This post is the first in a series of posts about the “Fallacious Simplicity of Deep Learning”. I have seen too many comments from non-practitioner who thinks Machine Learning (ML) and Deep Learning (DL) are easy. That any computer programmer following a few hours of training should be able to tackle any problem because after all there are plenty of libraries nowadays… (or other such excuses). This series of posts is adapted from a presentation I will give at the Ericsson Business Area Digital Services technology day on December 5th. So, for my Ericsson fellows, if you happen to be in Kista that day, don’t hesitate to come see it!
Artificial Intelligence (AI) is currently touching our lives, it is present on your phone, your personal assistants, your thermostats, pretty much all web sites you visit. It helps you choose what you will watch, what you will listen to, what you will read, what you will purchase and so on. AI is becoming a cornerstone of user experience.
Today, if you look at AI cutting edge technology, you must conclude that you can no longer trust what you see and hear. Some neural network techniques allow researchers to impersonate anybody in video, saying whatever they want with the right intonations, the right visual cues, etc. Neural networks are creating art piece, for example applying the style of great paint masters to any of your photography.
Soon, it will become even more relevant to your everyday life. We can already see looming the days of the autonomous cars. Eventually it will be all transportation, then regulation of all technology aspect of our life and even further…
The Artificial Intelligence technology reach growth is so fast and so transformational that we sometime have the impression that it must be all easy to apply. But is it so?
AI may look easy if you look at all the available resources, all the books available. The plethora of online courses, you cannot visit a web page nowadays without getting a machine learning course being proposed to you! There are tons of video available online. From those courses, but also from enthusiasts, or university teachers. And if you start digging in the available software frameworks, you’ll find plenty of them.
So why would someone like Andrew Ng, one of the world’s best-known AI expert would come forth with the mission of training a million AI experts? Well, Machine Learning, Deep Learning and Artificial Intelligence knowledge is still sparse. Big companies have grabbed a lot of the talented peoples leaving universities empty. A lot of Universities still don’t have programs dedicated to that topic. For those who have courses, most only propose a couple of introductory courses. Then from the online front, there will be countless number of people who will start to learn but will abandon it along the way for many reasons. Online course completion rate is much lower than University program completion rate.
Moreover, this is quite a difficult subject matter. There are many considerations which are quite different from what you would have from a software development background.
A first complexity, not enough skilled and knowledgeable peoples, a smaller community than say: web programming.
Stay tuned for my next post which will tackle the next complexity: the piling and proliferation of frameworks.