Conversations in this world are confusing. There are furious debates about whether or not vehicles are environmentally friendly, even though no one realizes that one side of the debate is talking about bikes and the other side is talking about trucks. There is a breakthrough in rocketry, but the media focuses on how vehicles have gotten faster—so people call their car dealer (oops, vehicle dealer) to ask when faster models will be available. Meanwhile, fraudsters have capitalized on the fact that consumers don’t know what to believe when it comes to vehicle technology, so scams are rampant in the vehicle sector. Now replace the word “vehicle” with “artificial intelligence,” and we have a pretty good description of the world we live in. Artificial intelligence, AI for short, is an umbrella term for a set of loosely related technologies. ChatGPT has little in common with, say, software that banks use to evaluate loan applicants. Both are referred to as AI, but in all the ways that matter—how they work, what they’re used for and by whom, and how they fail—they couldn’t be more different.

Njeriu jeton jo vetëm jetën e vet personale, por, me vetëdije apo pa vetëdije edhe atë të epokës dhe të bashkëkohësve të vet dhe, edhe në qoftë se do të ishte i prirur që bazat e përgjithshme dhe jashtëpërsonale të ekzistencës së tij t'i shihte si të dhëna në mënyrë të vetëkuptueshme, si edhe të ishte aq larg idesë për t'i kritikuar, siç ishte Hans Kastorpi shpirtmirë, do të ishte sidoqoftë gjithsesi e mundshme që ai t'i ndjente ashtu turbull mungesat dhe ndikimet e tyre në vetëndijimin e tij moral. Njeriut të veçantë mund t'i vegojnë para syve shumë qëllime, pikësynime, shpresa, perspektiva, prej të cilave ai merr shtysa për sforcime dhe veprimtari më të vrullshme, por kur jashtëpersonalja përreth tij, koha vetë, me gjithë përpjekjet e tij, u heq motivimin shpresave dhe perspektivave, në qoftë se ajo i shfaqet si e pashpresë, pa përspektivë dhe pyetjeve dhe pyetjeve të vëna, me apo pa vetëdije, por sidoqoftë të vëna në ndonjë mënyrë mbi kuptimin fundor, më tepër se personal, të të gjitha sforcimeve dhe veprimatarive, ajo u vë përballë një heshtje të shurdhër, kjo gjëndje e gjërave do të ushtronte një farë ndikimi paralizues qoftë edhe mbi karakteret më të mirëfilltë njerëzorë, ndikim i cili, përtej shpirtit dhe moralit, do të mund të shtrihej edhe mbi pjesën fizike dhe oraganike të individit. Për të qenë i gatshëm për një sforcim të madh, që sidoqoftë e kalon masën e atij të zakonshmit, pa qenë në gjëndje që t'i japë një përgjigje të kënaqshme pyetjes "përse"?, për këtë duhet ose një vetmi dhe pastërti morale që është e rrallë dhe e një natyre heroike, ose një vitalitet shumë i shëndoshë. Hans Kastorpi nuk e kishte as njërën, as tjetrën dhe nuk mund të ishte pra, veçse një i rëndomtë, ndonëse në një kuptim tepër pozitiv.

In the introduction, I wrote that COVID had started a war, and nobody won. Let me amend that. Technology won, specifically, the makers of disruptive new technologies and all those who benefit from them. Before the pandemic, American politicians were shaking their fists at the country’s leading tech companies. Republicans insisted that new media was as hopelessly biased against them as traditional media, and they demanded action. Democrats warned that tech giants like Amazon, Facebook, Apple, Alphabet, and Netflix had amassed too much market (and therefore political) power, that citizens had lost control of how these companies use the data they generate, and that the companies should therefore be broken into smaller, less dangerous pieces. European governments led a so-called techlash against the American tech powerhouses, which they accused of violating their customers’ privacy. COVID didn’t put an end to any of these criticisms, but it reminded policymakers and citizens alike just how indispensable digital technologies have become. Companies survived the pandemic only by allowing wired workers to log in from home. Consumers avoided possible infection by shopping online. Specially made drones helped deliver lifesaving medicine in rich and poor countries alike. Advances in telemedicine helped scientists and doctors understand and fight the virus. Artificial intelligence helped hospitals predict how many beds and ventilators they would need at any one time. A spike in Google searches using phrases that included specific symptoms helped health officials detect outbreaks in places where doctors and hospitals are few and far between. AI played a crucial role in vaccine development by absorbing all available medical literature to identify links between the genetic properties of the virus and the chemical composition and effects of existing drugs.

