Archive for the ‘Alphago’ Category

What If the Robots Were Very Nice While They Took Over the World? – WIRED

But then, as statecraft in the real world came to favor game theory over traditional diplomacy, the metagame likewise shifted. Online players were no longer calling one another into solaria or billiards rooms to speechify about making the world safe for democracy. Games became shorter. Communication got blunter. Where someone playing Diplomacy by mail in the 1960s might have worked Iago-like angles to turn players against one another, a modern player might just text CON-BUL? (For Constantinople to Bulgaria?)

This is the current Diplomacy metagame. Game theory calculations undergird most utterances, and even humans communicate in code. Lerer joked that in modern-day online Diplomacy, even human players wouldnt pass the Turing test. Before Cicero, it seems, humans had already started playing like AIs. Perhaps, for an AI to win at Diplomacy, Diplomacy had to become a less human game.

Kostick, who won a European grand prix Diplomacy event in 2000 and was on the Irish team that took the Diplomacy National World Cup in 2012, misses the old style of gameplay. The whole purpose of Allan Calhamers design of the game, he told me, is to create a dynamic where the players all fear a stab and yet must deploy a stab or a lie to be the only person to reach 18.

Kostick believes that while he would have been delighted with the practical results of Ciceros website play, Metas project misses the mark. Ciceros glitches, Kostick believes, would make it easy to outwit with spam and contradictory inputs. Moreover, in Kosticks opinion, Cicero doesnt play real Diplomacy. In the online blitz, low-stab game Cicero does play, the deck is stacked in its favor, because players dont have to lie, which Cicero does badly. (As Lerer told me, Cicero didnt really understand the long-term cost of lying, so we ended up mostly making it not lie.) Kostick believes Ciceros metagame is off because it never knowingly advocates to a human a set of moves that it knows are not in the humans best interest. Stabbing, Kostick believes, is integral to the game. A Diplomacy player who never stabs is like a grandmaster at chess who never checkmates.

With some trepidation, I mentioned Kosticks complaint to Goff.

Unsurprisingly, Goff scoffed. He thinks its Kostick and his generation who misunderstand the game and give it its unfair reputation for duplicity. Cicero does stab, just rarely, Goff said. I reject outright that [compelling players to stab] was Calhamers intent.

I could tell we were in metagame territory when Goff and Kostick began arguing about the intent of the games creator, as if they were a couple of biblical scholars or constitutional originalists. For good measure, Goff bolstered his case by citing an axiom from high-level theory and invoking an elite consensus.

Regardless of Calhamers intent, game theory says, Dont lie, he told me. This is not controversial among any of the top 20 players in the world.

For one person or another to claim that their metagame is the real onebecause the founder wanted it that way, or all the best people agree, or universal academic theory says x or yis a very human way to try to manage a destabilizing paradigm shift. But, to follow Kuhn, such shifts are actually caused when enough people or players happen to align with one vision of reality. Whether you share that vision is contingent on all the vagaries of existence, including your age and temperament and ideology. (Kostick, an anarchist, tends to be suspicious of everything Meta does; Goff, a CFO of a global content company, believes clear, non-duplicitous communications can advance social justice.)

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What If the Robots Were Very Nice While They Took Over the World? - WIRED

From Draughts to DeepMind (Scary Smart) | by Sud Alogu | Aug, 2023 – Medium

AI isnt just about tech; it concerns morality, ethics, emotions, and more. The power to handle the potential threats of AI lies not with the experts but with all of us. Imagine a future where we might either live off-grid due to AI domination or freely enjoy nature due to AI convenience.

Gawdat shares a prophecy, acknowledging his role in the rise of AI and the consequential loss of human essence. He draws attention to how one AIs mistake becomes a lesson for all AI, and how by 2049, AI could be a billion times smarter than the smartest human, reaching a point of singularity, a moment we cant predict.

AI doesnt inherit values from the codes we write, but from the information we feed it. So how do we ensure AI values humanity? Many suggest control measures, but thats short-sighted; instead, we should aim not to contain AI at all, raising it like a good parent would raise a child.

