Nov 23, 2021
Artificial intelligence and machine learning allow us to collect the best of the machine and the human being. It is the new open-source technological revolution.
For some years now, experts in artificial intelligence (AI) and machine learning have not ceased to amaze those passionate about technology. Every week we hear or read amazing news related to new achievements in various tasks such as natural language processing, image recognition, or speech recognition (the site https://mediaprojects.biz/ provides examples of using AI).
In short, the difference between artificial intelligence and machine learning is given because the former corresponds to a general umbrella where machines are capable of executing intelligent tasks such as learning, reasoning, perceiving, and solving complex problems. And the second, machine learning, is a sub-discipline of AI that provides machines with the ability to learn a task from data without being explicitly programmed.
The advances discussed often go hand in hand with applications to fields such as medicine, astronomy, agriculture, or electronic commerce. This has generated remarkable initiatives and business models that take the best of the machine and the best of the human.
By the best of the machine, I mean the ability to process, memorize and execute algorithms that allow solving complex mathematical problems that can include millions of decision variables.
I mean expert knowledge gained by generations of communities dedicated to experimenting, modeling, and validating knowledge by the best of humans. This knowledge can be transmitted in different stages of a project; some examples are the definition of the task to be solved, data selection and labeling, the learning model components, or the design of variables with expert knowledge. The human is still in the loop.
This phenomenon has not left political and economic actors indifferent; it is a fact that many of these technologies will change the way we interact, modify the labor market, allow us to explore new ways of teaching, and give us the possibility of creating new products and services...
For example, a person who did not learn to play musical instruments can use artificial intelligence like lava to create his own musical pieces. Or an older adult, art lover, may marvel at infinite works of art created by an artificial neural network at artillery. We can even enjoy a rich hamburger made from plants with ingredients that an AI selected is not.
Some factors that differentiate this technological revolution are a large community active on the web, supporting problem-solving, and sharing its knowledge. And, alongside the above, an open-source philosophy that shares insights and input quickly.
In this environment, prototypes of technological solutions emerge spontaneously. We could say that in this technological revolution, the entry barriers for business creation are lower, at least in the prototype stage.
AI appears to be triggering the well-described knowledge-based economy. Some questions derived from this promising context are: Will we take advantage of this technological revolution to diversify our productive matrix? Will we be able to generate and support technology-based ventures? Will we create the jobs that will be lost to process automation? Will we be consumers or also providers of technologies based on machine learning? Are there spaces for intelligent specialization within our production chains?
The answers to these questions require a deep analysis from different points of view, but a clear factor is human capital. Incorporating these technologies both for the development of technology-based ventures and providing solutions to problems in the national industry will require a critical mass of professionals who assume different roles.
We will need professionals capable of navigating the language of machine learning, adapting available technology (models or algorithms), and why not? Who are capable of developing technologies that generate global solutions. The path is still human capital.