The release of ChatGPT by OpenAI in November 2022 marked another significant milestone in the evolution of AI. ChatGPT, a large language model capable of generating human-like text, demonstrated the potential of AI to understand and generate natural language. This capability opened up new possibilities for AI applications, from customer service to content creation. The world responded to ChatGPT with a mix of awe and excitement, recognizing the potential of AI to transform how humans communicate and interact with technology to enhance our lives. Today, the rise of agentic AI -- systems capable of advanced reasoning and task execution -- is revolutionizing the way organizations operate.

Throughout history many traditions have believed that some fatal flaw in human nature tempts us to pursue powers we don't know how to handle. The Greek myth of Phaethon told of a boy who discovers that he is the son of Helios, the sun god. Wishing to prove his divine origin, Phaethon demands the privilege of driving the chariot of the sun. Helios warns Phaethon that no human can control the celestial horses that pull the solar chariot. But Phaethon insists, until the sun god relents. After rising proudly in the sky, Phaethon indeed loses control of the chariot. The sun veers off course, scorching all vegetation, killing numerous beings and threatening to burn the Earth itself. The gods reassert control of the sky and save the world. Two thousand years later, when the Industrial Revolution was making its first steps and machines began replacing humans in numerous tasks, Johann Wolfgang von Goethe published a similar cautionary tale titled The Sorcerer's Apprentice. Goethe's poem (later popularised as a Walt Disney animation starring Mickey Mouse) tells of an old sorcerer who leaves a young apprentice in charge of his workshop and gives him some chores to tend to while he is gone, such as fetching water from the river. The apprentice decides to make things easier for himself and, using one of the sorcerer's spells, enchants a broom to fetch the water for him.

Several years before ChatGPT began jibber-jabbering away, Google developed a very different kind of artificial intelligence program called AlphaGo that learned to play the board game Go with superhuman skill through tireless practice. Researchers at the company have now published research that combines the abilities of a large language model (the AI behind today's chatbots) with those of AlphaZero, a successor to AlphaGo also capable of playing chess, to solve very tricky mathematical proofs. Their new Frankensteinian creation, dubbed AlphaProof, has demonstrated its prowess by tackling several problems from the 2024 International Math Olympiad (IMO), a prestigious competition for high school students. AlphaProof uses the Gemini large language model to convert naturally phrased math questions into a programming language called Lean. This provides the training fodder for a second algorithm to learn, through trial and error, how to find proofs that can be confirmed as correct.

In 2016, an artificial intelligence program called AlphaGo from Google's DeepMind AI lab made history by defeating a champion player of the board game Go. Now Demis Hassabis, DeepMind's cofounder and CEO, says his engineers are using techniques from AlphaGo to make an AI system dubbed Gemini that will be more capable than that behind OpenAI's ChatGPT. DeepMind's Gemini, which is still in development, is a large language model that works with text and is similar in nature to GPT-4, which powers ChatGPT. But Hassabis says his team will combine that technology with techniques used in AlphaGo, aiming to give the system new capabilities such as planning or the ability to solve problems. "At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models," Hassabis says.

The technology that underpins ChatGPT has the potential to do much more than just talk. Linxi "Jim" Fan, an AI researcher at the chipmaker Nvidia, worked with some colleagues to devise a way to set the powerful language model GPT-4--the "brains" behind ChatGPT and a growing number of other apps and services--loose inside the blocky video game Minecraft. The Nvidia team, which included Anima Anandkumar, the company's director of machine learning and a professor at Caltech, created a Minecraft bot called Voyager that uses GPT-4 to solve problems inside the game. The language model generates objectives that help the agent explore the game, and code that improves the bot's skill at the game over time. Voyager doesn't play the game like a person, but it can read the state of the game directly, via an API.

Last fall, when generative AI abruptly started turning out competent high-school- and college-level writing, some educators saw it as an opportunity. Perhaps it was time, at last, to dispose of the five-paragraph essay, among other bad teaching practices that have lingered for generations. Universities and colleges convened emergency town halls before winter terms began to discuss how large language models might reshape their work, for better and worse. But just as quickly, most of those efforts evaporated into the reality of normal life. Educators and administrators have so many problems to address even before AI enters the picture; the prospect of utterly redesigning writing education and assessment felt impossible.

In 2016 a computer named AlphaGo made headlines for defeating then world champion Lee Sedol at the ancient, popular strategy game Go. The "superhuman" artificial intelligence, developed by Google DeepMind, lost only one of the five rounds to Sedol, generating comparisons to Garry Kasparov's 1997 chess loss to IBM's Deep Blue. Go, which involves players facing off by moving black and white pieces called stones with the goal of occupying territory on the game board, had been viewed as a more intractable challenge to a machine opponent than chess. Much agonizing about the threat of AI to human ingenuity and livelihood followed AlphaGo's victory, not unlike what's happening right now with ChatGPT and its kin. In a 2016 news conference after the loss, though, a subdued Sedol offered a comment with a kernel of positivity.

Earlier this year, an amateur Go player decisively defeated one of the game's top-ranked AI systems. They did so using a strategy developed with the help of a program researchers designed to probe systems like KataGo for weaknesses. It turns out that victory is just one part of a broader Go renaissance that is seeing human players become more creative since AlphaGO's milestone victory in 2016 In a recent study published in the journal PNAS, researchers from the City University of Hong Kong and Yale found that human Go players have become less predictable in recent years. As the New Scientist explains, the researchers came to that conclusion by analyzing a dataset of more than 5.8 million Go moves made during professional play between 1950 and 2021. With the help of a "superhuman" Go AI, a program that can play the game and grade the quality of any single move, they created a statistic called a "decision quality index," or DQI for short.

AIs can beat the world's best players at the board game Go but humans are starting to improve too. An analysis of millions of Go moves has found that professional players have been making better and more original game choices since Go-playing AIs overtook humans. Before 2016, AIs couldn't beat the world's best Go players. But this changed with an AI called AlphaGo developed by London-based research firm DeepMind. AlphaGo defeated multiple Go champions, including the then number one ranked human player.

The smartest AI is a highly debated topic and can be defined in various ways depending on the context. However, some of the most advanced and widely recognized AI systems that are considered to be the "smartest" include: Watson is an AI system that was developed by IBM and is known for its ability to understand and respond to natural language. It uses machine learning algorithms and natural language processing to analyze and interpret large amounts of data, making it a powerful tool for businesses and researchers. Watson has been used in various applications such as medical diagnosis, financial analysis, and even in the game show Jeopardy! AlphaGo is an AI system developed by Google's DeepMind that is able to play the complex game of Go at a professional level.