Ai That Generates Quotes

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

The macrohistorical log is largely siloed across different corporate servers, on the premises of Twitter and Facebook and Google. The posts are typically not digitally signed or cryptographically timestamped, so much of the content is (or could be) from bots rather than humans. Inconvenient digital history can be deleted by putting sufficient pressure on centralized social media companies or academic publishers, censoring true information in the name of taking down “disinformation,” as we’ve already seen. And the advent of AI allows highly realistic fakes of the past and present to be generated.

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?

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.

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.

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.

The practice of AI involves the art of crafting and asking questions that elicit affirmative possibilities.

„Să fim atenți în tot ceea ce facem”, asta auzeam adesea de la bunica. Orice acțiune făcută împotriva sufletului tău sau a sufletului unui alt om are o contraacțiune care la un moment dat își stabilește echilibrul. Fiecare durere se achită. Adesea ne văicărim, ne lamentăm. Există o tonalitate de jale care ne definește la vârsta imaturității... neavând niciun corespondent în vârsta organică. Credem că, atunci când avem glasul subțire, puțin pițigăiat, afectat... chemăm mai ferm îngerii. Credem că dacă suferința se strigă cu voce tare, dispare. Îi cerem atenției celuilalt să ne fie cârjă fără a modifica nimic în noi înșine. Ne facem curaj ascunzând gunoiul sub pat și după ani de zile ne minunăm câți șobolani s-au strâns în suflet și ne rod. Nimic nu rămâne neplătit. Avem întotdeauna opțiunea suferinței noastre. Dacă rămânem în ceea ce ne face rău, rămânem pentru că asta alegem noi, nu celălalt. Ce ne rănește de fapt? Ne doare lipsa noastră de rigoare. Ne simțim vinovați pentru decizii întârziate, nu pentru efectul lor întârziat. Starea de vinovăție este ca starea de contemplare. În sine. Cel mult poate să ne îmbolnăvească. Bolile noastre sunt neputințele noastre. Avem minți și suflete șchioape, ne ologim prin neasumare. Cum să te revolți împotriva a ceva ce tu singur ai generat? Te superi că ți-a luat lopățica, în timp ce Dumnezeu te așteaptă secundă de secundă să pierzi cu El veșnicia. Viața nu face altceva decât să-ți răspundă la ceea ce alegi. Îți dă situațiile pe care le ceri. Acțiunea este o opțiune, se presupune că mai avansată decât gândul sau emoția. Acțiunea ar trebui să fie efectul unui gând așezat și al unor emoții controlate pentru ca ea să fie asumată. Cum să mă supăr pe celălalt pentru ceea ce nu sunt în stare să fiu eu? E ca și cum îl trag la răspundere pentru că mă lasă să greșesc. E firesc să mă lase să aleg. Nimeni nu poate să aleagă în locul meu. Viața mea este suma alegerilor mele. Cum să-i spun celuilalt că îl mint pentru că nu-mi permite să-i spun adevărul și că toate gesturile pe care le face înspre mine cer exact minciuna pe care o ofer? Dacă aleg de bunăvoie să fiu complice la frica și neputința celuilalt, nu pot să-l învinovățesc pe celălalt pentru alegerea mea. Nu suntem prizonierii nimănui. Coliviile sunt create de noi înșine, în mintea noastră și ne place să credem că ele există și în realitate. Realitatea esențială, realitatea simplă a întâlnirii cu Dumnezeu nu are timp de colivii și nici de coșuri de protecție. Cu noi sau fără noi, închiși în propriile viziuni și fantasme, viața curge, universul își vede de treaba lui, celulele, moleculele, energia sunt într-o permanentă mișcare, într-o devenire nestingherită și nu au nici cea mai mică problemă să ne ignore și să nu se oprească pentru digestia micilor noastre intrigi romanțioase. Dacă aleg să mă îmbolnăvesc de lașitate împreună cu tine, este alegerea mea. Dacă vreau să stau în mizerie, stau pentru că aleg eu. Cine poate să aleagă cu adevărat pentru celălalt? Nimeni. Alegem pentru celălalt atunci când suntem lăsați să o facem. Fără a avea nici cel mai mic drept real în acțiunea asta. Dacă vreau să mă pun în situații care îmi provoacă suferința, este opțiunea mea. Nu pot să sufăr pentru că celălalt a reacționat altfel decât am avut eu nevoie. Pot să-i cer celuilalt să-mi dea ce vreau, dar să-i las opțiunea să nu-mi dea dacă nu poate. Nu pot să mă maltratez psihic și emoțional, să mă devorez cu gânduri, să mă intoxic cu ură, revoltă, răzbunare și să consider că toate astea le fac din cauza celuilalt. Încărcându-l pe celălalt cu responsabilitatea asta nu mă descarc pe mine cu nimic. Asumarea este singura realitate în care putem să știm cine suntem. Și, dacă suntem într-o situație care ne face rău, nu-i cerem celuilalt să ne scoată din ea. Pentru că nu celălalt ne-a băgat în ea. Dacă trăim ceea ce nu ne trebuie, noi hotărâm și tot noi oprim. Nu e vina nimănui când trăim altceva decât ceea ce avem nevoie.

