If you think that AI cannot replace computer programmers in the future, you are wrong! This is the dream of researchers: building a machine that could build other machines.
Recently, Jeff Dean, one of Google’s leading engineers, announced a new project called AutoML. ML stands for Machine Learning, if you want to know more about the differences between Artificial Intelligence and Machine Learning, I made an entire video about this, and I’m going to put a link to it right up there. Put it simply, AutoML is a machine learning algorithm that can create other machine learning algorithm. As you can imagine, in the long term, this technology may replace computer programmers.
If you are already familiar with machine learning, you know how much it requires mathematics. Did you know that approximatively 10.000 people worldwide have the knowledge and experiences needed to build these complex mathematical algorithms needed in the real world? Between us, if you are planning to be a machine learning engineer, I want to emphasize that the tech giants (google, facebook, Microsoft), are paying millions of dollars a year to keep their AI talent. This lack of AI talent is the reason why AI has not impacted the economy for the moment. All the research and investment have a tiny effect on productivity, and this is due to a lag in the adoption and effective use of AI.
The vision of Jeff Dean is very easy to understand: “the work we are working on will help companies build systems with artificial intelligence even if they lack extensive expertise”. Artificial Neural networks are computing systems inspired by the biological neural networks that constitute animal brains. Such systems can learn tasks without explicit instructions by considering examples. To have a neural network to learn a specific task, researchers are first running 10, or even 100 of experiments to find the right algorithm. It’s hard to find because it depends on so many factors. It can depend on the size, quality, and nature of data, but also on how much time they have. They also have to do many adjustments over and over until they obtain an algorithm that works well. Sometimes, it’s hard to explain to them why they did a particular adjustment. In fact, they may not know themselves! It’s like magic. Nowadays, those algorithms are like a black box that we don’t understand.
AutoML has been created to automate this process. I personally believe that if something can be automated, it should be automated. The results are promising: Google announced that AutoML built an image recognition algorithm that is more effective than those created by humans.
You can see the video related to this article here:
Thank you so much for reading guys, that is the end of Article 106. As always, I’m here to help. Hit me up on any of my social media below and stay in touch!
FOLLOW MY INSTAGRAM 😊- http://instagram.com/selimchehimi
FOLLOW MY TWITTER- https://twitter.com/SelimChehimi
Subscribe to my newsletter down below to get your free eBook and learn the basics of Artificial Intelligence.