{"id":10649,"date":"2009-05-16T07:13:34","date_gmt":"2009-05-16T06:13:34","guid":{"rendered":"http:\/\/www.pasteris.it\/blog\/?p=10649"},"modified":"2009-05-16T07:25:27","modified_gmt":"2009-05-16T06:25:27","slug":"wolframalpha-e-vivo","status":"publish","type":"post","link":"https:\/\/www.pasteris.it\/blog\/2009\/05\/16\/wolframalpha-e-vivo\/","title":{"rendered":"WolframAlpha \u00e8 vivo !"},"content":{"rendered":"

\"\"WolframAlpha<\/a> ha cambiato la sua roadmap che prevedeva il lancio per luned\u00ec 18 e ha lanciato nella serata di ieri 15 maggio il suo nuovo strumento di ricerca<\/a>.<\/p>\n

Le prime impressioni d’uso di\u00a0ReadWriteWeb<\/a>, CNET News<\/a>, Data Center Knowledge<\/a>, Lifehacker<\/a>, Gizmodo<\/a> , TechCrunch<\/a> , L.A. Times Tech Blog<\/a>, Mashable<\/a> , Search Engine Land<\/a><\/p>\n

La prima impressione grande potenza di ricerca, una esposizione molto chiara dei dati senza avere troppa chiarezza delle fonti, molte ricerce finite con desolanti poche informazioni. Sembra pi\u00f9 di essere su Wikipedia, piuttosto che su Google. Ci vuole del tempo per imparare a apprezare tutta la potenza di WolframAlpha.<\/p>\n

Un video di test<\/p>\n

<\/object><\/p>\n

Steven Wolfram spiega il retrobottega di WolframAlpha<\/a><\/p>\n

<\/p>\n

Wolfram|Alpha defines a new direction in computing\u2014that would have simply not have been possible without Mathematica<\/em>, and that in time will add some remarkable new dimensions to Mathematica<\/em> itself. In terms of technology, Wolfram|Alpha is a uniquely complex software system, which has been entirely developed and deployed with Mathematica<\/em> and Mathematica<\/em> technologies.<\/p>\n

We are still at the beginning of Wolfram|Alpha as a long-term project, but already it contains nearly 6 million lines of Mathematica<\/em> code\u2014all, of course, authored and maintained in Wolfram Workbench<\/em><\/a>. When we launch Wolfram|Alpha this weekend, it will be running Mathematica<\/em> on about 10,000 processor cores, using gridMathematica<\/em><\/a>-based parallelism. And every single query that comes into the system will be served with webMathematica<\/em><\/a>.<\/p>\n

If you watch the live webcast tonight, you\u2019ll see lots of real-time system analysis, logging, and visualization\u2014all written in Mathematica<\/em>. I\u2019ve been thinking about building Wolfram|Alpha for a very long time. But one of the most important things that\u2019s made it possible now is the state of Mathematica<\/em> today. We\u2019ve always thought that Mathematica<\/em> was an increasingly development environment. But what we\u2019ve done with the development of Wolfram|Alpha in the past few years serves as living proof.<\/p>\n

The Mathematica<\/em> Computable Data Initiative was the testbed for the large-scale data curation system that we\u2019ve set up for Wolfram|Alpha. And this curation system itself relies on many features of Mathematica<\/em>. We\u2019re importing data in almost every conceivable format using Mathematica<\/em>\u2019s import capabilities<\/a>. We\u2019re combining and analyzing data using Mathematica<\/em>\u2019s data<\/a>, statistics<\/a> and visualization<\/a> capabilities. Our human curation and expert review process is done using Mathematica<\/em> symbolic documents<\/a>, with extensive dynamic interface<\/a> capabilities. And our whole central data repository system is written in Mathematica<\/em>, with symbolic representations of data and its relationships, and efficient underlying use of DatabaseLink<\/em><\/a> for relevant large and real-time datasets.<\/p>\n

Already in Mathematica 7<\/a><\/em> we\u2019ve integrated many kinds of data seamlessly into the Mathematica<\/em> language. And within Mathematica<\/em> it\u2019s possible to do arbitrarily flexible large-scale computations with the data. Wolfram|Alpha adds tremendous ease of use for small-scale computations\u2014as well as introducing a large number of new types of data, which can potentially be accessed for large-scale computation in Mathematica<\/em> in the future.<\/p>\n