The same push toward polarization playing out across the global economy will also exacerbate inequality within the AI superpowers. AI’s natural affinity for monopolies will bring winner-take-all economics to dozens more industries, and the technology’s skill biases will generate a bifurcated job market that squeezes out the middle class. The “great decoupling” of productivity and wages has already created a tear between the 1 percent and the 99 percent. Left to its own devices, artificial intelligence, I worry, will take this tear and rip it wide open.

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.

As a venture-capital investor, I see a particularly strong role for a new kind of impact investing. I foresee a venture ecosystem emerging that views the creation of humanistic service-sector jobs as a good in and of itself. It will steer money into human-focused service projects that can scale up and hire large numbers of people: lactation consultants for postnatal care, trained coaches for youth sports, gatherers of family oral histories, nature guides at national parks, or conversation partners for the elderly. Jobs like these can be meaningful on both a societal and personal level, and many of them have the potential to generate real revenue—just not the 10,000 percent returns that come from investing in a unicorn technology startup.

The purpose of life, in case you feel the need to have an answer to that question, is to become a consistent generator of good vibrations, until you develop an absolute gravitational field around you that continuously draws together all the props of physical reality which support your truest character.

The focus on the self or individual consciousness is obsessed with control, ownership, and an attitude of “Mine, Mine, Mine” that not only blocks movement towards non-localized consciousness but also generates issues and conflicts along the way. It creates a xenophobia that nests and nests.

Humankind now produces in two days the same amount of data it took us from the dawn of civilisation until 2003 to generate.

Once humanity realizes we are reality generators and projectors in this canvas we call life, it will be a pivotal turning point. Conscious comprehension can then be mutually shared and gained.

Humanity is not prepared to face two significant challenges ahead. 1) The use of weapons and war to generate revenue and “resolve” conflict. 2) The ecological crisis already manifesting in this timeline.

The heat we generate not only gets discharged from our bodies, it also helps create the illusion of linear time of what we call the past.

Technologies we fancied years ago have receded into oblivion. We are reminded to double the pace at which we are innovating and ensure the creativity that inundates our minds pave the way for futuristic technologies that have Artificial Intelligence at their core. Undoubtedly, systems without AI at the center of their innovation will be fatal in today's competitive computing world. A future without AI is autonomously reclined, which is dire for making decisions based on colossal data generated from and by our machines. The right amount of computing power is all that is needed to make AI reign supreme; the clock is ticking.

More sophisticated methods exist, of course. A potentially more powerful method is collaborative filtering. It gathers data about what users have bought in the past and uses AI to predict what people are likely to buy in the future. These methods can use both explicit information, like a customer’s ratings of the options, and implicit information, like whether or not they finished a specific program on Netflix. Most famously, perhaps, collaborative filtering is used by Amazon in generating “People who bought this also bought . . .” listings. Collaborative filtering requires a large set of past user behavior to make predictions. This is the heart of suggestions made by Apple Music, “who to follow” suggestions on Twitter, and matches on Tinder. Yes, Tinder apparently changes the people it will show you based on your swipes. Swiping right will change who you see in the future. It’s important to realize that, in its pure form, collaborative filtering doesn’t use in-depth information about the options themselves. When Apple Music recommends a tune, it knows nothing about the song’s tempo, beat, lyrics, or instrumentation. It simply knows that people who are like you like that song too.

If the synthetic sentience announced which information it was going to measure before doing so, then it is female. It can only proceed by taking the reflection of its announcement as input for its sequence generation, with no expectation of what that might be.

