Slowly, I basically begin to understand Artificial Intelligence…
Warning: This article is completely rudimentary and may explain concepts that you the reader already know.
First a little bit of new history. I got re-introduced to Artificial Intelligence by the Facebook AI masterclass. Prior to the time I had no interest whatsoever in Machine Learning as the whole idea of data crunching had never appealed to me. I have always had the feeling that people who ogle over data are voyeurs, and that always left some sort of bile in my mouth.
Now for a little bit of old history. I have always been fascinated by robotics and automation. The way a machine could effortlessly handle task that a human could exert more time and energy on.
LITTLE DID I KNOW THAT IT WAS ALL CONNECTED!
Okay in this article this is my aim:
- To define Artificial Intelligence (AI), Data Science (DS), Machine Learning (ML), Automation and Robotics.
- To tie it all together using one simple/crude analogy.
Now for some very simple definitions:
AI according to wikipedia:
Artificial intelligence (AI, also machine intelligence, MI) is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals.
I learnt something at a meet up recently where the facilitator said to define a concept without using the original word in it.
Here’s what how I define AI:
Intelligence which is possessed by machines as handed down to it by man.
I understand that it sounds very contentious, but, please bear with me as it soon become very clear to us what I mean by the definition (in a follow up article to this one).
DS according to wikipedia:
Data science is a “concept to unify statistics, data analysis and their related methods” in order to “understand and analyze actual phenomena” with data.
The definition above is completely satisfactory to how I’ll eventually tie it all together.
ML according to wikipedia:
Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
It must be noted that ML is actually a subset of AI
Automation according to wikipedia:
Automation can be defined as the technology by which a process or procedure is performed without human assistance.
Simply put a repetitive task performed by machines instead of humans OR without human intervention.
Robotics according to wikipedia:
Robotics is a branch of engineering that involves the conception, design, manufacture, and operation of robots. This field overlaps with electronics, computer science, artificial intelligence, mechatronics, nanotechnology and bioengineering.
Worthy of note about the definition of robotics is that second part expressing it as a field which overlaps with other fields.
HOW DOES IT ALL TIE TOGETHER?
As I said I will make use of one simple analogy. I am fascinated by TV/devices remote control. Imagine how much more excited I get when I don’t have to reach for the remote control when I have already pre-tuned programs and the channel switches automatically based on programs that had already been marked by me on the viewer guide of my satellite TV… Too unrelated to AI, yes?… We are going some where with this based on what I have learned about AI.
It is to be noted that I’m not one of the school of thought that computers may or may not take control of the world. I see it as 1:1 chance of it happening. Meaning man has a chance a doing something to bring an end to machines taking over completely as much as machines can completely take over.
Back to the Satellite TV example. I envisage a lot of readers of this article will be primarily from Africa and hence are familiar with the Satellite company: DSTV. To tie the concepts defined above together:
I buy a DSTV decoder which comes with a remote control and document with a program info guide which tells the schedule of programs across channels. So therefore whenever I sit to watch the DSTV, using the program guide, I can easily switch across channels. DSTV comes with a feature whereby using my remote I can pre-program shows that I want to watch and when the time comes for such shows to run, the decoder automatically switches to the channel. Neat right?
Over time, it becomes obvious to my decoder what programs I “prefer” to watch. Imagine for one second that my decoder is able to load data about my taste in TV shows to a database and then my decoder company decides to go into making radios. Now, when I purchase a radio, the decoder company based off on the data which it possesses about my preferable listening habits can then decide to compile for me a listing of shows which I’m interested in and auto-switch from one channel to another based off on what “it” thinks I may “prefer” listening to at that point in time!
This is a simple recommendation system which harps on DS to build an AI. The AI having undergone ML based off on a graph drawn on the selection of my shows against the time I tune in to watch those shows. The whole process is now automated for me that my radio can now actually be described as a robot!
ALL SYNCED! YAY!
If that was too much of explanation in one block of paragraph, here are the breakdown steps:
- Purchase DSTV decoder.
- Pre-select and lock in show times based off on schedule data provided by DSTV.
- Say DSTV has a central databases to which my “preference” data is uploaded.
- Say DSTV decides to go into the radio business.
- I purchase a DSTV radio.
- Based off on the my “preference” data available to DSTV, she can now auto-select my shows for me and play-time whilst changing from one channel to another automatically!
- MY VERY OWN ROBOT!
It is to be understood by the reader that this is albeit a very crude explanation of the general concept of AI, but, as time progresses, I’ll continue sharing what it is I’m learning about AI with a keen interest on ML and an even keener interest in automation and computer vision. I’m fascinated by the subject matter.
Well, many thanks for reading this far!
Many thanks to Robert John and Peculiar Ediomo-Abasi for reviewing the draft. Thank you!