A ce discours, Candide s’évanouit encore; mais revenue à soi, et ayant dit tout ce qu’il devait dire, il s’enquit de la cause et de l’effet, et de la raison suffisante qui avait mis Pangloss dans un si piteux état. Hélas! dit l’autre, c’est l’amour: l’amour, le consolateur du genre humain, le conservateur de l’univers, l’âme de tous les êtres sensibles, le tender amour. Hélas! dit Candide, je l’ai connu cet amour, ce souverain des coeurs, cette âme de notre âme, il ne m’a jamais valu qu’un baiser et vingt coups de pied au cul. Comment cette belle cause a-t-elle pu produire en vous un effet si abominable? Pangloss répondit en ces termes: O mon cher Candide! vous avez connu Paquette, cette jolie suivante de notre auguste baronne: j’ai goûté dans ses bras les délices du paradis, qui ont produit ces tourments d’enfer dont vous me voyez dévoré; elle en était infectée, elle en est peut-être morte. Paquette tenait ce present d’un Cordelier très savant qui avait remonté à la source, car il l’avait eu d’une vieille comtesse, qui l’avait reçu d’un capitaine de cavalerie, qui le devait à une marquise, qui le tenait d’un page, qui l’avait reçu d’un jésuite, qui, étant novice, l’avait eu en droite ligne d’un des compagnons de Christophe Colomb. Pour moi, je ne le donnerai à personne, car je me meurs. O Pangloss! s’écria Candide, voilà une étrange généalogie! n’est-ce pas le diable qui en fut la souche? Point du tout, répliqua ce grand home; c’était une chose indispensable dans le meilleur des mondes, un ingredient nécessaire; car si Colomb n’avait pas attrapé dans une île de l'Amérique cette maladie qui empoisonne la source de la generation, qui souvent meme empêche la generation, et qui est évidemment l’opposé du grand but de la nature, nous n’aurions ni le chocolat ni la cochenille; il faut encore observer que jusqu’aujourd’hui, dans notre continent, cette maladie nous est particulière, comme la controverse.

In 2017, US companies are estimated to have allocated more than $650 million to fuel the AI talent race, with more than 10,000 available positions at top employers across the country. The top five tech companies have the capital to crowd out competitors: startups, universities, municipalities, established corporations in other industries, and less wealthy countries.31 In Britain, university administrators are already talking about a “missing generation” of data scientists.

I firmly believe we must forge a new synergy between artificial intelligence and the human heart, and look for ways to use the forthcoming material abundance generated by artificial intelligence to foster love and compassion in our societies.

AI will certainly increase productivity across society, but can it really generate the huge sums necessary to finance such dramatic expansion in government expenditures? This too remains an open question, one that will only be settled once the AI technologies themselves proliferate across our economies. If AI meets or exceeds predictions for productivity gains and wealth creation, I believe we could fund these types of programs through super taxes on super profits. Yes, it would somewhat cut into economic incentives to advance AI, but given the dizzying profits that will accrue to the winners in the AI age, I don’t see this as a substantial impediment to innovation.

It could enable an open and interoperable new generation of the web—a Web 3.0 era that secures the privacy and property rights of individuals while ensuring secure and trustworthy interactions and transactions between the human, machine, and virtual economies. This future literally adds a new dimension to the web. It enables —The Spatial Web.

If artificial intelligence is the new electricity, big data is the oil that powers the generators.

Gordon dismissed the productivity potential of autonomous cars, failing to understand that the reduction in accidents and the decrease in traffic jams would generate an estimated $1 trillion in annual savings to the US economy.

Tools like ChatGPT are designed to assist and enhance human capabilities, not replace them entirely. Much like using Google for information retrieval, ChatGPT can be a valuable resource for obtaining quick information, generating ideas, or seeking assistance. When Google was introduced, some argued that it would make people lazy in terms of information retrieval. "Why bother memorizing facts when you can quickly search for them?" However, this didn't necessarily make people less intelligent; it shifted the emphasis from memorization to critical thinking and information synthesis. Similarly, ChatGPT doesn't make individuals lazy; it changes the nature of cognitive tasks. Instead of focusing on rote memorization or routine information retrieval, people can allocate their mental energy to more complex and creative endeavors. The key is how individuals use these tools.

