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1. The Deep Blue computer is a better chess-player since 1997

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2017: The year AI beat us at all our own games

Contemplate the transience of all things. Then email us at Mail at CardsAgainstHumanity dot com. What is Cards Against Humanity? Make your own deck for free. Provided with the same inputs as any human player the AI figured out how to play, and win, many of the games.

11 Times AI Beat Humans at Games, Art, Law and Everything in Between

Some games proved harder than others for the AI to master though, and the classic, but notoriously difficult, s video game Ms Pac-Man was especially challenging. In , a deep learning startup called Maluuba was acquired by Google and incorporated into the DeepMind group. Applying this method to Ms Pac-Man the system created more than individual agents, each tasked with specific goals — such as finding a specific pellet, or avoiding ghosts.

The HRA method generates a top agent, something akin to a senior manager. This top agent evaluates all the suggestions from the lower agents before making the final decision on an individual move. The approach has been euphemistically dubbed "divide-and-conquer," where a complex task is broken up into smaller parts. After applying the method to Ms Pac-Man the AI quickly figured out how to achieve a top score of ,, which no human or AI has managed to achieve previously.

A researcher from the University of Falmouth recently revealed a machine learning algorithm that he claims can dream up its own games for us to play from scratch. Called Angelina, this AI system is improving itself from day to day but can currently make games using datasets it scrapes from sources as varied as Wikimedia Commons to online newspapers and social media. Perhaps the most significant, and potentially frightening, development of has been the dramatic progress of reinforcement learning systems.

These programs can efficiently teach themselves how to master new skills. The most recent AlphaZero iteration, for example, can achieve superhuman skills at some games after just a few days of self-directed learning. A large survey of more than AI researchers suggested it won't be too long before AI can beat us as pretty much everything. The survey predicted that within 10 years AI will drive better than us, by it will be able to write a best-selling novel, and by it will perform better than humans at surgery.

In fact, the survey concluded that there is a 50 percent chance that by AI will essentially be able to do everything we can do, but better. Many of these AI-development companies are quickly turning their sights on real-world challenges. Google DeepMind has already moved the AlphaGo Zero system away from the game and onto a comprehensive study of protein folding in the hopes of revealing a treatment for diseases such as Alzheimer's and Parkinson's.

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Chess was only the beginning in the realm of computers beating humans at games. After a grueling day marathon, the machine has comprehensively thrashed all four professional poker players Credit: The International is a giant eSports competition with millions of dollars in prize money Credit: AI beat us at a bunch of games in and it looks like it's something we'll have to get used to Credit: Elon Musk's AI experiment.

Divide and conquer - The Pac-Man challenge.

11 Times AI Beat Humans at Games, Art, Law and Everything in Between

AI will soon make the games. What is the next logical step if AI can beat us in almost every game out there? So what does all this mean? Chess was only the beginning in the realm of computers beating humans at games DeepMind's AlphaGo Master AI comprehensively beat the world Go champion across three matches in Credit: DeepMind After a grueling day marathon, the machine has comprehensively thrashed all four professional poker players Credit: Any repetitive task that creates a lot of data will eventually be learned by computers.

AI developed by online retail giant, Alibaba has reportedly beat humans at a reading comprehension test.


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The computer's results were compared to average human responses and in surprising results, the computer came out on top by a few points. DeepMind beat Jie at the notoriously difficult game without any input from humans. A collaborative team of scientists have developed an AI system capable of creating original pieces of art. One creates a solution or image and the other judges sit in a continuous loop until the desired outcome is achieved.

Going, going, gone

LawGeex put a three-year-old algorithm trained to evaluate contract up against twenty experienced attorneys with the robot being the clear winner. The bots and humans were tasked with identifying and highlighting 30 proposed legal issues in five standard non-disclosure agreements NDAs in just four hours. LawGeex neural network managed a 94 percent accuracy rate, beating the humans who achieved an average of 85 percent.

Not only was the AI more accurate it managed the task in just 26 seconds compared to the human time of anywhere between 51 minutes to more than 2. According to the report released about the experiments, robots are simply better at being able to read an analyze this kind of data. Lawyers and the AI, for instance, were penalized for missing an exemption relevant to the contract, or mistakenly identifying an exemption where it was irrelevant.


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