Reasoning about being a nerd


After going through the rites of passage into corporate adult-hood through a school, one question that people may ask is why does it seem that those who make the most popular people list are those who may have learnt the art of Machiavellian politics at a young age or the ultimate over exaggerators if one is female?

Mathematically, popularity can be measured through a network. Those with large networks are more popular than those with small network. It corresponds to what people call a ‘profile’.

The downside is that kids sometimes are pressured to adopt a particular way of thinking or behaving that they know not to be part of their psychology and make up, just to fit in with the over-exaggerators or to expand their network. In fact, with tools like Instagram available these days, kids may even target a number of likes or hits like a corporate targets a stock price.

But I think the nerdy ones may actually have a better outlook and future.

Recently, I stumbled across a YouTube channel called Stuff Made Here. It features an obviously super intelligent guy building stuff do crazy things, like a baseball bat that can literally break Babe Ruth’s world record or a an automatic pool stick that can calculate the best shot. Both videos had massive hits, with 8 million for the first video and 12 million views for the second video. What makes it even more amazing is that the dude actually has a fully tooled machine shop in his basement , including his own self-built CNC machine, a 3D printer and a plasma cutter.

But for those without the space for their own machine shop, YouTube still offers amazing videos for free that can help one improve their skills and knowledge. This is especially important in the technology industry, because literally, the industry is built on the premise that Knowledge is Power.

The nice thing about the tech industry is its democratization. All you need is a RM 2,000 desktop equipped Windows, an internet connection, a good table and chair and you are set. You have literally everything you need to launch your career into Technology world. You can build an App, or a platform (as what I am doing), and take advantage of the latest technologies out there.

For example, in my development cycle, I hit a road block last week (siaran tergendala situation, which lasted until yesterday) . To put simply, there was this resource available called FIBO EDM, which combined hundreds of thousands of man hours to come out with the most elaborate and comprehensive data model for business use, but there was a snag.

No, it was not the cost as you could download it for free.

It was the complexity.

By complex, take a look at this picture below.

This is actually not part of the FIBO package but it illustrates the idea. What the above picture shows is something called a class diagram and how different real world things relate to each other in terms  of their properties.

The FIBO package is several orders more complex but the issue is how could one start to wrap their heads around this.  You could read the manual but that would be about 1,000 pages. And worse still, the package even though encompassing a world class design did not have programming examples in Python which programmers require to try out various features.

Here is where we have to thank SAP.

SAP’s Chairman, Mr. Hasso Plattner (above), personally funded the technology department at the University of Postdam , hence it is called the Hasso Plattner Institute. And they actually have one of the best online courses out there to get your head around the above diagram through their Knowledge Engineering Youtube series by Prof Dr. Harald Sack.

So I spent several hours (even was listening while I fell a sleep as my attempt at a Jedi Mind trick)  going through the course in detail yesterday.

So why this violence?

The reason is that in order to use the FIBO model, one needs to have a good understanding of this creature called OWL , or Web Ontology Language. Without an understanding of OWL and Web Ontologies, one cannot take advantage of the millions of dollars of effort that went into building FIBO. Now what makes this really exciting is that Web Ontologies come with this promise of “Reasoning” – which means computers making logical deductions based on certain axioms of this thing called Descriptive Logic.

We will have more to say on Reasoning once we hit there. Our Named Entity worked (albeit a crude hack was required) and once we can pump the data into the FIBO model and use automated reasoning, then we may something good going on.

That is all I want to say today.


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