Contributed by guest blogger Gareth Murran from the ThirdForce Innovation Technology team
Such is Google’s dominance in the world of online search and advertising that there is always the urge to declare any major new search player a “Google Killer” amid copious amounts of technology industry hype.
Recent examples include Cuil, which I used once and never heard of again and Powerset which is an interesting way of presenting the information on a Wikipedia page. Powerset was acquired by Microsoft before ever really getting a chance to prove itself as a commercially viable product. It may reappear as part of Microsoft Live but there is a general acceptance in the industry that Google can’t be beaten with an evolutionary approach so something revolutionary is required.
Enter British-born physicist Stephen Wolfram. Stephen is apparently a very well-known figure in the sciences for inventions like the math problem-solving software Mathematica. Stephen is in the news again because he is attempting to reinvent web search by making a smart “fact computer” engine, Wolfram Alpha. In a demo available on YouTube we can see how the tool computes many of the answers “on the fly” by grabbing raw data from public and licensed databases, along with live feeds such as the height of Mount Everest – or crunch several data sets together to produce new results, such as a country’s GDP.
The system’s not like previous efforts at this technology which used natural language processing to determine your question and then simply present the web-search results. Instead Alpha is supposedly revolutionary since it actually computes the answer for you. What’s interesting about this technology is that it doesn’t simply return documents that (might) contain the answers, like Google does, and it isn’t a giant database of knowledge, like the Wikipedia. Nor does it parse natural language and then use that to retrieve documents, like Powerset, for example.
Formal Knowledge
The vision seems to be to create a system which can do for formal knowledge (all the formally definable systems, heuristics, algorithms, rules, methods, theorems, and facts in the world) what search engines have done for informal knowledge (all the text and documents in various forms of media). The management of unstructured data (informal knowledge) is recognised as one of the major unsolved problems in the technology industry. The main reason being, that the tools and techniques that have proved so successful transforming structured data (formal knowledge) into business intelligence and actionable information simply don’t work when it comes to unstructured data.
Five approaches currently exist but further new approaches are necessary.
- Tagging
- Algorithms and Statistics
- Linguistics
- Semantic Web
- Artificial Intelligence
Google currently provides the best results in search using very computer intensive algorithms. Wolfram Alpha seems like it’s mainly designed to perform the missing task at the end of a Google search taking all the matched web pages into one final answer. It looks like Google will still corner the market on most normal search.
When the Alpha is released in May I expect it to remain a niche player. It will be a highly valuable tool for a small subset of potential users. Though, hopefully, over time the team will add more and better data sets to draw information from so that Alpha will become more useful for a mainstream audience as well.