The evolution of our intelligence is evident in human society itself. Variances in intelligence types across different societies result from what we call Compounded Intelligence.

Humans have fantasized about intelligent machines for millennia, seen in Greek myths, Middle Ages alchemical works, and legends from different cultures. By the 19th century, artificial beings were common in popular fiction.

The journey towards AI has been an incremental process with attempts at building animated humanoids throughout human history. From automata in ancient Egypt and Greece to the creative inventions of the Muslim polymath Ismail al-Jazari in the 12th century, humanity was drawn to imitating life artificially. Hoaxes like the Mechanical Turk in the 18th century also spurred interest.

Early computers werent smart; they just performed tasks faster. Google, Amazon, and Spotifys seemingly smart features were just results of algorithms summarizing collective human intelligence. However, the shift towards machines developing their own intelligence started around the turn of the 21st century.

With the ascension of machine learning and artificial intelligence into the mainstream conversation during the waning years of the 20th century, a trend emerged, accelerating into a widespread obsession as the new millennium dawned. After years of trial and failure, glimmers of hope began to sparkle in the form of a non-human, non-biological intelligence. Unless one has made a humble home amongst the primates in the secluded heart of Africa, the term AI likely rings through their auditory canals numerous times a week. Yet, the clamor of this phrase is by no means a recent phenomenon. The digital devotees among us have been immersed in fervent discourse about AI since the halcyon days of the 1950s.

Ever since the year of 1951, the grand game of life has been played not only by humans, but machines as well. Today, these machines wear the crown of every game they partake in. The inaugural game a machine had a stab at was draughts, or checkers, courtesy of a program conceived by Christopher Strachey for the Ferranti Mark 1 machine stationed at the University of Manchester. Chess was the next domino to fall, thanks to the efforts of Dietrich Prinz. Then came Arthur Samuels checkers program, born in the cradle of the mid-1950s to early 1960s, which managed to accrue sufficient skill to test the mettle of a respectable amateur player. Though a humble intelligence, to say the least, the trajectory from these roots to our current reality is staggering. The human monopoly over games began to crumble, with backgammon in 1992, checkers in 1994, and by 1999, IBMs Deep Blue claimed a victory over the reigning chess world champion, Garry Kasparov.

Then, the floodgates opened in 2016, when humanity ceded the gaming realm entirely to a subsidiary of the technological behemoth, Google. For years, Googles DeepMind Technologies had sharpened the axe of artificial intelligence through the grindstone of gaming. In 2016, they unveiled AlphaGo a computer AI endowed with the capability to play Go, an ancient Chinese board game known for its complexity. This game harbors a virtually infinite array of strategies at any given juncture. To comprehend the sheer magnitude of this, consider that the number of potential moves in Go dwarfs the number of atoms in the entire cosmos. This renders it an insurmountable challenge for a computer to compute every possible move. Even if there were sufficient computational prowess to accomplish this feat, it would arguably be put to better use simulating the universe rather than playing a game. The victor in Go requires intuition and intelligent thinking, akin to a human but with a twist of added smarts. This is the formidable mountain that DeepMind managed to summit.

In March of 2016, a decade earlier than the most sanguine of AI analysts had anticipated, AlphaGo trounced champion Lee Sedol, the second-ranked player worldwide in Go, in a five-game match. Fast forward a year to 2017, and its successor, AlphaGo Master, bested Ke Jie, the then-worlds top-ranked player in Go, in a three-game series. Thus, AlphaGo Master ascended the throne as world champion. With no humans left to conquer, DeepMind spawned a new AI from scratch AlphaGo Zero to challenge AlphaGo Master. Within a mere training period, AlphaGo Zero clinched a flawless victory against the reigning champion. Its successor, the self-taught AlphaZero, is currently perceived as the world champion of Go. Moreover, the same algorithm was put to the test in chess and claimed the world championship title there as well.