Every photograph has the capacity to be a creative canvas, and with the correct tools, commonplace events may become engrossing visual tales. Here's PicVik, an AI photo editor, collage creator, and background remover tool that blurs the lines between creativity and innovation. PicVik is more than simply an app; it's a doorway to a world where your artistic ambitions and the power of artificial intelligence collide. With PicVik, you can easily remove backgrounds from photos, create complex collages, and enhance the details in your images. PicVik is meant to be your go-to tool for digital art.

For a story on Facebook’s failings in developing countries, Newley Purnell and Justin Scheck found a woman who had been trafficked from Kenya to Saudi Arabia, and they were looking into the role Facebook had played in recruiting hit men for Mexican drug lords. That story would reveal that Facebook had failed to effectively shut down the presence of the Jalisco New Generation Cartel on Facebook and Instagram, allowing it to repeatedly post photos of extreme gore, including severed hands and beheadings. Looking into how the platform encouraged anger, Keach Hagey relied on documents showing that political parties in Poland had complained to Facebook that the changes it had made around engagement made them embrace more negative positions. The documents didn’t name the parties; she was trying to figure out which ones. Deepa Seetharaman was working to understand how Facebook’s vaunted AI managed to take down such a tiny percentage—a low single-digit percent, according to the documents Haugen had given me—of hate speech on the platform, including constant failures to identify first-person shooting videos and racist rants.

Ideas are constantly being generated, abandoned, and rediscovered. A good idea—a real breakthrough—will often go unnoticed at the time and may only later be understood as having provided the basis for a substantial advance in AI, perhaps when someone reinvents it at a more convenient time. Ideas are tried out, initially on simple problems to show that the basic intuitions are correct and then on harder problems to see how well they scale up. Often, an idea will fail by itself to provide a substantial improvement in capabilities, and it has to wait for another idea to come along so that the combination of the two can demonstrate value.

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A better alternative might be to combine the incentive method with the use of motivation selection to give the AI a final goal that makes it easier to control. Suppose that an AI were designed to have as its final goal that a particular red button inside a command bunker never be pressed. Since the pressing of the button is disvalued intrinsically and not because of its causal consequences, the button could be completely inert: it could be made of Play-Doh. Furthermore, it is irrelevant whether the AI can ever know whether the button had been pressed. What is essential is that the AI believes that the button will more likely remain unpressed if the AI continuously acts in the principal’s interest than if it rebels. Refinements to this setup are possible. Instead of trying to endow an AI with a final goal that refers to a physical button, one could build an AI that places final value on receiving a stream of “cryptographic reward tokens.”11 These would be sequences of numbers serving as keys to ciphers that would have been generated before the AI was created and that would have been built into its motivation system.12 These special number sequences would be extremely desirable to the AI, constituting a special kind of reward token that the AI could not attain though wireheading.13 The keys would be stored in a secure location where they could be quickly destroyed if the AI ever made an attempt to seize them. So long as the AI cooperates, the keys are doled out at a steady rate.

Just as AI lacks the causal frames to win at Dota 2 and needs them encoded by people, so too computers can’t generate counterfactuals on their own but require people to supply them. Carcraft’s rare scenarios were not the result of a machine dreaming alternative worlds, or randomly generating extreme events. Rather, humans came up with them.

I have an uncompromising principle against the use of AI in literature.

Part of the issue is the characterisation of generative AI as a human replacement. This makes people treat the tool as a hyperintelligent magical being that deserves reverence. Recent research, however, shows that AI tools get the law wrong between 69 and 88 per cent of the time, producing 'legal hallucinations' when asked 'specific, verifiable questions about random federal court cases'. A human lawyer or judge with that kind of error rate would undermine public faith in justice. Automation bias means we are more likely to believe the machine than the person who questions it, but also more likely to cut it some slack when we know it has got things wrong. Automation bias's little sibling, automation complacency, means that we are also less likely to check the output of a machine than that of a human. The problem is not the technology; it is the human perception of it that leads us to put it to utterly unsuitable uses which makes it dangerous.

NO AI TRAINING: Without in any way limiting the author’s and publisher’s exclusive rights under copyright, any use of this publication to “train” generative artificial intelligence (AI) technologies to generate text is expressly prohibited. The author reserves all rights to license uses of this work for generative AI training and development of machine learning language models.

