Héctor creates scripts to equip resources in the cloud for the pharmaceutical company where he works. When asked about the business, he answers: It doesn’t interest me.
Mario is a Kaggel Master. His passion is data science. He knows all the resources to find relationships between variables. The names of the columns in the tables he likes are: column1, column2 … The content of the columns? He’s not interested. His part is the pure abstraction. Content is a business thing, algorithms are his.
Jonás gives a pleasant talk about AI. At the beginning of it he starts with Unity, a video game engine. On the screen you can see two dolls lying on the floor. Jonás applies an algorithm so that they learn to walk. The dolls stiffen as they move shoulder height away from the ground. While continuing his talk, the dolls perform jerky and random movements. Little by little they crawl. At the end of the talk he returns to Unity. In the half an hour that the speech had lasted, the humanoid agents have risen and done something similar to walking. The algorithm worked.
Fernando, organizer of one of the AI events, is the technology director of a well-known savings bank. The relationship between talent and business? It’s difficult, he answers. In a competition the contestants found an almost perfect correlation between two variables unknown to them. One variable was the date of abandoning an insurance policy. The other was the death of the insured. We already knew that correlation, he says with a sneer.
One tends to say that there is no talent. They lack new skills in Big Data and AI. But the truth is that there are thousands of young people who enjoy using, refining and creating algorithms for problems they invented themselves, purely for fun. It’s the geeks. Smart, restless and creative.
On the other side there are companies that, day by day, prevent themselves from tackling new projects. Innovative projects, those which we hear so much about. They don’t even know what can be done, it sounds like they should do something, but they don’t know where to start.
Traditionally, the IT specialists of a company knew everything about the business. Programmers knew about policies, stores or checking accounts. Today it is difficult to find someone who knows as much about Deep Learning as payroll.
The gap between business and geeks is enormous. The former does not know what algorithmic resources exist. The latter does not know what practical matter to apply their wisdom. The result is a gigantic waste of talent.