peetm writes: I have an above averagely bright nephew, aged 10, who's into maths and whose birthday is coming up soon. I'd like to get him a suitable present – most likely one that's mathematically centred. At Christmas we sat together while I helped him build a few very simple Python programs that 'animated' some simple but interesting maths, e.g., we built a factorial function, investigated the Collatz conjecture (3n + 1 problem) and talked about, but didn't implement Eratosthenes' Sieve – one step too far for him at the moment perhaps. I've looked about for books that might blend computing + maths, but haven't really found anything appropriate for a 10-year-old. I should be indebted to anyone who might suggest either a suitable maths book, or one that brings in some facet of computing. Or, if not a book, then some other present that might pique his interest.
theodp writes: From Stephen Wolfram's blog post announcing the Wolfram Programming Lab: "It's a very important — and in fact transformative — moment for programming education. In the past one could use a 'toy programming language' like Scratch, or one could use a professional low-level programming language like C++ or Java. Scratch is easy to use, but is very limited. C++ or Java can ultimately do much more (though they don't have built-in knowledge), but you need to put in significant time—and get deep into the engineering details—to make programs that get beyond a toy level of functionality. With the Wolfram Language, though, it's a completely different story. Because now even beginners can write programs that do really interesting things. And the programs don't have to just be 'computer science exercises': they can be programs that immediately connect to the real world, and to what students study across the whole curriculum. Wolfram Programming Lab gives people a broad way to learn modern programming — and to acquire an incredibly valuable career-building practical skill. But it also helps develop the kind of computational thinking that's increasingly central to today's world." So, when it comes to programming education, are schools hitchIng their cart to the wrong horse?
theodp writes: To commemorate the 200th birthday of Ada Lovelace, Google's CS Education in Media Program partnered with YouTube Kids on Happy Birthday Ada! for Computer Science Education Week. For those seeking (much!) more information on The Enchantress of Numbers, Stephen Wolfram has penned a pretty epic blog post, Untangling the Tale of Ada Lovelace. "Ada Lovelace was born 200 years ago today," Wolfram begins. "To some she is a great hero in the history of computing; to others an overestimated minor figure. I've been curious for a long time what the real story is. And in preparation for her bicentennial, I decided to try to solve what for me has always been the 'mystery of Ada'." If you're not up for the full 12,000+ word read, skip to "The Final Story" for the TL;DR summary.
theodp writes: Stephen Wolfram received a PhD in particle physics at age 20 (his thesis committee included Richard Feynman). So it's probably not too surprising that Wolfram's new book, An Elementary Introduction to the Wolfram Language (free on the web), aspires to teach those new to programming how to do much more than just move Minecraft and Star Wars characters around. "The goal of the book," explains Wolfram in a blog post, "is to take people from zero to the point where they know enough about the Wolfram Language that they can routinely use it to create programs for things they want to do. And when I say 'zero', I really mean 'zero'. This is a book for everyone. It doesn't assume any knowledge of programming, or math (beyond basic arithmetic), or anything else. It just starts from scratch and explains things. I've tried to make it appropriate for both adults and kids. I think it'll work for typical kids aged about 12 and up."
Stephen Wolfram's accomplishments and contributions to science and computing are numerous. He earned a PhD in particle physics from Caltech at 20, and has been cited by over 30,000 research publications. Wolfram is the the author of A New Kind of Science, creator of Mathematica, the creator of Wolfram Alpha, and the founder and CEO of Wolfram Research. He developed Wolfram Language, a general multi-paradigm programming language, in 2014. Stephen has graciously agreed to answer any questions you may have for him. As usual, ask as many as you'd like, but please, one per post.
theodp writes "The devil will be in the details, but if you were stoked about last November's announcement of the Wolfram programming language, you'll be pleased to know that a just-released dry-but-insanely-great demo delivered by Stephen Wolfram does not disappoint. Even if you're not in love with the syntax or are a FOSS devotee, you'll find it hard not to be impressed by Wolfram's 4-line solution to a traveling salesman tour of the capitals of Western Europe, 6-line camera-capture-to-image-manipulation demo, or 2-line web crawling and data visualization example. And that's just for starters. So, start your Raspberry Pi engines, kids!"
First time accepted submitter sixoh1 writes "Scientific American has an excellent summary of a new book 'The Improbabilty Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day' by David J. Hand. The summary offers a quick way to relate statistical math (something that's really hard to intuit) to our daily experiences with unlikely events. The simple equations here make it easier to understand that improbable things really are not so improbable, which Hand call the 'Improbability Principle:' 'How can a huge number of opportunities occur without people realizing they are there? The law of combinations, a related strand of the Improbability Principle, points the way. It says: the number of combinations of interacting elements increases exponentially with the number of elements. The 'birthday problem' is a well-known example. Now if only we could harness this to make an infinite improbability drive!"
