Artificial Intelligence and Us

May 22, 2017

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What is AI?

The origin of AI (Artificial Intelligence) begins in 1950 with an English Mathematician by the name of Alan Turing, he published a paper entitled “Computing Machinery and Intelligence”. This then opened the fields of which would later be called “AI”. The term “Artificial Intelligence” was first coined by John McCarthy in 1956 when he held the first-ever academic conference on the subject.

AI has been studied for over 60 years and is constantly advancing. It is one of the vastest subjects in computer science, this is ultimately due to how nebulous the subject matter is.

What counts as AI?

Over the years, AI has conjured up an image of an “all-powerful supercomputer”, with either innovative or catastrophic potential. However there is tech we use every single day, that is in-fact “artificially intelligent” such as predictive advertising, voice recognition, predictive texting, chat bots, the list goes on.

AI is integrated into the very fabric of things that we use every day such as smart cars, video games, applications, and VA’s (Virtual Assistants).

We are not quite at the Tony Stark (Iron Man) level of AI with our own “Jarvis” at our beck and call, but we have the next best things, Siri & Alexa for exampe.

But, what classifies something as artificially intelligent? By the term artificial, for something to be “artificially intelligent,” it cannot be of natural descent but crafted and designed by humans. The paramount ingredient for a device to be classified as an “artificially intelligent mechanism” is it must be “intelligent”, in these terms a device that is able to perceive its environment and take necessary actions to maximise its chance of success at a given task.

The vernacular term for artificial intelligence is applied when a machine imitates human functions and decision making that would usually only be associated with human minds, not in the subjective form of rational thought but “learning” & “problem-solving”, this is also known as machine learning.

ML branches off from AI into its own category followed by deep learning and predictive analytics. To summarise, let’s say we wanted to teach an artificially intelligent bot how to walk up a set of stairs, instead of teaching it to lift its left leg then push up and vice versa, you would show the bot 5000 videos of people walking upstairs correctly and 5000 videos of people falling down them. Then let the bot decide which is the best way to do its job based on the evidence and data it has access to.

Google Translator

One of my favourite examples of Machine Learning is when Google Translator created its own language – it’s genuinely impressive and not nearly enough people know about it, see below:

Google Translator for numerous years has been translating languages of all tongues and has continually been collecting and building data from all of the translations, using that data it has been able to make connections between the different languages and ultimately create its own artificial language in order to translate more efficiently. Google Researchers say that in a sense, Google Translator has created a new common language, one that is only relative to the function of translation and is unreadable and unusable for humans.

It has been able to do this via the Google Neural Machine Translation that had gone live last September (2016), the idea was that “If you teach the translation system to translate English to Korean and vice versa, and also English to Japanese and vice versa… could it translate Korean to Japanese, without resorting to English as a bridge between them?” The conclusion is yes! It produces “reasonable” translations between two languages that it has not explicitly linked in any way.

This then sparked a debate between the researchers to say that if the GNMT could translate equivalent words and phrases not previously linked to each other through understanding those words and phrases then does the computer understand the meaning behind those words?? Cliffhanger.

AI and Society

We as a race have reached one of our peaks of technology advancement. That we can have robots communicate to one other and have AI’s show us items we want without us realising we want them yet. This raises the question of impact, what impact could all of this have on us as a race?

Have we become lazy? Do we rely too heavily on technology in our every day lives? Will computers eventually replace menial jobs? Is technology doing all the hard work while we slack off? Or are we really intelligent because we’ve realised that computers can do a lot of the hard work for us?

There’s lots of opinions about the future of AI and the human race, some say it will complete us, some say it will end us, one of the greatest minds of our time, Stephen Hawking, shares an opinion with the latter group – he put it bluntly…

“The development of full Artificial Intelligence could spell the end of the human race” – Stephen Hawking’s

What are your thoughts?

This article is courtesy of Claire & Harry