It's Rishi

Last week I was channel surfing while eating dinner in front of the TV. After failing to find anything interesting, I gave up and settled on Jeopardy. I used to watch Jeopardy sometimes as a kid and I recall being amazed at how smart the better contestants were. Not only did they have vast amounts of knowledge, but more importantly could recall it in just one or two seconds. While watching the show last week, I found myself equally amazed as before. One particular contestant fired off answers to 15th century European history questions (or more correctly “questions for answers”) so quickly I thought he must have just finished authoring a book on the subject.

By the time the Final Jeopardy round came, I was done with dinner and in front of my laptop. The question (err answer, whatever..) was given and (of course) I had not the faintest clue. For the heck of it, I typed some relevant keywords into Google and bingo! I solved Final Jeopardy. It turned out that two of the three contestants solved it correctly also. Sure, they couldn’t use Google to find the answer, but at the end of the day, in the real world, I would be equally as effective as these two contestants. This realization sparked me to think about the value of knowledge.

What’s the purpose of knowledge? My answer would be that knowledge allows one to perform a task more efficiently. Any task. The task could be conquering the latest shoot-em-up video game, cooking dinner, or solving a complex mathematics proof. Each of these tasks can be performed faster if the individual performing that task has relevant knowledge in the respective domain. The problem though is that for knowledge to be useful, it’s not sufficient that you had once gained that knowledge. Instead, for it to be useful, you not only need to have once gained it, you also must be able to recall it both accurately and in a timely manner. Without speed and accuracy in recollection, having knowledge is useless.

How useless? The test is this: Your brain or an electronic/digital means, which is faster? Which will give me the info I need faster, more accurately, and more consistently? Nine times out of ten, my answer to this question is the latter. Honestly, I wonder why I even bother remembering anything. Phone numbers? Got my cell. Favorite restaurants? Got Yelp. CS stuff? Google works just fine. Forgot who my friends are? Got my AIM buddy list, MySpace and Facebook. How to get home from work? Got a navigation system. How to spell my name? Outlook auto-corrects it. Ok, I think you get my point…

The thing you need to remember is that all the electronic information sources I just mentioned came very recently. You think finding this information is easy now? Trust me, it’ll get easier. I’m just waiting for Google to announce a search plugin for your brain. Sounds ridiculous but is it really that crazy to imagine such a device might be available in my lifetime?

Now, you might argue that humans are capable creatures because of our intelligence, not simply our knowledge. Intelligence implies not just semantic knowledge but the ability to combine building-blocks of knowledge into composite forms of knowledge and, ultimately, to innovate. Innovation, after all, is a hallmark of human civilization. Innovation implies a certain higher level of thought which only a human can perform. You could say that freeing our minds of the burden of knowledge management will allow our mind to focus on innovation and other forms of higher-level thought.

But this implies that computers cannot perform high-level thought. Computers can be given “intelligence”. It is very common today to program computers to make sophisticated decisions based on input data. Due to complexity, or other limitations, many of such decisions were once thought impossible for a computer to make. A classic example is chess. A couple hundred years ago, the thought of a chess-playing machine was just a big joke. Ten years ago, IBM’s Deep Blue computer beat the greatest chess player of our time.

But can computers innovate? If you look up the word “innovation”, the word “new” is mentioned repeatedly: new ideas, new dimensions, something new, etc. Convention has it that computers cannot think “outside of the box”. While computers can perform sophisticated logic and are able to “learn” patterns, they can’t really form new thought . A recent example of this is an article I was reading about Monitor110. They have developed some proprietary technology that allows their software to scour niche information sources on the Web (blogs, message boards etc.) and pick out potentially market-moving news before it hits the mainstream. So, their software can pick out the bits of signal from the noise, but it cannot determine if and how to act on information to bring financial reward and, moreover, outperform the rest of the market (the common term is “generate alpha” in the alternative-investment world). The formation of a unique investing strategy can only be performed by the human investor staring at the computer screen. The investor may utilize computer-based modeling tools to aid in development of the strategy, but the high-level strategy still is up to him to devise.