Nerval's Lobster writes "Which football team will win the Super Bowl this weekend? That's a multi-million-dollar question, given the amount of cash people will bet on either the Seattle Seahawks or the Denver Broncos to win. Fortunately, Wolfram Alpha (the self-billed "computational knowledge engine") can analyze the historical statistics for both teams and throw out some potentially useful numbers. Developed by Stephen Wolfram and based his Wolfram Research's Mathematica analytical platform, Wolfram Alpha is an altogether different search engine from Bing or Google, which generally return pages of blue hyperlinks in response to queries. Instead of multiple results leading to still other Webpages, Wolfram Alpha usually returns set of definitive, numerical answers. (A lengthy rundown of the engine's capabilities is found on its 'About' page.) So how does Wolfram's engine, which features sophisticated algorithms chewing through trillions of pieces of data, break down the potentials for Sunday's game? Out of the 38 times the two teams have met on the field, the Broncos have triumphed 25 times (versus 12 wins for the Seahawks), scoring 98 total touchdowns to the Seahawks' 84. It's definitely advantage Broncos, in that sense. But the teams' percentages are fairly close with regard to total yardage, penalties, penalty yards, and other metrics, although the Seahawks have managed to nab more interceptions (47, versus the Broncos' 37). But while Wolfram Alpha can crunch all the historical data it wants, and that data can suggest one team will likely triumph over another, there's always the likelihood that something random—a freak injury, or a tweak to the player lineup—can change the course of the game in ways that nobody can anticipate. Also, given how player and coaching rosters vary from year to year, the teams taking the field can change radically between meetings." EA has correctly predicted eight of the last ten Super Bowl winners using the latest Madden game.
theodp writes "Weighing in for the WSJ on Spike Jonze's Oscar-nominated, futuristic love story Her (parodies), Stephen Wolfram — whose Wolfram Alpha drives the AI-like component of Siri — thinks that an operating system like Samantha as depicted in the film isn't that far off. In Her, OS Samantha and BeautifulHandwrittenLetters.com employee Theodore Twombly have a relationship that appears to exhibit all the elements of a typical romance, despite the OS's lack of a physical body. They talk late into the night, relax on the beach, and even double date with friends. Both Wolfram and Google director of research Peter Norvig (who hadn't yet seen the film) believe this type of emotional attachment isn't a big hurdle to clear. 'People are only too keen, I think, to anthropomorphize things around them,' explained Wolfram. 'Whether they're stuffed animals, Tamagotchi, things in videogames, whatever else.' By the way, why no supporting actor nomination for Jonze's portrayal of foul-mouthed animated video game character Alien Child?"
An anonymous reader writes "Working with the Raspberry Pi Foundation, effective immediately, there's a pilot release of the Wolfram Language — as well as Mathematica—that will soon be bundled as part of the standard system software for every Raspberry Pi computer. Quite soon the Wolfram Language is going to start showing up in lots of places, notably on the web and in the cloud."
Nerval's Lobster writes "Stephen Wolfram, the chief designer of the Mathematica software platform and the Wolfram Alpha 'computation knowledge engine,' has another massive project in the works—although he's remaining somewhat vague about details for the time being. In simplest terms, the project is a new programming language—which he's dubbing the 'Wolfram Language'—which will allow developers and software engineers to program a wide variety of complex functions in a streamlined fashion, for pretty much every single type of hardware from PCs and smartphones all the way up to datacenters and embedded systems. The Language will leverage automation to cut out much of the nitpicking complexity that dominates current programming. 'The Wolfram Language does things automatically whenever you want it to,' he wrote in a recent blog posting. 'Whether it's selecting an optimal algorithm for something. Or picking the most aesthetic layout. Or parallelizing a computation efficiently. Or figuring out the semantic meaning of a piece of data. Or, for that matter, predicting what you might want to do next. Or understanding input you've given in natural language.' In other words, he's proposing a general-purpose programming language with a mind-boggling amount of functions built right in. At this year's SXSW, Wolfram alluded to his decades of work coming together in 'a very nice way,' and this is clearly what he meant. And while it's tempting to dismiss anyone who makes sweeping statements about radically changing the existing paradigm, he does have a record of launching very big projects (Wolfram Alpha contains more than 10 trillion pieces of data cultivated from primary sources, along with tens of thousands of algorithms and equations) that function reliably. At many points over the past few years, he's also expressed a belief that simple equations and programming can converge to create and support enormously complicated systems. Combine all those factors together, and it's clear that Wolfram's pronouncements—no matter how grandiose—can't simply be dismissed. But it remains to be seen how much of an impact he actually has on programming as an art and science."
Gary Marcus writes in the New Yorker about the state of artificial intelligence, and how we take it for granted that AI involves a very particular, very narrow definition of intelligence. A computer's ability to answer questions is still largely dependent on whether the computer has seen that question before. Quoting: "Siri and Google’s voice searches may be able to understand canned sentences like 'What movies are showing near me at seven o’clock?,' but what about questions—'Can an alligator run the hundred-metre hurdles?'—that nobody has heard before? Any ordinary adult can figure that one out. (No. Alligators can’t hurdle.) But if you type the question into Google, you get information about Florida Gators track and field. Other search engines, like Wolfram Alpha, can’t answer the question, either. Watson, the computer system that won “Jeopardy!,” likely wouldn’t do much better. In a terrific paper just presented at the premier international conference on artificial intelligence (PDF), Levesque, a University of Toronto computer scientist who studies these questions, has taken just about everyone in the field of A.I. to task. ...Levesque argues that the Turing test is almost meaningless, because it is far too easy to game. ... To try and get the field back on track, Levesque is encouraging artificial-intelligence researchers to consider a different test that is much harder to game ..."
