Fascinating talk on emergence

Here is a talk by Prof. Bonnie Bassler on the phenomenon of emergence in bacteria and how they "communicate". This demonstrates how simple interactions combine to create complex behavior.

The beginning of Web 3.0 : Wolfram Alpha

In a previous post, we discussed the current paradigm of “search-and-click” as the principal paradigm of information retrieval over the web. Search, while (and very laudably) making information available, is far from making it usable. As Einstein is reported to have said, “Information is not knowledge”. The next goal of the web should be to make this information-glut usable as “knowledge”.

In this post, we discuss Cognika’s ideas on what the next-generation of web can and should be. We believe that next generation systems should address the four “C” s of information retrieval:

1. Contextual
2. Customizable
3. Composite
4. Complete

Unfortunately, current search technologies are far from meeting such requirements. However, a fascinating effort called Wolfram Alpha (of Mathematica and Mathworld fame) seems to be along the lines of we at Cognika have been working on.

Nova Spivak of Twine describes it thus:

“In a nutshell, Wolfram and his team have built what he calls a "computational knowledge engine" for the Web. OK, so what does that really mean? Basically it means that you can ask it factual questions and it computes answers for you.
It doesn't simply return documents that (might) contain the answers, like Google does, and it isn't just a giant database of knowledge, like the Wikipedia. It doesn't simply parse natural language and then use that to retrieve documents, like Powerset, for example.

Instead, Wolfram Alpha actually computes the answers to a wide range of questions -- like questions that have factual answers such as "What is the location of Timbuktu?" or "How many protons are in a hydrogen atom?," "What was the average rainfall in Boston last year?," "What is the 307th digit of Pi?," or "what would 80/20 vision look like?”

We believe while computing the answers to scientific questions as Wolfram Alpha apparently does is amazing and potentially world-changing. However there are far simpler approaches that make information usable for the average user. At Cognika we are developing technologies towards that end, and you can view the Cognika XI demonstrator preview we have created to illustrate what we mean. There are very many lower hanging fruit, which could lead up to tools like Alpha. As described earlier, we are big believers in the concept of emergent semantics, and are positive that such "knowledge" could arise out of much simpler approaches and interactions. Alpha apparently does this by hiring a horde of scientists and researchers to codify the scientific knowledge, but to do this on a web-scale is a different matter altogether. Here the idea of emergent semantics is likely to help develop knowledge on a web-scale.

Having said that, we are very eagerly looking forward to Alpha's due to be release later this year. This promises to be a game-changing tool and move the web to a completely new paradigm of information retrieval. Exciting times lie ahead!

"Intelligent" Design

Here is a fascinating list of intelligent and smart design approach (no pun intended): of design following or borrowing from nature. Such cross-domain fertilization is a truly powerful way of cracking some of the hardest challenges of the modern world.

In a previous post we discussed the potential of biomimetics or mimetics in general. What is needed is the ability to connect scientific challenges with potential solutions from learning in nature and a variety of other domains.

Despite valiant efforts by some academicians and some in industry, such a project needs a lot more resources to reach critical-mass. One wishes there was a full-fledged collaborative effort from government, academia and big pharma and other businesses to push for a shared knowledge corpus (a la Wikipedia), but published in a machine-understandable or machine-query-able format that could be leveraged for such cross-domain breakthroughs.

The Semantic Web concept is a a great step in that direction, but we hope baby-steps could be taken by people and organizations just publishing more metadata and better descriptors of their data, on which approaches like the above can be built upon. It certainly need not be a single repository like the Wikipedia, but a just a collection of sources much like the current WWW.

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.

Cognika gets some press

Cognika gets covered in Mass Hightech. We are proud of the fact that we are among the few companies to survive this brutal economy. As Paul Graham points out in his very insightful article, this is the best time for a startup: "why to startup in a bad economy".