This AI writes better songs than Nirvana or Pink Floyd

Is it still necessary to have a soul to compose good songs? Well, surely many artists will tell you yes, but that is a statement that is more distorted every day, or at least, further from reality than ever. The TickPick company has put the artistic creativity of machines to the test through a curious as well as revealing experiment.

The first thing he did was take the lyrics of thousands of songs from the genius.com website and fed them to 4 artificial intelligences through a text generation algorithm called GPT-2. From here, each of these intelligences has been trained between 5 and 12 hours to specialize in a different musical genre: rock, pop, country and hip-hop / rap. Considering that an AI is capable of reading 186 times faster than a human, that dozen hours of training is quite a considerable amount of time.

After having put the batteries brooding the style and the way of composing the letters, each AI has generated a hundred original songs for each of the musical genres analyzed. At this point, TickPick has come across 4 records written by 4 completely artificial artists: Rockin 'Robots, Young AI, Cowboy Computers, and Artificial Pop. The next step, show those song lyrics to other people and take a survey to rate their opinion on this curious artistic material.

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More creative and emotional lyrics than Adele or the Beatles

The directors of the experiment showed the respondents 4 songs, 3 of them by well-known artists such as the Beatles or Pink Floyd, along with 1 song composed by one of these machines. Respondents had to indicate which was their favorite song and then try to guess which of them had been written by an Artificial Intelligence.

The results were amazing. 65% answered that the letters created by the AI they were the most creative. And the truth is that with texts like this we cannot say that they lack reason:

When clouds part to reveal a man in the wilderness outside the pale light of morning, a secret within the door can hear him say, the clouds will reveal what I mean.

(When the clouds part to show a man in the desert out of the pale morning light, a secret inside the door can hear him say: the clouds will reveal what I mean.) "

They were then asked about the most emotional songs, and almost 40% had no qualms about admitting that Artificial Intelligence lyrics were better than Adele, R.E.M. or Johnny Cash. Who could contradict them? They have already beaten me with lyrics like this:

I stand alone and think it's better to be alone. Lonely days, I just can't find the will to go on. I'm in this state, and my eyes show me that I've been taken.

(I am alone and I think it is better to be alone. Lonely days, I just cannot find the will to continue. I am in this state and my eyes show me that they have taken me.) "

At the time of choosing his favourite song the AI ​​was not so lucky, only 16.9% chose the letter of the machine as their favorite. There is still hope for the human race!

I got my rig in the back of my Beemer. Professional when I graze, I'm professional when I argue. 40 glass, I'm laughing at that s ***, I'm roaring at that s ***.

(I have a hottie in the back seat of my Beemer. Professional when I slap you on the face, I'm a professional when I argue. A cubata, I laugh at that shit, I break the box with that sh * ***.) "

The most difficult genres to imitate

The experiment also revealed which genres are the most difficult for an artificial music composer to tackle. Respondents had trouble differentiating which were the pop and country songs written by Artificial Intelligence. In the case of rock, many respondents were convinced that some of the songs composed by the AI they were so emotionally charged that they had to be written by My Chemical Romance or Nirvana.

Now, when it comes to hip-hop things change, this being the most difficult genre for machines to imitate. Something that we can understand if we consider that the syntax used in rap songs is much more complex and difficult to interpret by these learning algorithms.

We can find all the information about this experiment on the TickPick website.

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