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Category: entertainment – Page 61

The triumph of Google’s AlphaGo in 2016 against Go world champion Lee Sedol by 4:1 caused quite the stir that reached far beyond the Go community, with over a hundred million people watching while the match was taking place. It was a milestone in the development of AI: Go had withstood the attempts of computer scientists to build algorithms that could play at a human level for a long time. And now an artificial mind had been built, dominating someone that had dedicated thousands of hours of practice to hone his craft with relative ease.

This was already quite the achievement, but then AlphaGoZero came along, and fed AlphaGo some of its own medicine: it won against AlphaGo with a margin of 100:0 only a year after Lee Sedol’s defeat. This was even more spectacular, and for more than the obvious reasons. AlphaGoZero was not only an improved version of AlphaGo. Where AlphaGo had trained with the help of expert games played by the best human Go players, AlphaGoZero had started literally from zero, working the intricacies of the game out without any supervision.

Given nothing more than the rules of the game and how to win, it had locked itself in its virtual room and played against itself for only 34 hours. It didn’t combine historically humanity’s built up an understanding of the principles and aesthetics of the game with the unquestionably superior numerical power of computers, but it emerged, just by itself, as the dominant Go force of the known universe.

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Eric klein.

If you followed the world of pop-culture or tech for some time now, then you know that advances in artificial intelligence are heating up. In reality, AI has been the talk of mainstream pop-culture and sci-fi since the first Terminator movie came out in 1984. These movies present an example of something called “Artificial General Intelligence.” So how close are we to that?

No, not how close are we to when the terminators take over, but how close are we to having an AI capable of navigating nearly any problem it’s presented with.

Continue reading “How Close We Are to Fully Self-Sufficient Artificial Intelligence” | >

What are some of ways that technology can be used to combat things like racism, bipartisan politics, Islamophobia, antisemitism, and extreme prejudice? Especially when these things are systemically embedded in certain cultures to the point that rationality seems to fly out the window? I see conversations on social media in peaceful international groups such as this one as a great potential stepping stone to mediate the tension between groups who seem to be devoted to blind hatred for one another. What are some other ways technology can advance social and political sciences?

“This article analyzes the narratives of Islamophobia in Hindu Nationalism (Hindutva). Specifically, it analyzes how Indian Prime Minister Narendra Modi, from the Hindu nationalist Bharatiya Janata Party (BJP), articulates Islamophobia in his speeches, interviews, and podcasts. In total, a discourse analysis of 35 such documents has been conducted. Conceptually, this article applies the notion of language-games to understand how Modi articulates Islamophobia. The article contends that while Modi’s Islamophobia is executed subtly, it is nonetheless a function of the way in which Hindutva conceives of Muslims as subordinate to Hindus. Two Islamophobic narratives in Modi’s political discourse have been mapped out: the erasure of Indian Muslim histories in Modi’s economic development agenda, and the characterization of Hinduism as having a taming effect on Islam in India. The article provides a conceptual overview of language-games and a review of how Hindutva defines Hindus and Muslims, before analyzing how Modi articulates Islamophobia. The article concludes by suggesting that a Hindutva-driven Islamophobia may have permeated into the Hindu mainstream.”

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John Horton Conway, a legendary mathematician who stood out for his love of games and for bringing mathematics to the masses, died on Saturday, April 11, in New Brunswick, New Jersey, from complications related to COVID-19. He was 82.

Known for his unbounded curiosity and enthusiasm for subjects far beyond mathematics, Conway was a beloved figure in the hallways of Princeton’s mathematics building and at the Small World coffee shop on Nassau Street, where he engaged with students, faculty and mathematical hobbyists with equal interest.

Conway, who joined the faculty in 1987, was the John von Neumann Professor in Applied and Computational Mathematics and a professor of mathematics until 2013 when he transferred to emeritus status.

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There’s an iconic scene in the original Star Wars movie where Luke Skywalker looks out over the desert landscape of Tatooine at the amazing spectacle of a double sunset.

Now, a new study out of the National Radio Astronomy Observatory (NRAO) suggests that such exotic exoplanet worlds orbiting multiple stars may exist in misaligned orbits, far out of the primary orbital plane.

The find has implications for planetary formation in complex multiple star systems. The study used ALMA (the Atacama Large Millimeter/submillimeter Array) in Chile to look at 19 protoplanetary disks around binary stars with longer period orbits, versus a dozen binary stars known to host exoplanets with periods less than 40 days found in the Kepler space telescope observations.

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Nowadays, artificial neural networks have an impact on many areas of our day-to-day lives. They are used for a wide variety of complex tasks, such as driving cars, performing speech recognition (for example, Siri, Cortana, Alexa), suggesting shopping items and trends, or improving visual effects in movies (e.g., animated characters such as Thanos from the movie Infinity War by Marvel).

Traditionally, algorithms are handcrafted to solve complex tasks. This requires experts to spend a significant amount of time to identify the optimal strategies for various situations. Artificial neural networks — inspired by interconnected neurons in the brain — can automatically learn from data a close-to-optimal solution for the given objective. Often, the automated learning or “training” required to obtain these solutions is “supervised” through the use of supplementary information provided by an expert. Other approaches are “unsupervised” and can identify patterns in the data. The mathematical theory behind artificial neural networks has evolved over several decades, yet only recently have we developed our understanding of how to train them efficiently. The required calculations are very similar to those performed by standard video graphics cards (that contain a graphics processing unit or GPU) when rendering three-dimensional scenes in video games.

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Replicating human interaction and behavior is what artificial intelligence has always been about. In recent times, the peak of technology has well and truly surpassed what was initially thought possible, with countless examples of the prolific nature of AI and other technologies solving problems around the world.

Think about this: Gary Kasparov stated that he would never lose a game of chess to a computer. For a long time, this seemed like a statement that would withstand all tests.

Roll on 1996, however, and IBM developed Deep Blue, a computer bot/program/application that beat the master Gary Kasparov at his own game.

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