Teams are working on products that will generate new DNA sequences using only natural language instructions. Transformer models are learning the language of biology and chemistry, again discovering relationships and significance in long, complex sequences illegible to the human mind.

No part of the book was generated by AI. All intelligence witnessed herein is my own, which is worrisome enough.

Statement on Generative AI Just like Artificial Intelligence as a whole, on the matter of Generative AI, the world is divided into two camps - one side is the ardent advocate, the other is the outspoken opposition. As for me, I am neither. I don't have a problem with AI generated content, I have a problem when it's rooted in fraud and deception. In fact, AI generated content could open up new horizons of human creativity - but only if practiced with conscience. For example, we could set up a whole new genre of AI generated material in every field of human endeavor. We could have AI generated movies, alongside human movies - we could have AI generated music, alongside human music - we could have AI generated poetry and literature, alongside human poetry and literature - and so on. The possibilities are endless - and all above board. This way we make AI a positive part of human existence, rather than facilitating the obliteration of everything human about human life. This of course brings up a rather existential question - how do we distinguish between AI generated content and human created material? Well, you can't - any more than you can tell the photoshop alterations on billboard models or good CGI effects in sci-fi movies. Therefore, that responsibility must be carried by experts, just like medical problems are handled by healthcare practitioners. Here I have two particular expertise in mind - one precautionary, the other counteractive. Let's talk about the counteractive measure first - this duty falls upon the shoulders of journalists. Every viral content must be source-checked by responsible journalists, and declared publicly as fake, i.e. AI generated, unless recognized otherwise. Littlest of fake content can do great damage to society - therefore - journalists, stand guard! Now comes the precautionary part. Precaution against AI generated content must be borne by the makers of AI, i.e. the developers. No AI model must produce any material without some form of digital signature embedded in them, that effectively makes the distinction between AI generated content and human material mainstream. If developers fail to stand accountable out of their own free will, they must be held accountable legally. On this point, to the nations of the world I say, you can't expect backward governments like our United States to take the first step - where guns get priority over children - therefore, my brave and civilized nations of the world - you gotta set the precedent on holding tech giants accountable - without depending on morally bankrupt democratic imperialists. And remember, the idea is not to ban innovation, but to adapt it with human welfare. All said and done, the final responsibility falls upon just one person, and one person alone - the everyday ordinary consumer. Your mind has no reason to not believe the things you find on the internet, unless you make it a habit to actively question everything - or at least, not accept anything at face value. Remember this. Just because it's viral, doesn't make it true. Just because it's popular, doesn't make it right.

I don't have a problem with AI generated content, I have a problem when it's rooted in fraud and deception. In fact, AI generated content could open up new horizons of human creativity - but only if practiced with conscience. For example, we could set up a whole new genre of AI generated material in every field of human endeavor. We could have AI generated movies, alongside human movies - we could have AI generated music, alongside human music - we could have AI generated poetry and literature, alongside human poetry and literature - and so on. The possibilities are endless - and all above board. This way we make AI a positive part of human existence, rather than facilitating the obliteration of everything human about human life.

No AI model must produce any material without some form of digital signature embedded in them, that effectively makes the distinction between AI generated content and human material mainstream. If developers fail to stand accountable out of their own free will, they must be held accountable legally.

The key to getting the best results from these tools is to write a good prompt. You want to give the tool enough information and context so that it can generate something useful and relevant to what you’re looking for. Trust me, it makes all the difference, and

This generation will witness social and economic changes in our societies, that will be irreversible, thanks to AI.

It is the author’s strong belief that the current state of generative AI is unethical, and exists solely because of the unauthorized theft and use of work from countless artists and writers.

Once upon a time, knowledge was king. The person who could provide the answers, solve the most problems and remember the most facts was considered the smartest in the room. Being intellectually sharp was synonymous with possessing vast stores of information and the ability to recall it at a moment's notice. However, with the rise and widespread use of tools like ChatGPT and other Generative AI technologies, this paradigm has shifted.

The first principle is that you must not fool yourself, and you are the easiest person to fool.’ By relying solely on AI-generated answers without understanding the reasoning behind them, we run the risk of fooling ourselves and accepting information without scrutiny.