Will computers one day be able to innovate? Maybe. If and when scientists are better able to model the human brain, it may turn out that deep-down, it is, in fact, a deterministic system. If that is the case, it may be possible to model the human brain electronically.

Until this day, though, I do think, on the basis of the test I put forth earlier, that much of the knowledge in people’s brains is truly useless. Instead of just giving students knowledge, it is more important to teach them how to efficiently find knowledge when the situation demands it.
“Give a man a piece of knowledge and you feed him for a day. Teach a man to locate knowledge and you feed him for a lifetime.” Yeah I know..I’m a dork.

Ok, it’s way past my bedtime again. Maybe I’ll continue this thought in a later post…

I’ve been doing some Kurzweil-inspired thinking lately and I have a question for you all:

What percentage of the knowledge in your brain can be found on the Web? In other words, let’s say you were able to express all the knowledge in your brain as statements of fact. What percentage of those statements would you be able to find on the Web?

Follow up question:
Think about that percent of knowledge that cannot be found on the Web. What kind of knowledge is it? What does it pertain to?

I have my own set of answers to these questions which I will be sharing in an upcoming mini-essay I’m writing, but I was hoping that some of you might post a comment with your own answers to these questions.
Thanks for your help!

About a month ago, I was watching an interview of Raymond Kurzweil on Charlie Rose. I had heard of him before but, to be honest, did not know much about his background. So, I searched my good pal Wikipedia and read about him. Kurzweil wrote an essay back in 2001 titled, “The Law of Accelerating Returns” in which he theorizes about how continuing exponential growth of technology will soon (read: in many of our lifetimes) lead to The Singularity:

It represents the nearly vertical phase of exponential growth where the rate of growth is so extreme that technology appears to be growing at infinite speed. Of course, from a mathematical perspective, there is no discontinuity, no rupture, and the growth rates remain finite, albeit extraordinarily large. But from our currently limited perspective, this imminent event appears to be an acute and abrupt break in the continuity of progress. However, I emphasize the word “currently,” because one of the salient implications of the Singularity will be a change in the nature of our ability to understand. In other words, we will become vastly smarter as we merge with our technology.

Now I know that some of you are probably like “Wow, sounds like this Kurzweil guy’s been smoking a stash of some sweet chiba. You think I could get some off him?”. But what I really appreciate about the essay is his scientific approach using empirical data from many areas of technology and methodical analysis to support his theories.

I can in no way do this paper justice by summarizing it. I wanted to highlight some of the key points here but my list was getting too long and many of the points just don’t make sense out of context.

Like I said, I first read this paper about a month ago and ever since, I’ve mentioned it to almost everyone I know. Even if you have absolutely no curiosity about the future of technology and how it will change your life, how can you not read an essay which begins by stating:

“You will get $40 trillion just by reading this essay and understanding what it says.”

Over the next few weeks, I hope to read more from Kurzweil and other researchers to gain a broader perspective of this topic.

Last month, Patrick Bedard of Car & Driver (my favorite automotive publication) wrote a great article in which he crunched some numbers on what our country’s energy consumption would be if we all drove hydrogen-powered cars. The underlying problem is producing hydrogen. Because pure hydrogen does not exist naturally, it requires an input of energy to seperate hydrogen from a hydrogen-containing molecule (most often this molecule is water and the process is electrolysis). So where does this energy input come from?

Coal – Producing Hydrogen using coal is 12% efficient. If all cars in the US were hydrogen powered, we would consume twice as much coal than we currently are with gasoline power. We would also produce 2.7x carbon emissions.

Natural Gas – The popular process for creating Hydrogen from natural gas is called “steam reforming” and is 30% efficient. If all cars in the US ran on hydrogen created from natural gas, our gas consumption would actually increase 66% over current levels.

As depressing as it may be, the article offers clear evidence that hydrogen power cars are far from mainstream reality. Until scientists can come up with a very efficient way to produce hydrogen, this technology just does not make sense.