Road to UEFA Champions League

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Photo by Mitch Rosen on Unsplash

Football. The most popular sport in the world. A concentrate of passion, hope and romanticism. Every year thousands and thousands of teams compete in their leagues with different purposes. Some of them are built to win the title. Others just want to not be relegated.

But the answer to their hopes always relies on the same thing: numbers.

One point more and you succeed. One point less and it’s a failure. One goal more and you are the champion. One goal less and you throw away the all season. It’s a matter of details. Every football fan knows that.


How many points do you need to survive in the Italian league?

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Photo by Liam McKay on Unsplash

Football. The most popular sport in the world. A concentrate of passion, hope and romanticism. Every year thousands and thousands of teams compete in their leagues with different purposes. Some of them are built to win the title. Others just want to not be relegated.

But the answer to their hopes always relies on the same thing: numbers.

One point more and you succeed. One point less and it’s a failure. One goal more and you are the champion. One goal less and you throw away the all season. It’s a matter of details. Every football fan knows that.


Hint #1: to not burn billions of dollars.

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Photo by Jeremy Thomas on Unsplash

Space exploration is more than just a curiosity with respect to unknown places and worlds in the universe. Research in this field brings a number of benefits which cover every aspect of the technology and helps us to create increasingly sophisticated solutions to be applied in the industry that will help humans simplify their jobs.

Since it is not a new research field, we have a precise idea of how the space is, at least in the part closest to the Earth.

But this represents just an infinitesimal part of the entire universe, so we need to go further. As we move away from Earth, new problems come out.


Probably yes. And you don’t even know it.

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Photo by Sushil Nash on Unsplash

Let’s do a simple test.

Search for these keywords on Google: how many inhabitants does Berlin have?

Answer: 3.5 million.

Incontrovertible data, even proposed by Google itself without you having to click on any link. And just to be even more unassailable, the relative date is also provided. 2016.

Another question: who’s the US president?

Answer: Donald J. Trump.

Again, no link to click. Google knows the answer and provides it immediately.

Since you are curious, you don’t stop and keep looking, this time something more demanding: why are riots taking place in the United States?

And here the first alarm bell goes off. Note that the answer is not as immediate as before. …


Based on my experience.

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Photo by Markus Winkler on Unsplash

Introduction

In machine learning when we need to compute the distance between a predicted value and an actual value, we use the so-called loss function.

Contrary to what many believe, the loss function is not the same thing as the cost function. While the loss function computes the distance of a single prediction from its actual value, the cost function is usually more general. Indeed, the cost function can be, for example, the sum of loss functions over the training set plus some regularization.

Another term often incorrectly used as a synonym of the first two is represented by the objective function, that is the most general term for any function optimized during training. …


Maybe. Maybe not.

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Imagine having to undergo a delicate surgical operation and having two possibilities. On the one hand, you can be operated by a robot that has a 90% success rate. On the other hand, you can get a doctor who has an 80% success rate. What would you choose?

Obviously, there are those who would choose the first option, just as there would be those who would choose the second one. The problem is not answering this question.

The problem is: in which circumstances does the robot reach a 90%? On which patients has it been tested? Were they men? Or women? Were they white? …


An introduction to the problems that may arise when it comes to use AI.

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Source: Markus Winkler | Unsplash

The biggest mistake that can be made when talking about artificial intelligence is to think that once asked the machine to perform a certain task, it is only a matter of time before it is actually carried out. A belief which is maybe the result of an extreme trust placed in the machine’s ability to understand the world and our requests.

There are at least two great reasons why this belief is dangerous:

  • A machine is absolutely not aware of the reality that surrounds it. In other words, even if it is terrific in recognizing a pedestrian crossing the road, it has no idea what a pedestrian is. …

A brief consideration after watching the TV series.

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Inspired by the Westworld Season 3 poster. Source: Wikipedia

Ok, for those unfamiliar with Westworld, I’ll try to explain in a minute what it is.

Westworld is an HBO science fiction television series created by Jonathan Nolan and his wife Lisa Joy. In particular, Westworld is a western-themed amusement park set around 2050, populated by robots with human features that are employed to make the visitor experience as engaging as possible. Those who enter Westworld can unleash their most hidden fantasies, becoming any type of person, benefited by the fact that the robots have been designed to do no harm to humans. …


We should change our idea on AI before it’s too late.

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Source: Unsplash

Let’s be honest.

How many times do you see the word “AI” associated with a product or a brand even if the product itself has nothing in common with AI?

Every single day we are surrounded by companies that try to sell the product “X” which amazingly exploits AI to reach the highest level of smartness.

It seems like the word AI has become the new magic word. Everything that includes AI seems to be perfect and ensures a huge number of sells. Then, it’s not relevant if the product is either a toaster or an air conditioner. …


Not exactly what you expected.

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Source: Unsplash

1997. IBM’s DeepBlue computer beats chess world champion Garry Kasparov.

2016. AlphaGo beats Lee Sedol, one of the best Go players in the world.

In both 1997 and 2016, the scientific community reacted enthusiastically to these artificial intelligence victories. But why is there so much to be happy, are we not just talking about board games in the end?

More generally, why is research in this field heavily based on solving videogame problems?

An immediate answer is surely this: because videogames represent difficult problems to solve.

The difficulty is mainly given by the fact that they often have more than one solution and that in most cases they play against an opponent who in turn will try to win at any cost. …

About

Davide Giordano

Artificial intelligence and robotics student. IT engineer. Sports lover.

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