As we navigate the transformative era of Generative AI, let us leverage this powerful technology to redefine the boundaries of possibility, fostering creativity, efficiency, and growth. In this journey, we are not merely participants but pioneers, shaping a future where business and technology converge to unlock new realms of human achievement.

Internet platforms such as Substack, Flipboard, and Steemit enable individuals not only to create content but also to become independent producers and brand managers of their work.

Monkeys burn millions selling you the future, while back on earth humans struggle to make ends meet on 1/4 to 7 dollar hourly wage.

Sonnet 1492 If you cared more about making people smile than bringing machines to life, we'd be at a much better place. With all the tech we have today, we could equalize the world tomorrow. But no, cyborgs gotta develop more, they feel impotent unless their tentacles grow. That's why, neither genocide nor invasion must obstruct the growth of apely machines. It's okay if children die of malnourishment, funding mustn't cease for glorious tech fiends. Terrestrial terrains to celestial shores, humanity is the only species to die of smart-ness. If we cared more about people than devices, truly and honestly, we'd be at a much better place.

With all the tech we have today, we could equalize the world tomorrow. But no, cyborgs gotta develop more, they feel impotent unless their tentacles grow. That's why, neither genocide nor invasion must obstruct the growth of apely machines. It's okay if children die of malnourishment, funding mustn't cease for glorious tech fiends.

If you cared more about making people smile than bringing machines to life, we'd be at a much better place.

Yet another pondered: If a teacher generates lesson plans with an AI, who gets the credit? (I wondered what the importance of credit in lesson planning is in the first place, and if creators on Teachers Pay Teachers get credit if a teacher buys lesson plans there.)

We are crossing a threshold into a new reality in which AI is generating its own programs, creating its own algorithms, and making choices without humans in the loop. At the moment, no one, in any country, has the right to interrogate an AI and see clearly how a decision was made.

Begin rant: I think the internet, social media, smartphones, a progressive education system that teaches socialist values and the false theory of evolution based on an atheistic worldview, moral relativism and post-modern thought mixed with a rejection of biblical truth, social justice over true justice, the teaching that everyone gets a trophy, and that everyone is uniquely special and should desire fame, add to that helicopter parents, absentee parents, confusing parental messages, confusing family structures, gender identity politics, and the idea that this generation is somehow the most brilliant generation ever because they can google every answer or ask some AI-based computer speaker box, mixed with all the confusing heretical, blasphemous, and unbiblical models of the Church, and it’s no wonder these young people are so bent on doing their own thing and not listening to what seems to be hypocritical,

University of North Carolina, Ralph S. Baric had already successfully used reverse genetics10 to generate a chimeric11 (Gain-of-Function) coronavirus. He not only published12 this research funded by the NIH (grant numbers AI23946, GM63228, and

Once I feel the language and culture in my veins, I can deliver my ideas in any language I want. I can write in any language, because I want to. And no, I don't use some fancy AI tools. In fact, I have an uncompromising principle against the use of AI in literature. Heck, I opted not to use something so trivial as an image containing yours truly with a mace, as cover image of "Bulletproof Backbone", because it collided with the book's anti-weaponry vision - so you can imagine my stance on fraudulent material generated by AI! What I do use, while writing in other languages, is old-fashioned dictionary - online dictionary that is, to fix things like spelling, missing vocabulary and other broken bits - which makes me a broken polyglot. And believe you me, broken polyglots are potent polyglots. I may not be fluent in a lot of languages, but after I am long gone, each of these languages and cultures will have something distinctly personal left by me to call their own. For example, I may not speak fluent German, yet if I write even one page in the German language, it'll forever become an indelible part of the German culture. It'll not be some off-key German translation of an original Naskar, rather it'll be a German literature from the vast Naskarean oeuvre. Sure, I know my limits in each of these languages, that's why I keep my sentence structure simple, which I am not compelled to do in Turkish and Spanish. But more than my limits, I am aware of my limitlessness. And once the being transcends the limits of language, culture, border and tradition, puny apparatus like intellect is bound to follow.

The recent revelation regarding the unethical sourcing of data for generative AI models highlights a pressing concern in the technology industry. A report20 by Alex Reisner exposed that major tech giants, including Meta, used copyrighted books to train their language models, violating intellectual property rights. Notable authors like Stephen King, Zadie Smith, and Michael Pollan have been victims of this unauthorized data harvesting.