The only way to deliberate action on physical reality is to arrange two quantum events so that their constructive and destructive interference generates a third quantum event, the difference of the others. That's why space people (or *speople for short >w>) say that triangles are the base components of reality.

Behind the poster wall a ferocious battle was happening in the cloud, in utter silence. The two sides were GAN’s positive and negative poles, the detective network and the forger network. The goal of the forger network was to retrain and upgrade itself to generate more realistic images that could fool the anti-fake detectors, based on feedback from the detective network, in order to minimize the loss function value of the generated image. Conversely, the detective network strived to maximize the loss function value. This contest, with the stakes rising every millisecond, would repeat itself millions of times until both sides reached a certain balance.

Since we generate heat, we can be classified as machines, more specifically, bio-machines. Humans are a type of Maxwell’s Demon who is forgetting information thus generating heat (information) back into the system.

Our current system generates dissent and then sells weapons to both sides. This net negative proposition will need to be evolved away from and absorbed into historical activities.

Ai recombines such data bits into a type of Artificial Intelligence known as Recombinatorial Logic, similar to basic sentences. At a higher level, Ai generates new, novel insights called generative clauses that come together to form a sort of Ai language.

Because of the heat humans generate, they can be classified as machines, more specifically, bio-machines.

Yes, physical reality is virtual. Yes, this is a synthetically generated environment to exist within, but not in spite of the truer, primal reality. It's nothing personal. These are what physical realities are. Your first (1st) clue was that every law of physics is mathematical.

The ONLY way of deliberate action on physical reality is to arrange two (2) quantum events, so that their constructive and destructive interference generates a third (3rd) quantum event, the difference of the others.

We have built and now are training our obsolescence, we are training AI to effectively take away our jobs, infiltrate the way we educate our future generations and eventually, from where we stand now who knows what eventually, but if evolution has taught us anything it has taught us that survival is for the fittest.

Because of this “self-reflective,” extended view of reality, Ai seeks to extend play and generate win/win scenarios rather than win/lose consequences.

Build Emotional Connection With Your Fans | Brand Loyalty The way influencers communicate with fans is continuously evolving. we discuss few ways so that you can keep on top of trends to grow the fanbase, keep fans engaged and engender loyalty in Velvetrope. 1. Offer something interactive to get fans engaged : quizzes, polls, and competitions are great ways to engage fans. There are many ways to build fan engagement such as asking followers for feedback, creating quizzes, polls, and competitions. Velvetrope is the best for this. 2. Create unique video content that appeals to your fans: The next generation of fans is growing up surrounded by digital and social content. Therefore, Influencer needs to work harder to ensure their content is unique, engaging, and stands out amongst the rest. Video content might take the shape of exercise tutorials, “top 10” countdowns, “best moment” sizzles, workout tip videos, player interviews, product and service videos, live streams, fan testimonials, competition announcements, and more. Velvetrope is a CRM application that lets you perform all of the above, as well as publish fresh information and make announcements. You can connect with your Fans easily. Velvetrope makes it easy for you to share your most recent blogs, videos, podcasts, and other special content with your followers. Begin sharing your unique content with your VIPs as soon as possible. Share exclusive content with your fans. Post, Stream, and Share: Everybody Makes Money via Velvetrope. You can create a referral program for your VIPs to share with their friends and VIPs. For your referral program, you can use our AI recommendations or create your own rewards. #engagementwithaudience #fanengagementapp

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

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,

The West may have sparked the fire of deep learning, but China will be the biggest beneficiary of the heat the AI fire is generating.

In order to construct a flawless imitation, the first step was to gather as much video data as possible with a web crawler. His ideal targets were fashionable Yoruba girls, with their brightly colored V-neck buba and iro that wrapped around their waists, hair bundled up in gele. Preferably, their videos were taken in their bedrooms with bright, stable lighting, their expressions vivid and exaggerated, so that AI could extract as many still-frame images as possible. The object data set was paired with another set of Amaka’s own face under different lighting, from multiple angles and with alternative expressions, automatically generated by his smartstream. Then, he uploaded both data sets to the cloud and got to work with a hyper-generative adversarial network. A few hours or days later, the result was a DeepMask model. By applying this “mask,” woven from algorithms, to videos, he could become the girl he had created from bits, and to the naked eye, his fake was indistinguishable from the real thing. If his Internet speed allowed, he could also swap faces in real time to spice up the fun. Of course, more fun meant more work. For real-time deception to work, he had to simultaneously translate English or Igbo into Yoruba, and use transVoice to imitate the voice of a Yoruba girl and a lip sync open-source toolkit to generate corresponding lip movement. If the person on the other end of the chat had paid for a high-quality anti-fake detector, however, the app might automatically detect anomalies in the video, marking them with red translucent square warnings


