If you are looking for something different from the regular Internet search that you get from Google, Yahoo or DuckDuckGo, try the new Computational Knowledge Engine Wolfram|Alpha (www.wolframalpha.com). In 2009, Stephen Wolfram Research released the new engine that could answer questions written in natural language.
When you try out Wolfram|Alpha, you may be surprised that the site does not actually work like the search engines you are so accustomed to. In fact, you may not see results to some of your simple queries. Regular search engines attempt to catalog the information on the Web, and that is exactly what Alpha does not do. Rather, the Wolfram engine is a computational knowledge engine.
Traditional search engines scour the web for sites to add them to their directories. They rank different pages up or down based on the algorithms built into them, judging them on several factors. If you have a public web site and it has links to it from other sites, chances are that traditional search engines will pick it up without any effort from your side.
It is different for Wolfram|Alpha. They rely on their own licensed databases where the content entered is tagged and cataloged by employees of Wolfram Research. To give an example of the scale of things we are dealing with, at the time of launch, Alpha servers had more than 10 trillion individual chunks of data. According to Wolfram Research, its employees vet all the information for accuracy before adding anything to the Wolfram|Alpha database.
Apart from the scientific search engine, Wolfram Research also has a piece of software called Mathematica, which is a highly respected program that helps people manipulate data in many ways. Now the company has released its Wolfram Language and this is the underlying platform for all its engines from Mathematica to Alpha. The best part is that you can run it on your tiny, credit card sized single board computer, the Raspberry Pi or RBPi.
Not only is Wolfram Language free to download and use, it runs on any platform and that includes RBPi and supercomputer clusters alike. You can run it locally or in the cloud to suit your requirements. According to Wolfram Research, its performance on the RBPi is somewhat faster than the NeXT cubes when Mathematica first shipped. Considering that the NeXT cubes were multi-thousand-dollar workstations, it is surprising what your tiny RBPi is capable of.
With the RBPi taking computing back to the level of hobbyists once again, the Wolfram Language and Mathematica take it to the next level for schoolchildren. In essence, the combination becomes a highly effective knowledge-driven computational device for kids to learn about programming computers at practically no major cost.
Wolfram Language claims to be ten times faster at development compared to other languages. This is because Wolfram Language aims to maximize the productivity of the programmer by automating most of the work and building as far as possible directly within the language. The programmer has to build only the unique parts of the code, while relying on the language for everything else. The result is concise readable code, which is easy to debug. Large systems can be simply built up incrementally with symbolic components.
