From the Editor | Main Blog Index
March 11, 2009
Last week, Mathematica inventor Stephen Wolfram announced that he would be launching a new kind of Internet search engine in May, with the not-so-modest name of Wolfram Alpha. Actually it isn't a search engine at all -- it's more like a fact-finding engine. Wolfram himself calls it a "computational knowledge engine," which is meant to convey the idea that the software will be computing results, rather than just indexing Web pages based on keywords.

So presumably you could ask Alpha a question like "When was the last time SGI's stock was above $10 a share?" and Alpha would go fetch -- sorry, compute -- the answer. (By the way, the answer is Oct. 8, 2008.) Usually queries like that would only be possible with highly-specialized database applications. Alpha aims to generalize that kind of capability using only the unstructured data that exists on the Web. If Wolfram has really succeeded in doing this, it would introduce an entirely new kind of Web interaction.
Well, maybe not entirely new. Even Google lets you do simple math calculations in its search box and allows you to find definitions of words by using a "define:" prefix on a keyword. But the scope of Alpha is much larger.
Wolfram provided few details on how his new software would be implemented and made no mention if he had a supercomputer in his basement to do all this computational heavy lifting. The basic idea is that you would present a question to the Alpha box (which coincidentally looks a lot like Google's search box). Alpha would then untangle the semantics of the question, map it to the desired operation and then go distill the answer from the available data.
The last step is the most mysterious part. Whereas some people have suggested that the Web's data needs to be systematically tagged to make it semantically friendly, Wolfram has apparently taken a different tack. He says the engine will be based on Mathematica and the computational approach outline in his 2002 book, A New Kind of Science (NKS) to provide the engine's intelligence. In a nutshell, NKS describes a way of applying a general set of methods to computational systems, the idea being that a great deal of complexity is able to arise from a very simple set of rules.
If that's not obtuse enough for you, Wolfram says the Alpha engine will "explicitly implement methods and models, as algorithms, and explicitly curate all data so that it is immediately computable." I'm not at all sure what he means by "curate all data" other than reorganizing the Web data on the fly so that it's more digestible to the software. Any way you look at, Alpha's going to need a lot of smarts to do even basic fact finding, especially considering that there's no way to verify the accuracy of data encountered on the Web.
All of this might be passed off as worthless hype, except for the fact that Wolfram has plenty of street cred in the industry. As the founder and CEO of Wolfram Research, he has built a highly successful business based on a very useful piece of software. Before his success in business, Wolfram was an accomplished scientist in his own right, having received his Ph.D. in particle physics from Caltech at the age 20. His NKS book opened to mix reviews, but the ideas presented in the text show he can still plumb the depths of computational theory and mathematical modeling.
I'm anxious to see how Alpha performs in the wild. If it lives up to even a fraction of the hype it has generated, Alpha is destined to become a common Web tool like Google and Wikipedia. And maybe someday, when your son or daughter asks you why the sky is blue, you'll say: "Let's wolfram it."
Posted by Michael Feldman - March 11, 2009 @ 1:25 PM, Pacific Daylight Time
![]()
Michael Feldman is the editor of HPCwire.
No Recent Blog Comments
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Read more...
The Xeon Phi coprocessor might be the new kid on the high performance block, but out of all first-rate kickers of the Intel tires, the Texas Advanced Computing Center (TACC) got the first real jab with its new top ten Stampede system.We talk with the center's Karl Schultz about the challenges of programming for Phi--but more specifically, the optimization...
Read more...
Although Horst Simon was named Deputy Director of Lawrence Berkeley National Laboratory, he maintains his strong ties to the scientific computing community as an editor of the TOP500 list and as an invited speaker at conferences.
Read more...
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
Read more...
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
Read more...
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
Read more...
May 09, 2013 |
The Japanese government has revealed its plans to best its previous K Computer efforts with what they hope will be the first exascale system...
Read more...
May 08, 2013 |
For engineers looking to leverage high-performance computing, the accessibility of a cloud-based approach is a powerful draw, but there are costs that may not be readily apparent.
Read more...
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.