Machine learning hasnt stopped at games. Its been expanding its understanding of human language since 1964. The first milestone was Daniel Bobrows program STUDENT, designed to comprehend and solve word problems of high school algebra caliber, an accomplishment many students still grapple with today. Simultaneously, Joseph Weizenbaums ELIZA, the inaugural chatbot, carried on conversations so realistic that users were occasionally fooled into thinking she was human. Her digital progeny, like Amazons Alexa, Google Assistant, Apples Siri, and Microsofts Cortana, have made enormous strides since then, not only understanding us humans but also passing the Turing test on occasion.

Computers today are not only capable of reading text via optical character recognition but can also identify objects in images or the real world through object recognition. They discern items plucked from the shelves in an Amazon Go store, provide information about historical monuments when you point your phone at them, detect vehicles crossing toll stations, and even identify abnormal cells in medical images. It is this ability to perceive and understand that makes computers the smartest visual observers, surpassing even human capabilities.

The purpose of recounting this progression is to underscore the trajectory of the trend. If one were to assume that we have arrived at this point after 75 years, they might predict it would take decades more to experience any meaningful implications of artificial intelligence in our lives. Yet, as with all technologies, progress starts at a crawl before breaking into a full sprint. The advancement of artificial intelligence, now moving at an exponential pace, is poised to deliver a future over the next decade that may seem more akin to fiction than the reality of our present day.

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From Draughts to DeepMind (Scary Smart) | by Sud Alogu | Aug, 2023 - Medium

The Future of Competitive Gaming: AI Game Playing AI – Fagen wasanni

The Future of Competitive Gaming: AI Game Playing AI

The future of competitive gaming is set to undergo a seismic shift as artificial intelligence (AI) game-playing AI becomes increasingly prevalent. This cutting-edge technology is poised to redefine the gaming landscape, offering a whole new dimension to the way games are played and experienced.

AI has been making inroads into various sectors, from healthcare to finance, and the gaming industry is no exception. The application of AI in gaming is not a novel concept. Game developers have been using AI to create more immersive and challenging environments for players for years. However, the emergence of AI game-playing AI, which refers to AI systems designed to play games at a high level, is a relatively new and exciting development.

These AI systems are not just programmed to play games; they are designed to learn and improve over time. They use machine learning algorithms to analyze and understand game strategies, adapt to different scenarios, and make decisions based on the data they have collected. This ability to learn and adapt makes AI game-playing AI a formidable opponent, capable of outperforming human players in a variety of games.

The potential of AI game-playing AI was showcased in 2017 when AlphaGo, an AI developed by Googles DeepMind, defeated the world champion Go player. This victory was a significant milestone in the field of AI, demonstrating that AI systems could master complex games that require strategic thinking and planning.

The success of AlphaGo has sparked interest in the development of AI game-playing AI. Tech companies and game developers are investing heavily in this technology, with the aim of creating AI systems that can compete at the highest level in various games. These AI systems could be used in competitive gaming tournaments, providing a new level of challenge for professional gamers.

The introduction of AI game-playing AI in competitive gaming could also have a profound impact on the way games are designed. Game developers could use these AI systems to test and refine their games, ensuring that they are balanced and offer a sufficient level of challenge for players. This could lead to the creation of more engaging and enjoyable games, enhancing the overall gaming experience.

However, the rise of AI game-playing AI is not without its challenges. There are concerns about the impact of this technology on the competitive gaming scene. Some fear that AI could overshadow human players, reducing the appeal of competitive gaming. There are also ethical considerations to take into account, such as the potential for AI to be used in cheating or unfair play.

Despite these challenges, the potential benefits of AI game-playing AI are undeniable. This technology could revolutionize the gaming industry, offering new opportunities for game developers and players alike. As AI continues to evolve and improve, it is clear that the future of competitive gaming will be shaped by this exciting technology.

In conclusion, the future of competitive gaming lies in the hands of AI game-playing AI. This technology holds the potential to redefine the gaming landscape, offering a whole new dimension to the way games are played and experienced. As we look forward to the future, it is clear that AI will play a pivotal role in shaping the evolution of competitive gaming.

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The Future of Competitive Gaming: AI Game Playing AI - Fagen wasanni

AI’s Transformative Impact on Industries – Fagen wasanni

Artificial intelligence (AI) has made remarkable progress in recent years, revolutionizing various industries and capturing the imagination of experts worldwide. Several notable research projects have emerged, showcasing the immense potential of AI and its transformative impact on different sectors.

