Is Search the Future? (Part-1)

This is the first in a multi-part series on Cognika’s vision of information access in the next generation of the web. In subsequent posts we will provide specifics on how this would work in practice.

A hotly debated topic is the so-called “future of search” or "the next Google". Opinions have ranged from Google’s Marissa Mayer's “search is 90% solved” to Bill Gates’ opinion that search has barely scratched the surface. However, search is increasingly more of a problem than a solution.

Undoubtedly, companies like Google, Yahoo etc. efforts in search have made information accessible to anyone with an internet connection - which is a very laudable achievement - but it has made the challenge of information overload worse than anyone could have imagined. Search, has made information available, but it has not yet begun to make it usable, and there is a night/day difference between information availability and usability. To make information usable, it needs to be coalesced from multiple-sources in a context-specific manner and presented intelligently to achieve a task. (look for specifics in later posts)

Search today is - pardon the expression - a** backwards. Imagine a child asking a parent questions that typically puzzle the infant mind, about “why it rains”, “why birds fly” or “why are leaves green” etc. and now picture the parent handing out a collection of encyclopedias, books, papers, articles etc. in response, and saying “go figure it out”. In many ways, the current paradigm is just as inane. It is left up to the user to make sense of the information from across multiple-sources (and most information does indeed span multiple sources).

A school of thought believes that the holy grail of search is a crisp, succinct response to queries. While this approach might work for questions such as “What is the capital of Peru?” or “Who is the current president of Ukraine?”, this approach would fail for the vast majority of queries – the ones for which there is no ready-made response. Since this involves aggregating information from multiple-sources, reasoning therewith, providing a response that is relevant and contextual, and yet provide a user-definable level of detail.

For example, could such a system answer a subjective question such as “What are the greatest movies of all time?” A response would typically involve user iterations: as ranked by AFI or IMDB or MPAA? Hollywood or International? Specific genre? And so on…

Some might argue the faceted browsing approach would work since a result set could be filtered by selecting/deselecting facets for the above etc. However, that is not quite the end of it. While the content might include Movie Title, Synopsis, Cast and some associated information. This does not allow inclusion of user-definable data points: such as reviews from select critics, availability in local stores, movies with similar plot lines, other movies by the same director, or other movies in the same genre etc.

This information would usually span multiple data-sources, documents, domains and would require repeated searches and manual collation. Now extrapolate this to highly complex domains (such as scientific research, business analysis etc.) and the challenge is multiplied manifold.

At Cognika we believe that a new paradigm needs to be developed for information processing and that search as-is today is a stepping-stone towards this vision. This quote best summarizes Cognika’s vision for the future: “Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning.” – Winston Churchill.