While at this moment most of the large organizations are probably thinking about learning systems, and how such learning can be used in some way to gain competitive advantage, I invite you to think of something else, or different: thinking about thinking systems.
In other words, the big challenge today is not, anymore, find learning models and translate it to algorithms, since machine learning is ready to do this, but how to achieve real artificial intelligence evolution using machine learning before your competitors discover it.
And what is real artificial intelligence evolution? In my opinion, thinking systems!
But I know that this is not an easy problem since most of the organizations must build a data science and machine learning substrate, to start thinking about such systems. And this is the good news — at least to who are heavily investing in technology — since it’s not clear to everybody that there is a great opportunity, and risk, behind the AI hype.
To a better understand about what I’m talking about, machine learning is focused on answer questions, most of them regarding the future, but artificial intelligence evolution needs create, autonomously, the questions that will find the right answers, in a completely new way.
Or, if you prefer, machine learning is looking for intelligent systems, while the future of artificial intelligence looks for wise systems, that think, autonomously.
By Rogerio Figurelli at 05/29/2020