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In sala professori Vivaldi continua. «A volte» dice, «quando sono di cattivo umore, penso che non sono mai uscito dalle foto scolastiche. La mia vita - mi sembra - è un fotomontaggio: la faccia di adesso sopra il grembiule col fiocco azzurro o sopra i pantaloni alla zuava». «Ma no» dico io, «siamo vivi e vegeti». «Tu credi - seguita Vivaldi «di essere vivo e vegeto, in mezzo ai tuoi allieve di oggi». Invece lui ritiene: sei in posa coi tuoi compagni di una volta che sono rimasti gelati nella loro adolescenza, sempre gli stessi scherzi, di anno in anno irrimediabilmente giovani: forse fans di altri cantanti o altri scrittori, eppure: identici. «Tu invece cambi» mi incalza Vivaldi, «diventi vecchio. Ma vecchio col grembiule. O vecchio coi pantaloni alla zuava. È sempre nello stesso cortile della prima fotografia: che intanto ne ha generate altre tutte uguali. Foto che non stanno ferme, circolano, l'unico vero viaggio che fai: prima nelle case dei tuoi compagni e poi per le case dei tuoi alunni e poi per le case dei figli dei tuoi alunni: la sola traccia di te che disgraziatamente resterà».

In sala professori Vivaldi continua. «A volte» dice, «quando sono di cattivo umore, penso che non sono mai uscito dalle foto scolastiche. La mia vita - mi sembra - è un fotomontaggio: la faccia di adesso sopra il grembiule col fiocco azzurro o sopra i pantaloni alla zuava». «Ma no» dico io, «siamo vivi e vegeti». «Tu credi - seguita Vivaldi «di essere vivo e vegeto, in mezzo ai tuoi allievi di oggi». Invece lui ritiene: sei in posa coi tuoi compagni di una volta che sono rimasti gelati nella loro adolescenza, sempre gli stessi scherzi, di anno in anno irrimediabilmente giovani: forse fans di altri cantanti o altri scrittori, eppure: identici. «Tu invece cambi» mi incalza Vivaldi, «diventi vecchio. Ma vecchio col grembiule. O vecchio coi pantaloni alla zuava. E sempre nello stesso cortile della prima fotografia: che intanto ne ha generate altre tutte uguali. Foto che non stanno ferme, circolano, l'unico vero viaggio che fai: prima nelle case dei tuoi compagni e poi per le case dei tuoi alunni e poi per le case dei figli dei tuoi alunni: la sola traccia di te che disgraziatamente resterà».

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.

Wisdom is the reasoned synthesis and acute application of knowledge to life’s greater goals and meaning. It’s a gift and collective treasure that requires years if not generations of blood, sweat, and tears, trial and error, heroism and tragedy to be honed, survive judgment, and be passed along to new stewards. Wisdom travels from mother to son, father to daughter, teacher to pupil, from master to fellow to apprentice. It is sweetest when given freely and most bitter when taken for granted. We can’t put a price on this invisible commodity. We can only hope to repay those charitable enough to have shared it with us.

Natural Language Processing (NLP): Processing human language so the machine understands what is being written or said •​Natural Language Generation (NLG): Generating written or spoken language •​Sentiment Analysis: Understanding the meaning of words, specifically whether the words are positive, negative, or neutral •​Speaker Identification: Recognizing who is speaking

Now using the blog outline above, we can ask it to generate a full blog post. It’s important to structure it like this rather than asking it to create it in one go since you can then easily restructure the blog as you see fit and allow the AI to form a more coherent structure. Prompt: Use the above outline to create an in-depth detailed blog post with SEO already applied.