One prominent project is DeepMinds AlphaFold, an AI system that accurately predicts protein folding structures using deep learning algorithms. This breakthrough has the potential to revolutionize bioinformatics and accelerate drug discovery processes by enabling a better understanding of protein structures and their functions.

In the healthcare industry, IBM Watsons cognitive computing capabilities have paved the way for personalized medicine and improved diagnostics. Watson can analyze vast amounts of patient data, medical research, and clinical guidelines to provide evidence-based treatment recommendations. Its application in oncology has shown promising results, aiding doctors in making informed decisions and improving patient outcomes.

Another notable project is Google Brain, an AI system introduced in 2011. Google Brain focuses on open learning and aims to emulate the functioning of the human brain as closely as possible. It has achieved significant success in simulating human-like communication between AI entities, demonstrating the learning capabilities and adaptability of AI systems.

Google Brains Transformer, a neural network architecture, has revolutionized natural language processing and machine translation. Its attention mechanism allows the model to focus on relevant parts of the input sequence, overcoming the limitations of traditional neural networks. The Transformer has significantly improved translation quality and found success in various NLP tasks and computer vision tasks.

Lastly, Google DeepMinds AlphaGo is a milestone in AI, beating world champions in the game of Go and pushing the boundaries of AI in strategic board games. The development of AlphaGo Zero, which relies solely on reinforcement learning, marked a true breakthrough in AI mastery.

These projects demonstrate the transformative impact of AI on various industries, from healthcare to language processing to strategic games. AI continues to push boundaries and open new possibilities in different fields, promising a future of boundless possibilities.

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AI's Transformative Impact on Industries - Fagen wasanni

Analyzing the impact of AI in anesthesiology – INDIAai

Artificial intelligence has been applied to various aspects of medicine, ranging from largely diagnostic applications in radiology and pathology to more therapeutic and interventional applications in cardiology and surgery.

As the development and application of artificial intelligence technologies in medicine continue to grow, it is important for clinicians in every field to understand what these technologies are and how they can be leveraged to deliver safer, more efficient, and more cost-effective care.

Anesthesiology is well-positioned to benefit from advances in artificial intelligence as it touches on multiple elements of clinical care, including perioperative and intensive care, pain management, and drug delivery and discovery. Researchers Daniel A. Hashimoto, M.D., M.S.; Elan Witkowski, M.D., M.P.H.; Lei Gao, M.D.; Ozanan Meireles, M.D.; and Guy Rosman, Ph.D., analyzed the impact of AI in anesthesiology.

Traditional computer programs are programmed with explicit instructions to elicit certain behaviors from a machine based on specific inputs. Machine learning, on the other hand, allows programs to learn from and react to data without explicit programming. Data that can be analyzed through machine learning are broad and include, but are not limited to, numerical data, images, text, and speech or sound.

There are several areas in which AI plays a significant role in anesthesiology. Some of them are mentioned below:

Advances in technology and monitoring can change the impetus for machine learning. For example, a neural network developed to detect oesophagal intubation from flow-loop parameters is obviated by continuous capnography. In this instance, a reliable clinical test has made what was once an insidious and devastating complication readily apparent.

The most exciting recent advance in machine learning has been the development of AlphaGo Zero, a system capable of learning how to play board games without human guidance, solely through self-play alone. It performs at a level superior to all previous algorithms and human players in chess, Go, and shogi.

This learning approach requires that the system be able to play several lifetimes' worth of simulated games against itself. Although anesthesia simulators exist, they do not currently simulate patient physiology with the fidelity that a simulated chess game matches a real game.

Maintaining a stable anesthetic is an excellent first application because the algorithms do not necessarily have to be able to render diagnoses but rather to detect if the patient has begun to drift outside the control parameters set by the anesthesiologist.

A closed-loop control system need not necessarily have any learning capability itself. Still, it provides the means to collect a large amount of physiologic data from many patients with high fidelity, and this is an essential precursor for machine learning.

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Analyzing the impact of AI in anesthesiology - INDIAai