Nerval's Lobster writes "Back in January, when Wolfram Alpha launched an updated version of its Personal Analytics for Facebook module, the self-billed 'computational knowledge engine' asked users to contribute their detailed Facebook data for research purposes. The researchers at Wolfram Alpha, having crunched all that information, are now offering some data on how users interact with Facebook. For starters, the median number of 'friends' is 342, with the average number of friends peaking for those in their late teens before declining at a steady rate. Younger people also have a tendency to largely add Facebook friends around their own age — for example, someone who's 20 might have lots of friends in the twenty-something range, and comparatively few in other decades of life—while middle-aged people tend to have friends across the age spectrum. Beyond that, the Wolfram Alpha blog offers up some interesting information about friend counts (and 'friend of friend' counts), how friends' networks tend to 'cluster' around life events such as school and sports teams, and even how peoples' postings tend to evolve as they get older — as people age, for example, they tend to talk less about video games and more about politics. 'It feels like we're starting to be able to train a serious "computational telescope" on the "social universe,"' the blog concluded. 'And it's letting us discover all sorts of phenomena.'"
Nerval's Lobster writes "At this year's SXSW conference, Stephen Wolfram—most famous in tech circles as the chief designer of the Mathematica software platform, as well as the Wolfram Alpha 'computation knowledge engine'—demonstrated his upcoming Programming Cloud, and indicated he was developing a mobile platform for engineering and mathematical applications based on the Wolfram programming language built for Mathematica. He also talked more broadly about the future of Wolfram Alpha, which he said will become more anticipatory of peoples' queries. 'People generally don't understand all the things that Wolfram Alpha can do,' Wolfram told the audience. His researchers are also working on a system modeler tool, which will allow researchers to simulate complex devices with tens of thousands of components; in theory, you could even use such a platform for 3D printing. Wolfram also wants to set Wolfram Alpha loose on documents, with the ability to apply complex calculations to, say, company spreadsheets. 'A whole bunch of things that I've been working on for 30 years are converging in a very nice way,' he said."
Nerval's Lobster writes "Whatever your actual feelings about football and this weekend's Super Bowl, you have to admire Wolfram Alpha's willingness to crunch any dataset and see what it can find. The self-billed 'computational knowledge engine' has analyzed the historical data for both teams involved in this Sunday's Super Bowl XLVII. Its conclusion? The San Francisco 49ers and Baltimore Ravens are 'annoyingly similar' when it comes to numbers, although some players stand out as potential game changers — if the math plays out right."
Nerval's Lobster writes "Wolfram Alpha has upgraded its Personal Analytics for Facebook module, giving users the ability to dissect their own social-networking data in new ways. Wolfram Alpha's creators first launched its Facebook data-mining module in August 2012. Users could leverage the platform's computational abilities to analyze and visualize their weekly distribution of Facebook posts, types of posts (photos, links, status updates), weekly app activity, frequency of particular words in posts, and more. This latest update isn't radical, but it does offer some interesting new features, including added color coding for 'interesting' friend properties, including relationship status, age, sex, and so on; users can also slice their network data by metrics such as location and age." Wolfram users could also use some of that new site-specific searching power to come up with some unsavory results.
TsukiKage writes "A 50-card M:tG combo for four players is demonstrated that is used to construct a simple Turing machine, performing arbitrary computations just by following the rules of Magic and card text thereafter."
Nerval's Lobster writes "Ever wanted to mine your own Facebook data? Wolfram Alpha is offering you the chance. Wolfram Alpha bills itself as a 'computational knowledge engine.' In contrast to other search engines such as Google and Bing, which return pages of blue hyperlinks in response to queries, Wolfram Alpha offers up objective data: type in the name of a person, for example, and you might receive their dates of birth and death, a timeline, and a graph of Wikipedia page hits. Now Wolfram Alpha's offering a new feature that can spit back years of your personal Facebook data sliced, diced, visualized and analyzed."
New submitter submeta writes "Katsunobu Imai at Hiroshima University has figured out a way to construct a universal Turing machine using cellular automata in a Penrose tile universe. 'Tiles in the first state act as wires that transmit signals between the logic gates, with the signal itself consisting of either a 'front' or 'back' state. Four other states manage the redirecting of the signal within the logic gates, while the final state is simply an unused background to keep the various states separate.' He was not aware of the recent development of the Penrose glider, so he developed this alternative approach."
judgecorp writes "Apple has changed the answer Siri gives to the question 'What is the best smartphone ever?' to prevent the voice-driven assistant from promoting the Nokia Lumia 900. Originally Siri trawled online reviews on the web, using the Wolfram Alpha search engine, to come up with the Lumia, much to Apple's embarrassment. Now, Apple has intervened, replacing that answer with a joke: 'Wait there are other phones?'"