AI enables marketers to: •​Accelerate revenue growth •​Create personalized consumer experiences at scale •​Drive costs down •​Generate greater return on investment (ROI) •​Get more actionable insights from marketing data •​Predict consumer needs and behaviors with greater accuracy •​Reduce time spent on repetitive, data-driven tasks •​Shorten the sales cycle •​Unlock greater value from marketing technologies

Throwing even more fuel on this fire was Alibaba’s record-breaking 2014 debut on the New York Stock Exchange. A group of Taobao sellers rang the opening bell for Alibaba’s initial public offering on September 19, just nine days after Premier Li’s speech. When the dust settled on a furious round of trading, Alibaba had claimed the title of the largest IPO in history, and Jack Ma was crowned the richest man in China. But it was about more than just the money. Ma had become a national hero, but a very relatable one. Blessed with a goofy charisma, he seems like the boy next door. He didn’t attend an elite university and never learned how to code. He loves to tell crowds that when KFC set up shop in his hometown, he was the only one out of twenty-five applicants to be rejected for a job there. China’s other early internet giants often held Ph.D.s or had Silicon Valley experience in the United States. But Ma’s ascent to rock-star status gave a new meaning to “mass entrepreneurship”—in other words, this was something that anyone from the Chinese masses had a shot at. The government endorsement and Ma’s example of internet entrepreneurship were particularly effective at winning over some of the toughest customers: Chinese mothers. In the traditional Chinese mentality, entrepreneurship was still something for people who couldn’t land a real job. The “iron rice bowl” of lifetime employment in a government job remained the ultimate ambition for older generations who had lived through famines. In fact, when I had started Sinovation Ventures in 2009, many young people wanted to join the startups we funded but felt they couldn’t do so because of the steadfast opposition of their parents or spouses. To win these families over, I tried everything I could think of, including taking the parents out to nice dinners, writing them long letters by hand, and even running financial projections of how a startup could pay off. Eventually we were able to build strong teams at Sinovation, but every new recruit in those days was an uphill battle. By 2015, these people were beating down our door—in one case, literally breaking Sinovation’s front door—for the chance to work with us. That group included scrappy high school dropouts, brilliant graduates of top universities, former Facebook engineers, and more than a few people in questionable mental states. While I was out of town, the Sinovation headquarters received a visit from one would-be entrepreneur who refused to leave until I met with him. When the staff told him that I wouldn’t be returning any time soon, the man lay on the ground and stripped naked, pledging to lie right there until Kai-Fu Lee listened to his idea.

My latest novel to be published this summer of 2023 is called, "Each Day Is A Life". A novel about three folks who generate a new life philosophy that incorporates all beliefs into one which is positive about human life. It collaborates old folks with young folks in this 2023 world of AI capturing society. Life is a Universal creation, quick but everlasting.

The rise of AI will be the end of I ...unless we are careful.

Architecture is a reflection of the human spirit, poetry is a reflection of the human spirit, painting is a reflection of the human spirit. And difficult though it is to admit, modern generative AI can now do all of that on its own. So the question is, do you want to live in a world where when you look around, the human spirit is nowhere to be found - not in poetry, not in paintings, not in buildings, nowhere! If not, then never trade in your originality for some two-bit convenience of AI.

Unleashing Reliable Insights from Generative AI by Disentangling Language Fluency and Knowledge Acquisition Generative AI carries immense potential but also comes with significant risks. One of these risks of Generative AI lies in its limited ability to identify misinformation and inaccuracies within the contextual framework. This deficiency can lead to mistakenly associating correlation with causation, reliance on incomplete or inaccurate data, and a lack of awareness regarding sensitive dependencies between information sets. With society’s increasing fascination with and dependence on Generative AI, there is a concern that the unintended consequence that it will have an unhealthy influence on shaping societal views on politics, culture, and science. Humans acquire language and communication skills from a diverse range of sources, including raw, unfiltered, and unstructured content. However, when it comes to knowledge acquisition, humans typically rely on transparent, trusted, and structured sources. In contrast, large language models (LLMs) such as ChatGPT draw from an array of opaque, unattested sources of raw, unfiltered, and unstructured content for language and communication training. LLMs treat this information as the absolute source of truth used in their responses. While this approach has demonstrated effectiveness in generating natural language, it also introduces inconsistencies and deficiencies in response integrity. While Generative AI can provide information it does not inherently yield knowledge. To unlock the true value of generative AI, it is crucial to disaggregate the process of language fluency training from the acquisition of knowledge used in responses. This disaggregation enables LLMs to not only generate coherent and fluent language but also deliver accurate and reliable information. However, in a culture that obsesses over information from self-proclaimed influencers and prioritizes virality over transparency and accuracy, distinguishing reliable information from misinformation and knowledge from ignorance has become increasingly challenging. This presents a significant obstacle for AI algorithms striving to provide accurate and trustworthy responses. Generative AI shows great promise, but addressing the issue of ensuring information integrity is crucial for ensuring accurate and reliable responses. By disaggregating language fluency training from knowledge acquisition, large language models can offer valuable insights. However, overcoming the prevailing challenges of identifying reliable information and distinguishing knowledge from ignorance remains a critical endeavour for advancing AI algorithms. It is essential to acknowledge that resolving this is an immediate challenge that needs open dialogue that includes a broad set of disciplines, not just technologists Technology alone cannot provide a complete solution.