Beyond curated data, another important aspect of Wolfram|Alpha is its ability to actually do computations. In building Wolfram|Alpha, we\u2019ve been systematically implementing all the methods and models of science and other areas whether quantitative approaches can be used. This is of course an immense undertaking, and without Mathematica<\/em> it would have been impossible.<\/p>\n

The coherent symbolic structure of Mathematica<\/em> is crucial to constructing the frameworks that make the programming even vaguely conceivable. And in the actual implements of so many models and methods, we\u2019re using practically every corner of Mathematica<\/em>\u2019s huge web of algorithmic capabilities.<\/p>\n

Often there may be some simple approximation that could be implemented just as a formula. But because we have Mathematica<\/em>, we can do the real computation\u2014and get real state-of-the-art results, solving differential equations, performing global optimizations, and doing whatever sophisticated math or computations are needed.<\/p>\n

One of the highly visible features of Wolfram|Alpha is its ability to understand free-form linguistic input. And this too would have been impossible without Mathematica<\/em>.<\/p>\n

There are many parts to Wolfram|Alpha\u2019s linguistic processing system. But one common theme is the deep use of symbolic programming and Mathematica<\/em>\u2019s unique symbolic pattern-matching capabilities. And here again the immediate access to efficient algorithms is also crucial\u2014whether it be for string processing, discrete math or something else. (Who knew that parsing nested sequences of |\u2019s is best done with efficient linear programming?)<\/p>\n

Yet another central aspect of Wolfram|Alpha is its automated presentation of results. And here again, many parts of Mathematica<\/em> play crucial roles. Every output from Wolfram|Alpha is constructed by the Wolfram|Alpha server as a Mathematica<\/em> notebook. The ability to automatically typeset tables, math and collections of graphics of unknown sizes and shapes is crucial. And the automatic computational aesthetics built into Mathematica<\/em> are what have made it practical to implement thousands of different kinds of visualizations in Wolfram|Alpha.<\/p>\n

If one looks at the internal code of Wolfram|Alpha, it\u2019s amazing how diverse the uses of Mathematica<\/em> are. Two principles bring it all together. The first is the symbolic character of Mathematica<\/em>\u2014which makes it possible to implement so many diverse kinds of knowledge in a unified way, and have them successfully interact with each other.<\/p>\n

The second is automation\u2014the idea that functions in Mathematica<\/em> should be as automated as possible\u2014automatically selecting algorithms, choosing visualizations, working out import formats, and so on. Because automation is what makes it feasible to create a robust system of the magnitude and functionality of Wolfram|Alpha with manageable resources.<\/p>\n

And even beyond the actual user-visible functionality of Wolfram|Alpha, Mathematica<\/em> has been crucial in the project. All of the many automated testing systems for Wolfram|Alpha are written in Mathematica<\/em>\u2014and rely on such diverse capabilities as parallel computation, symbolic structure comparison, and bitmap image manipulation.<\/p>\n

Mathematica<\/em> has been extensively used in meta-analysis of the code base and of the development process itself. And for example the ability to easily create complex interactive algorithmic diagrams\u2014say to represent stages in linguistic processing\u2014has been crucial. So Mathematica<\/em> is what\u2019s inside Wolfram|Alpha\u2014and what\u2019s made Wolfram|Alpha possible.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"

WolframAlpha ha cambiato la sua roadmap che prevedeva il lancio per luned\u00ec 18 e ha lanciato nella serata di ieri 15 maggio il suo nuovo strumento di ricerca. Le prime impressioni d’uso di\u00a0ReadWriteWeb, CNET News, Data Center Knowledge, Lifehacker, Gizmodo , TechCrunch , L.A. Times Tech Blog, Mashable , Search Engine Land La prima impressione … Leggi tutto<\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17,6,18],"tags":[162,757],"class_list":["post-10649","post","type-post","status-publish","format-standard","hentry","category-economia","category-internet","category-scienza","tag-google","tag-wolfram"],"_links":{"self":[{"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/posts\/10649","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/comments?post=10649"}],"version-history":[{"count":4,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/posts\/10649\/revisions"}],"predecessor-version":[{"id":10653,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/posts\/10649\/revisions\/10653"}],"wp:attachment":[{"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/media?parent=10649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/categories?post=10649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pasteris.it\/blog\/wp-json\/wp\/v2\/tags?post=10649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}