Developments such as Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL), have begun to impact the solutions of the audiovisual industry.

Andrea Mereghetti *

We already left in the past one of the most controversial years in the history of humanity, we reached a level of social stress that I think is comparable only to past events such as the Red Brigades in Italy, the Cold War (USA and the former USSR) and the threat of a nuclear war, just under 30 years ago. Characters such as Donald Trump, Kim Jong-un, and other populists around the world have defined and are defining our future and how to perceive what will come.

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Alan Touring, Mathematician and brilliant mind, the father of the Science of Computational Theory and Artificial Intelligence (AI), in addition to "Codebreaker" in World War II, received official apologies in 2013 from the British Government of Gordon Brown , after his suicide at the young age of 41 years, for having been discriminated against and humiliated for his homosexuality.

His is the "Test Touring", which for decades was indicated as one of the tests par excellence to recognize if it was interacting with a machine or a person, is it still valid? What are the tools available to define or realize the differences? Well, there is not.

These technologies (AI) are defining our lives and little or nothing is being done to protect us. In 2017, taking the 1 laws of robotics defined in the 1942 by Isaac Asimov (famous writer of the last century, author of the Trilogy of the Foundation, I Robot, and many other science fiction stories) the European Union made a first attempt to reduce a possible impact on society.

Elon Musk, one of the visionaries of this century, on different occasions emphasized that it is time to regulate Artificial Intelligence (AI) before it is too late, it is surprising and at the same time fascinating as SpaceX (one of its companies) , in addition to Tesla) could make a composite tube can return from the atmosphere and land (after a period of learning) without apparent problems and can be reused in a short time. How they did it?

Lars Blackmore2 graduated from MIT wrote algorithms (Machine Learning) that could learn according to variables related to their environment and make an unmanned vehicle can define its route, reaching its final destination (obviously he works in SpaceX now). Or as Waze that also supports Machine Learning to define the best route, maybe without considering many external variables (like the ones we have in CDMX). Curious case is what happened in New Jersey, where for a period of time the best route to get to New York was going through a small town named Leonia, and the mayor decided to close the streets to avoid the increase in traffic. Will the algorithm learn from man's unpredictable decisions?

Did you see what they achieved in Boston Dynamics3 by applying AI and ML? They designed and programmed a humanoid robot named ATLAS and its puppy SPOTMINI4, which are capable of running, jumping, avoiding obstacles, carrying weights, if they fall they get up and also work as a team. Obviously all financed by the Department of Defense of the United States of America (DARPA5).

Today these technologies are available, maybe not yet for everyone, but it is no longer necessary to have a "Master Degree" in mathematics or be an experienced developer. We have access to many APIs to be able to create applications, services that support neural networks and algorithms of Artificial Intelligence, Machine Learning, or Deep Learning, from Google Cloud Platform to Amazon ML, or as Microsoft Azure ML, IBM Spectrum, Intel Nervana, among other.

It is important to understand what the differences are, since with all these terms it is easy to get confused, we can say that ML and DL are ramifications of the AI.

With "Machine Learning" it is understood what a computer can learn from what a human does, for example, repeating analyzes, identifying patterns and applying logical solutions, learning from the result and remembering it.

And with the term "Deep Learning", as a big difference, it is understood that you can learn and write your own code to apply improvements and obtain the result. Amazing examples were obtained by Facebook where a set of BOTS6 algorithms reached a level where they developed a language that man could not understand (the engineers ended up turning off the machines); or what Google7 managed to do, synthesizing the first digital voice without being able to distinguish it from the human one, with learning algorithm ML and DL.

Prestigious universities such as Harvard, license their Deep Learning platform with the private sector to develop new materials for display and lighting with OLED technology.

With the "Deep Learning" multinational companies in the technological field are defining our future, solve problems of the current world and make computers act and think like humans; for example, imitating the functioning of our brain, they can analyze a photo or video and generate a descriptive text of that image, not only of who or what it is, in what place or setting, and everything with an accuracy of 93.9% .

And in the digital signage industry? All this is already being applied, and the Mexican Digital Signage Association (DSMX) is very aware of its evolution and measuring impacts, regulating and promoting the correct application. Audience measurement is based on ML algorithms and Neural Networks, which learn from experience and become more accurate over time.

In Slovenia8 the experience of the users in a departmental store is molded so that the ML algorithms are in charge of defining the patterns and, with the correct signaling, communicate effectively and in real time. All this will become predictive by applying DL, controlling the manufacture and distribution of products, anticipating the needs of consumers, efficiently, without human intervention. And as if it were a Black Mirror story, the machines will be able to create new products, to become creative and one day not too distant, to dispense with the human being?

* Andrea Mereghetti is CTO of the Mexican company Kolo DS. Text edited by Boris Dallafontana, MKT Manager of Kolo DS.

References:
1 https://blogthinkbig.com/las-6-leyes-de-la-robotica-de-la-union-europea
2 http://www.larsblackmore.com/stochasticcontrol.htm
3 https://youtu.be/fRj34o4hN4I
4 https://www.youtube.com/watch?v=rnTyzwpz4JI
5 https://es.wikipedia.org/wiki/Defense_Advanced_Research_Projects_Agency
6 https://www.forbes.com/sites/tonybradley/2017/07/31/facebook-ai-creates-its-own-language-in-creepy-preview-of-our-potential-future/ - 221b61d9292c
7 https://www.theverge.com/2016/9/9/12860866/google-deepmind-wavenet-ai-text-to-speech-synthesis
8 https://www.researchgate.net/publication/290365887_Modelling_In-Store_Consumer_Behaviour_Using_Machine_Learning_and_Digital_Signage_Audience_Measurement_Data

Richard Santa, RAVT
Author: Richard Santa, RAVT
Editor
Journalist from the University of Antioquia (2010), with experience in technology and economics. Editor of the magazines TVyVideo + Radio and AVI Latin America. Academic Coordinator of TecnoTelevisión & Radio.

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