In its launch configuration, Wolfram Alpha is running Mathematica on about 10, processor cores distributed among five colocation facilities, using grid Mathematica -based parallelism.
And every query that comes into the system is served with web Mathematica. The Wolfram Alpha launch process has been broadcast live on Justin. Being engaged with high-performance computing on a large scale and offering world-class resources to researchers is our mission. For more information on Wolfram Alpha, visit its Media Resources page. The company aims to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything.
Wolfram Alpha builds on the achievements of science and other systematizations of knowledge to provide a single source that can be relied on by everyone for definitive answers to factual queries. Wolfram Research, Inc.
With Mathematica 7, Wolfram Research delivered powerful new capabilities, including image processing, parallel high-performance computing, and new on-demand data—making the software more relevant than ever to everyone from leading researchers to students and other users. And starting in , this allowed him to make a series of startling discoveries about the origins of complexity.
The papers Wolfram published quickly had a major impact, and laid the groundwork for the emerging field that Wolfram called complex systems research. Through the mids, Wolfram continued his work on complexity, discovering a number of fundamental connections between computation and nature, and inventing such concepts as computational irreducibility. Wolfram's work led to a wide range of applications—and provided the main scientific foundations for such initiatives as complexity theory and artificial life.
Wolfram himself used his ideas to develop a new randomness generation system and a new approach to computational fluid dynamics —both of which are now in widespread use. Following his scientific work on complex systems research, in Wolfram founded the first journal in the field, Complex Systems , and its first research center. Wolfram began the development of Mathematica in late The first version of Mathematica was released on June 23, , and was immediately hailed as a major advance in computing.
In the years that followed, the popularity of Mathematica grew rapidly, and Wolfram Research became established as a world leader in the software industry, widely recognized for excellence in both technology and business.
Of course, I started typing in things from old stuff, and, yes, modern Wolfram Alpha gets them right. But I realized that in some sense I was probably fated for nearly 40 years to build a Wolfram Alpha. Some of what will happen with them we can foresee. But some—as we build out these new paradigms—will be as seemingly unexpected as Wolfram Alpha. It was quite tense. We were going to launch Wolfram Alpha. Leibniz was talking about a version of it years ago.
But I decided that we should give it a try. It had all started with some abstract intellectual ideas. Some news had come out about our project. So there was a lot of anticipation. Well, at the appointed time we started the live webcast. There was a horrible networking and load balancing problem.
Well, fortunately we did actually have good weather and news feeds. Because this was May in the Midwest. Here, we can actually look at live Wolfram Alpha to find out about it. See that giant spike in wind speed just before 8pm? That was a tornado. Approaching our location. But still, we had a tornado coming straight for us.
Well, fortunately, at the last minute, it turned away. And our giant project was launched—out of the starting gate. The story goes a long way back. I was a kid, growing up in England in the s. At first, I had really been into the space program. A thing called an Elliott C. About the size of a large desk. With 8K of bit words of core memory. And programmed with paper tape. Well, I started programming that machine. My top goal was to reproduce this physics process. And in the process, I learned quite a bit about programming.
And it might have been a disqualifying handicap. I wanted to make a very general system. Well, almost exactly 30 years ago today the system first came alive. And in the system was to the point where it could really be released. I was by then a young faculty member in physics at Caltech. But the company did get started.
Well, at first I thought about all sorts of complicated models for that. So I started looking at the very simplest possible programs. Well, here was the big experiment I did. In line-printer-output form from Well, in nature we see lots of complexity. Well, I thought this was pretty exciting. Well, I did lots of work in this direction myself. And I pulled in quite a few other people as well. And I wanted to start some kind of institute for the science too.
So it was hard really to fully staff up. But so I decided I need to build a new, more general, computational system. And that I needed to start and run a company to do that. Right here in Champaign, Illinois. At first, of course, it was a tiny operation. And very quickly we started to grow our company in Champaign. And gradually we realized how to do this. In a sense my idea with it was to use it automate as much as possible. All algorithms.
All forms of computation. So it gets easier and easier to build. But by now, math is a small part of what Mathematica does. Well, so things with Mathematica were going really well. Well, then the web came along. And we started doing things with that. With the numbers going up and down in different calculus seasons and so on.
One day I expect that methodology will be the dominant one in engineering. And that will be the real mega-killer industry of NKS. But back in , I was thinking about the first killer app for NKS. Of course, it helped that we had Mathematica. But still, there were many things that could wrong. And it might not be possible to curate it in any reasonable way. Or there might be too many different models and methods to implement.
With everything having to be separately built for every tiny subspecialty. Instead of trying to hassle with interpreting a spreadsheet of website traffic and sales data, he or she could upload it to Wolfram Alpha Pro and have some level of confidence that a it will understand exactly what the data is and b it will present him or her with an analysis that's actionable.
Regular users may not have had much reason to dig into the service before now, but the ability to bring the entire brunt of Wolfram Alpha's computational engine on any arbitrary piece of data democratizes the idea of statistical analysis. The service goes live on Wednesday the 8th, and there will be a trial period if you'd like to give it a shot yourself. Subscribe to get the best Verge-approved tech deals of the week.
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