Intro to AI
Mentioning artificial intelligence in a boardroom just a decade ago would’ve labeled you the village idiot. Today, AI is causing unprecedented change. The current and future potential capabilities of AI could ignite profound societal change, whether it will be for better or for worse, we still don’t know. Despite this many of us are still clueless on how AI actually works and how it is being used today by businesses both big and small. For this very reason, I decided to educate myself and share my learnings with you!
I won’t focus too much on the history of AI, but the modern application of artificial intelligence dates back to the mid 1950’s when scholars at Dartmouth College pursued the idea of creating an electronic brain. Millions of dollars of funding were provided by the US government to turn the vision into a reality, however, after almost 2 decades and very little progress, it became apparent that the leaders in AI research had grossly underestimated the difficulty of creating a machine with intellectual capabilities and what is now termed the “AI winter” ensued. 30 years on -circa 2000- Moore’s law had taken effect and computers had become exponentially more powerful; artificial intelligence was once again relevant and funding poured into new projects, accelerating the development and application of the technology.
Now that we’ve got a bit of context, let’s look at the practical application of AI in today’s world, including some every day examples. There are 3 types of artificial intelligence, ranging from 50-year-old -relatively basic applications- to cutting edge machines that attempt to mimic the biological make-up of the brain through the use of neural networks.
Reactive machines make up the most basic component of AI and were the forerunners to AI as we know it today. These machines are, in fact, not intelligent at all and cannot draw on past experiences to inform any future decisions. An example of a reactive machine would be the computer opponent when you play a game of chess on your computer. The program has been ‘preprogrammed’ to recognize the pieces, their possible moves, and other pieces in relation to each other but ignores everything before or after the present moment.
Machine learning is the processes whereby an algorithm analyses large subsets of data to identify patterns, relationships between the inputs and outputs are then established and the effects on one another quantified and recorded for future reference. When the machine comes across these variables in future it will revert back to its records and take the most relevant action. A good example of this kind of AI is your Apple Music App, the algorithm running in the background monitors your music preferences and suggests new music based on similarities in the genres, artists and era of music you prefer.
This is where AI tech starts to get spicy, bear with me on the description! Deep learning programs map out a set of virtual neurons and then assigns random numerical values, or “weights,” to connections between them. These weights determine how each “neuron” responds—with a mathematical output between 0 and 1— and allows the program to recognize features such as the edge of an object in an image, a shade of blue in a painting, or even a particular energy level in a frequency of sound or speech. An incredible example of this new technology is speech software being developed by Microsoft that translates conversations from English into Mandarin in real time! Facebook is also experimenting with this technology to create object recognition in pictures uploaded by their users.
This level of intelligence requires massive amounts of computing power and vast data resources. Exciting developments in quantum computing are driving rapid development in this area of AI. To understand quantum computing in more detail, take a look at my colleague’s article Click Here that was posted on our blog a few months ago!
So, what does the future of AI mean for us mere mortals? Well, the answer will vary depending on who you ask. Brilliant minds such as Stephen Hawking and Elon Musk have relayed their fear of AI getting out of control unless proper controls and legislation are implemented, reason being that the technology could cause massive job disruption. On the other side of the fence billionaire Mark Zuckerberg believes that AI will bring with it huge improvements in the quality and equality of human life through things such as the early diagnosis of diseases and self-driving cars.
Either way, in a field that attempts something as profound as modeling the human brain, we are sure to see things that were only ever dreamed up in Sci-fi movies!