The new sci-fi drama from Vince Gilligan posits an end-of-humanity scenario that everyone other than its protagonist can agree on. Even before her fellow-humans' contamination, Carol didn't seem to have much use for them. On the night that the world as we know it is destroyed, a novelist named Carol Sturka (played by Rhea Seehorn) sees cars and planes veer off course, an emergency room full of convulsing bodies, and her city, Albuquerque, on fire. The President dies under mysterious circumstances, and, more devastatingly for Carol, so does her live-in partner, Helen (Miriam Shor). Then, in less than an hour, the apocalypse cleans up after itself.

The narrowness of AI will someday be replaced by artificial general intelligence. But will it have the capability to rival human intelligence and creativity? Some of the world's most advanced artificial intelligence (AI) systems, at least the ones the public hear about, are famous for beating human players at chess or poker. Other algorithms are known for their ability to learn how to recognize cats or their inability to recognize people with darker skin. But are current AI systems anything more than toys?

Some of the world's most advanced artificial intelligence (AI) systems, at least the ones the public hear about, are famous for beating human players at chess or poker. Other algorithms are known for their ability to learn how to recognize cats or their inability to recognize people with darker skin. But are current AI systems anything more than toys? Sure, their ability to play games or identify animals is impressive, but does this help toward creating useful AI systems? To answer this, we need to take a step back and question what the goals of AI are.

Computers are solving problems no human could ever decode -- and in ways that feel distinctly nonhuman to us. Should we embrace or rethink the strange intelligence of machines?In 2019, five of the top poker players in the world sat down in a casino to play poker against a computer. Over the course of the game they lost big -- some $1.7 million (E1.77 million) -- to a poker bot called Pluribus. It was the first time an artificial-intelligence (AI) program beat elite human players at a game of more than two players. In a post-game interview, the players were asked how they felt about losing to a computer.

In 2019, five of the top poker players in the world sat down in a casino to play poker against a computer. Over the course of the game they lost big -- some $1.7 million (€1.77 million) -- to a poker bot called Pluribus. It was the first time an artificial-intelligence (AI) program beat elite human players at a game of more than two players. In a post-game interview, the players were asked how they felt about losing to a computer. Pluribus, they said, ʺbluffed really well.

ARTIFICIAL intelligence systems have mastered some of mankind's best creations and natural intuitions. These AI systems notched some of the first wins for the machines. Artificial intelligence and table games make a good pair because humans have been trying to develop perfect tactics for strategy games for decades or even centuries. Chess is "known as a game that requires strategy, foresight, logic--all sorts of qualities that make up human intelligence," IBM researcher Murray Campbell told Scientific American. Campbell and a team developed Deep Blue, a six-foot supercomputer that defeated chess grandmaster Garry Kasparov in a six-game series in 1997.

AI systems reached superhuman performance in 2 player, zero-sum games (where one player wins, the other loses) such as Chess, Checkers, Go, and two-player poker. Now, an AI called Pluribus is capable of defeating elite poker players in 6 player, no-limit Texas Hold'em Poker, the most common game format. Poker elegantly captures the challenges of hidden information games. There are too many decision points to navigate individually, so, some actions are disregarded, and similar decisions are bucketed together in a simplification process called abstraction. AI systems that win in zero-sum games approximate the Nash equilibrium strategies and generate moves accordingly.

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Poker has been considered by many the core inspiration for the formalization of game theory. John von Neuman was reportedly an avid poker fan and use many analogies of the card game while creating the foundation of game-theory.

The 32-year-old is the only person to have won four World Poker Tour titles and has earned more than $7 million at tournaments. Despite his expertise, he learned something new this spring from an artificial intelligence bot. Elias was helping test new soft ware from researchers at Carnegie Mellon University and Facebook. He and another pro, Chris "Jesus" Ferguson, each played 5,000 hands over the internet in six-way games against five copies of a bot called Pluribus. At the end, the bot was ahead by a good margin.

From beating humans at poker games to predicting weather forecasts, AI technology is making great strides in present times However, it is by no means clear yet whether this will project as a game-changer in the world ahead. Computer programmers have been trying hard to find the right and relevant pattern in data just to be sure they become extremely good at beating multiplayer games. Perhaps they’re already on it. A whitepaper published by researchers at Facebook and Carnegie Mellon University said their software is good at embracing randomness and that it is reliable to beat humans at games. This