Every three months, participants in the Metaculus forecasting cup try to predict the future for a prize pot of about $5,000. Metaculus, a forecasting platform, poses questions of geopolitical importance such as " Will Thailand experience a military coup before September 2025?" and " Will Israel strike the Iranian military again before September 2025?" Forecasters estimate the probabilities of the events occurring--a more informative guess than a simple "yes" or "no"--weeks to months in advance, often with remarkable accuracy. Metaculus users correctly predicted the date of the Russian invasion of Ukraine two weeks in advance and put a 90 percent chance of Roe v. Wade being overturned almost two months before it happened. Still, one of the top 10 finishers in the Summer Cup, whose winners were announced Wednesday, was surprising even to the forecasters: an AI. "It's actually kind of mind blowing," says Toby Shevlane, CEO of Mantic, the recently-announced UK-based startup that developed the AI.

Jeopardy! champion Emma Boettcher's Master's paper on using text mining to predict how hard a Jeopardy!

Since the earliest days of virtual chess and solitaire, video games have been a playing field for developing artificial intelligence (AI). Each victory of machine against human has helped make algorithms smarter and more efficient. But in order to tackle real world problems – such as automating complex tasks including driving and negotiation – these algorithms must navigate more complex environments than board games, and learn teamwork. Teaching AI how to work and interact with other players to succeed had been an insurmountable task – until now.

Since the earliest days of virtual chess and solitaire, video games have been a playing field for developing artificial intelligence (AI). Each victory of machine against human has helped make algorithms smarter and more efficient. But in order to tackle real world problems – such as automating complex tasks including driving and negotiation – these algorithms must navigate more complex environments than board games, and learn teamwork. Teaching AI how to work and interact with other players to succeed had been an insurmountable task – until now. In a new study, researchers detailed a way to train AI algorithms to reach human levels of performance in a popular 3D multiplayer game – a modified version of Quake III Arena in Capture the Flag mode.

Artificial Intelligence There is a constant battle in human's curiosity to check out if we can defeat computers. Due to that, people are creating different games to play against the robot. After chess, Jeopardy or even soccer, humans decided to test robots in one of the most interesting game tables – foosball. The idea to create a foosball table you can play against robot was born on the Swiss École polytechnique fédérale de Lausanne as a part of their education. When you look at that table, it looks like an average foosball table, with a pretty sleek design.

Elon Musk, CEO of Tesla was recently quoted saying: "There will be fewer and fewer jobs a robot cannot do better." In his impassioned speech he asked what meaning humans will have without jobs. This follows others including Stephen Hawking, Bill Gates and Mark Carney, Governor of the Bank of England, who have made comments on the dangers of robotics and AI "destroying jobs". Musk argued that if humans want to add value, they should embrace a "merger of biological intelligence and machine intelligence". Although this might sound like a sci-fi movie in the works, Musk's suggestions really do extend to the symbiosis of man and machine.

If there's one thing that humanity used to be able to hang its hat on in the war against our future computer overlords, it's that we could definitely beat the machines in a good old fashioned game of Doom. Now, however, it appears that even that accomplishment is another hubris of humanity. Two students at Carnegie Mellon University have designed an artificial intelligence program that is capable of beating human players in a deathmatch game of 1993's Doom. Guillaume Lample and Devendra Singh Chaplot spent four months developing a program capable of playing first-person shooter games. The program made its debut at VizDoom (an AI competition that centered around the classic shooter) where it took second place despite the fact that their creation managed to beat human participants.

"Really, the only game left after chess is Go," was how Demis Hassabis set the scene ahead of AlphaGo's match with world champion Lee Sedol earlier this month. Either Hassabis's copy of the latest Street Fighter didn't get delivered on time, or he was trying to be a little poetic to mark the occasion. Either way, you'd be forgiven for thinking there really were no games left to conquer after the media reaction to AlphaGo winning the first three games in a best-of-five against its human opponent. It's been a curious month to be an AI researcher. Watching the contest, which AlphaGo eventually won 4-1, I've learned a lot about Go and one of the most interesting things is how the spaces left empty on the board can often be as important and meaningful as the spaces where stones are played.