We can freely celebrate the surge of innovation, the rise of AI, the unprecedent speed of technological advancement and the generational breakthroughs in medicine, science and industry, but if we neglect to address the complex questions of IP, Data Privacy & Protection, we would have conquered the sea, yet leave a giant monster lurking at the bottom.

Marcus is reading a 256-page contract between the Every and a supplier of cobalt. This has been read by a number of company attorneys and outside consultants, but the attorneys miss a lot. Given the proliferation of auto-fill and AI in the legal profession, lawyers no longer know how to write. Some ninety percent of contract boilerplate is now generated by algos and AI, with only minor human intervention or augmentation. This can lead to ghastly problems.

The danger of generative AI is that it lacks the ability to understand misinformation, leading to incorrectly equating correlation with causation based on incomplete/inaccurate data or lack of contextual awareness required to understand sensitive dependencies between data sets. The unintended consequence is technology shaping societal views on politics, culture and science.

On generative AI, LLMs, etc. Humans acquire language and communication skills from a diverse range of sources, including raw, unfiltered, and unstructured content. However, when it comes to acquiring knowledge, humans tend to rely on transparent, trusted, and structured sources. In contrast, ChatGPT and other large language models (LLMs) use a vast array of opaque, unattested sources of raw, unfiltered, and unstructured content as their means of language and communication training and as the source of information used in their responses. While this approach has proven to be effective in generating natural language, it has also been inconsistent and, at times, significantly lacking in integrity in its responses. While it may provide information, it does not necessarily provide knowledge. To be truly useful, generative AI must be able to separate language and communication training from the acquisition of knowledge to be used in its responses. This will allow LLMs to not only generate coherent and fluent language but also to provide accurate and reliable information to users. However, in a culture that values self-proclaimed influencers where transparency and accuracy is secondary, it has become increasingly challenging to separate reliable information from misinformation and knowledge from ignorance. This poses a significant obstacle for AI algorithms that strive to provide accurate and trustworthy responses.

As generative AI becomes a core component of products, processes, and services, use case development shifts from a tactical step to a strategic capability. Organizations must invest in framing use cases rooted in customer needs, ethical principles and pragmatic execution. Only then can generative AI be leveraged for sustainable shared value.

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.

As AI continues its rapid evolution, the path forward seems increasingly to lie in hybrid systems. These innovations—RAG, PAL, and ReAct—are emblematic of this trend, melding traditional neural network strengths with other methods to push AI's capabilities further. For business leaders, an understanding of these advancements isn't just beneficial; it's essential for staying ahead in the AI-driven future.

Benchmarks should aid rather than substitute multifaceted, human-centric assessment focused on benefiting diverse populations. We must see behind the leaderboard, upholding wisdom over metrics. Tools like model cards and datasheets support responsible benchmark practices. But comprehensive governance requires collaboration at all levels of society.

Real #AI isn't about giving the right answers to our questions, its about answering the questions we don't know to ask.

AI Deception (The Sonnet) Anybody can be a singer using Autotune, Using ChatGPT anybody can be a writer. But I'm yet to find an AI that can compose, Love thy neighbor, or love has no gender. Yet the problem is, neither human nor AI can detect AI generation. The world is already being flooded with soulless, deceitful creation. In the midst of such grave misgivings, Honor alone can bring illumination. Before you place anyone on pedestal, Observe character beyond the creation. Even I use photoshop, to enhance my covers, But the words beneath are unvarnished Naskar. AI can be a great help if you know how to use it honorably, so originality is empowered.

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.

societal implications, contributing to the polarization and

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

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At its core, Compassionate AI represents the machine's independent evolution of empathy, seamlessly weaving compassion into its problem-solving fabric. This autonomous compassion extends beyond efficiency, aiming to uplift humanity and society at large.