A Journey in search of AI 01 – Introduction

As an Engineer who is and has been amazed by the mere concept of AI since childhood, its time for me to put things to work or I will forever be just a dreamer. So I am beginning my journey towards AI and hopefully it will be a successful one after a decade or so (I am told that it will take at-least a decade or so to get a good grasp of things.)

So what the hell, lets give it a try (said the idiotic engineer 🙂 )

But seriously, today I got a shock reading some thing that a Google engineer said a way back (in 2005).

We are not scanning all those books to be read by people, we are scanning them to be read by an AI.

This gave me goosebumps. Are will coding our own doomsday or are we going for a eutopia ? (Hmm that’s a good name for a new article series ‘Towards doomsday or eutopia ?’)

What ever it is it seems that AI (may be not the version you and me think) will be inevitable. Google’s co-founder Larry Page said the following and similar things during the past decade and that solidifies the direction world is heading.

Google will fulfill its mission only when its search engine is AI-complete. You guys know what that means? That’s artificial intelligence.–  (May 2002 )

Okay, so back to me. I am very new to the field. Except for a few dozen lectures on AI, I have almost zero expertise on the related fields. (dah !). This is my personal take on the subject as of now. Its a very very vast subject with many interconnected disciplines and sciences. So it would not be practical for a single person to be an expert on every field. One can be an expert in a handful of related AI fields and that’s it. But as a beginner it would be prudent to focus on all the fields and get a general idea on the basic concepts, kind of how we learn almost everything in school and then we use that knowledge to decide on what type of direction we wish to take for our graduate studies.

So in the coming months I am hoping to learn the basics related to AI (the smallest stuff). As a documentary of what I am covering I will be continuing this article series.

The artificial intelligence tasks are divided mainly in to three categories.

  1. mundane tasks
    • Perception (Vision and Speech)
    • Natural Language (Understanding, Generation, Translation)
    • Common Sense Reasoning
  2. formal tasks
    • Mathematical Proofs
    • Playing Games
  3. expert tasks
    • Engineering
    • Medical Diagnosis
    • Analysis

At the first look it seems like since we are yet to get the mundane tasks working in AI we are far far away from the expert tasks. But the irony is we have already made significant practical accurate AI systems which are doing expert tasks even though we still are baffled with how to get the mundane tasks working.

The Knowledge based Expert systems have been in use for years now and many of the day to day systems relay on such AI systems even without us knowing. The reason for expert tasks to be easy to implement in AI is because as the tasks get more specific it is much easier to teach and/or learn (for a machine) in comparison to learning common sense.

We humans on the other hand are very good at picking up common sense but it is harder for us to become experts in some field. The difficulty of trying to give a computer the ability of common sense was strongly stuck in my brain few years ago while listening to an online lecture from Prof. Patrick Winston. He gave the following example.

Imagine a man who is walking with a water bucket on his left hand.

Now we with our common sense know lots of things about this situation. But unless we specifically told the computer, it will never guess that ‘the man will be slightly bent towards his left side’

Going future with the example he also showcased that if the man is running then what would happen. Then by common sense we know that the water in the bucket will probably be spilling, his trousers and feet might getting a bit wet and so on. That is our common sense. A computer program does not have that ability.

Yes we can give it a huge knowledge base of past events then it will know from a past video or something that if a man is running with a bucket of water then it will be spilling. But we humans have an amazing ability of generalizing and applying the knowledge gained through different experiences to create one of the greatest tools in our arsenal, the common sense. If we see a body of water then we have common sense to jump in to the swimming pool and not the water well, to wash our hands from the tap water not from the water in the gutter, to drink from the water filter and not from the dog bowl. Even though its all water we have common sense to figure out the correct thing to do (at-least most of the time).

So I begin my journey learning about a small paradox in AI where it can do expert tasks such as medical diagnosis but not the simplest tasks such as perception. Seems its a good start for an interesting field :).

Next on : A Journey in search of AI 02 – (to be decided)



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