Search Engines

Search is the next big thing in the World Wide Web and every big player is trying their best to capture the bigger market share of the search today. Recently I had a chance to learn about Microsoft's new Search Engine Bing and came to know that the product bing is a result of M$ buying a company that was working on Semantic Search.

With my limited interaction with Bing I did not find any WOW factor with it. The accuracy of result is bit better than google search result, but still it misses out quite a few search results (what google brings back) with high level of relevance. But it promises to be a good alternative for google search.

I also tried out Wolfram Alpha's Computational Knowledge Engine. In my opinion that is not a search engine, the Wolfram Alpha is more like a knowledge engine, that brings back facts when we submit a query. I tried to ask few questions related to Biotech and other science subjects but the result were quite disappointing, as sometime it showed me the share prices of the company and sometimes it did not bring anything at all.

The search engine technology is still far from being matured and it will be sometime before we see a fully matured search engine that can answer most of our queries. We need a true semantic search if we want to build a search engine that is helpful to the users. In the next post I will discuss more about how a true semantic search can be achieved.

Until Next Time....!!!

Is AI a possibility

In one of my previous post I discussed whether the World is Ready for AI? Today I was reading this post with after a long time (more than 2 yrs) and asked myself this question whether we have made enough advancements in the comupting to make AI possible in near future. We have had faster computers, greater RAM and storage available on our laptops over last two years but we are still far from having the computing framework that can support AI.

The basic of computing is a bit that has two states 0 and 1. What it translates to is the computer always has a state of certainty ie whether it has something or it does not have. On a contrary our normal intelligence works on few more states. We operate on 3 states.

1. We know that we know.
2. We know that we don't know
3. We don't know that we don't know.

This third state of ours is what makes us intelligent and gives us the power to reason given a situation. Human intelligence operates mostly out of this 3rd state of mind. The moment we know about anything that falls in 3rd stage it moves to either 1st or 2nd category.

Our brain operates in a 3-dimensional space and that's what provides us the flexibility to process similar data differently. But on the contrary computers operate in a linear space and that limits the processing capability of the computers. A simple example is for computer a glass of water is a glass of water no matter how many times we feed this data in, but for humans the first glass of water is life saver (if we are thirsty) but the same is not true with the 30th glass of water if it is drunk in succession. The 30th glass may become a burden to drink. So the same data is interpreted differently here in case of humans.

What we may require is to think about the fundamental aspect on which our computing is based at. The basis of computing is 0 and 1, but we may need to think about a state where the computer can be in May Be state ie somewhere in transition. Once we have this third bit discovered and our machines are based on that, we may be able to feed consciousness and that will lead to natural intelligence in computer.

Until Next Time.

Object Structures and Descriptions

While reasoning an object we often fall into a trap of thinking about the attributes and methods of the object (in a typical Object Oriented way). But reasoning about an object goes beyond the attributes and methods. While reasoning an object we need to consider the following:

1. Object fall into categories. eg. My car is a Hatchback. My Pet is doberman. etc But then we also have instances where an object is part of multiple categories like I am an Employee, Blogger and a Husband.
2. Categories can be more general or more specific in nature eg. Physician and Surgeons are types of Doctors, A Father is a parent etc.
3. In addition to generalization being common for categories with simple names, it is also natural for those with more complex description. A Contract employee is an employee. A family with at least one child is not childless etc.
4. Object have parts and these parts have multiplicity of 1 or more. Books have Title, Humans have 2 arms, Cars have 4 wheels etc.
5. The relationship among an object's parts is essential to its being considered a member of the category. A pile of book is not same as catalog of book.
   

These are few things we need consider while deriving a framework for knowledge representation. Then there are additional complexities added to it as if the same word is used as noun or pronoun. He is Helium or He refers to another person depends on the context where the word is used.

Until Next Time....

Solving Problems in Semantic Web

It's been quite sometime since I am hearing about Semantic Web and what it can do. It's been the original idea of the World Wide Waste (WWW) since the day one. But somewhere down the line we seem to have side tracked from our original path. But the question everyone is asking is :

1. In-spite of spending so much in terms of manpower and research funding why this problem is still a PROBLEM?
2. Why we are drifting away from the actual problem i.e. the Semantic Web?
3. How much time it will take before Semantic Web becomes a reality?

The answer is simple because nobody is trying to solve it. We have vendors whose sole purpose is to push and promote their tools and technologies. We have committees that work on the standards but somewhere they get side-tracked. Nobody is working towards the big picture where we can see all the pieces of puzzle fitting together. But everybody is working on small-small pieces and then calling it a step towards the Semantic Web. But that is not the approach that will work in this case. To achieve Semantic Web we need to :

1. Identify what is needed to make it work. We are better of going away from current format of Web as trying to extract meaning out of Web (today) is like trying to extract water from stones.
2. Bring a team of experts who then will sit together and get their heads aligned in one common direction.
3. Build teams that work towards solution aligned with the top-level goal.
4. Build the tools and technologies that is solely designed to build the Semantic Web.
   
5. Last but not least Start Afresh.
   

I am sure if we take this approach we will have Semantic Web as a reality not just another science fiction.

Until Next Time....

Reasoning Mechanism and Project Halo

After a long silence I am back again to unleash the ideas through this blog. A while ago I had a look at the Questions of Project Halo and that made me thinking as how can I represent chemical elements and work out a general mechanism to represent elements, compounds and chemical reactions.

What I found that using the classification described in Tree of Porphyry it was easy to describe them all and also that made the whole scenario simple to explain. Basically the chemical reactions has 3 core parts. Chemical Elements (including molecules), Compounds and the Chemical Reactions. For a chemical reaction to proceed we need to either elements or compounds or a mixture of both. The result is again a compound, element etc.

In the future posts I will discuss the procedure I am following to tackle the elementary level problems in chemistry. I would love to hear from the readers if they have a problem scenario in mind they want to discuss and then we can work out how to solve this using the reasoning mechanism I am working on. The more complex the problem is, the better it will be for me work out an appropriate way to solve the same.

Until Next Time....