AI-Made music vs Human-Made Music: which is more attractive?
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AI-Made Music or Human-Made Music: Which Is More Attractive?

An AI-made music is a song in which computers compose without human supervision. Last year, Google launched Magenta, a project aimed at pushing the limits of what Artificial Intelligence can do in the area of arts. So will Artificial Intelligence just start making music? Just like humans, AI’s can learn to make music, but once mastered they are perfect at it. AI’s learn music compositions using algorithms.

“We trained the NSynth algorithm, which uses neural networks to synthesize new sounds, on notes generated by different instruments,” said Douglas Eck, the team’s leader in San Francisco, California. “The ‘SketchRNN’ algorithm was trained on millions of drawings from our Quick, “Draw!” game. Our most recent music algorithm, Performance RNN was trained on classical piano performances captured on a modern player piano. [ref: sciencemag]

AI-Made Music In Avia



Also, Avia Technologies is one of the leading startups in the field of AI-made music. Pierre Barreau, Denis Shtefan, Arnaud Decker, and Vincent Barreau founded the composition just last year in Luxembourg and London. They created an AI system called “Aiva” (Artificial Intelligence Virtual Artist) and taught it how to compose classical music. Aiva’s musical pieces pose as soundtracks for film directors, advertising agencies, and game studios. [futurism]

On February 2017, the Team was invited to participate in the highly-acclaimed European Film Market in Berlin, as well as the Artificial Intelligence in Business & Entrepreneurship (AIBE) Summit in London. Before, the team were backed by Lux innovation’s incubator program, and have even earned appreciation from Xavier Bettel, the Prime Minister of Luxembourg. The group released its first album called Genesis, as well as many single tracks. Aiva recently became the first AI-made music to acquire the worldwide status of Composer officially. [futurism]

Aviva’s technology relies on “deep learning” algorithms which use reinforcement learning techniques. Although only loosely based on the human brain’s neural structure, it helps to think of it that way. Deep learning is a unique type of machine learning. Whereby multiple layers of “neural networks” are for processing information between various input and output points. And this allows the AI to understand and model high-level abstractions in data. Such as the patterns in a melody or the features in a person’s face.

According to the team behind Avia: “We have taught a deep neural network to understand the art of music composition by reading through a large database of classical partitions written by the most famous composers (Bach, Beethoven, Mozart, etc.). Aiva is capable of capturing concepts of music theory just by making this acquisition of existing musical works.” [futurism]

AI-MADE MUSIC TAKING OVER HUMAN-MUSIC?



Can AI-made music be more creative than Human-made music? That’s a question bordering on the philosophical, but artificial intelligence (AI) can certainly make very creative music that people find pleasing.

No matter these people are businessmen or researchers, these teams are trying to answer the same question: can machines generate music, employing AI technologies like neural networks to train upon a catalog of human-made music before producing their own? But these companies’ work postures another significant question: if machines can create music, what does that mean for professional human musicians?

“I’ve always been fascinated by the concept that we could automate, or intelligently do, what humans think is only theirs to do. We always look at creativity as the last bastion of humanity,” says Mahdavi. However, he quickly decided not to pursue his first idea. “Could you press a button and write a symphony better than humans’?” Why not? “It’s very difficult to do, and I don’t know how useful it is. Musicians are queuing up to have their music to attract their audience, thus, to get on stage. The last thing they need is for this button to exist,” he says. [The Guardian]

Ed Newton-Rex, the CEO of Jukedeck, another company engaged in the AI music field, emphasizes that the music generated by such machines is not for competition the work of human artists. “It’s a bit of a false competition,” Newton-Rex remarks, “…The aim [for AI music] is not ‘will this get better than X?’ but ‘will it be useful to people, will it help them.’”. But Newton-Rex’s declaration has not entirely dispelled the sense of rivalry between AI music and human-produced music. Its lightning progression took into account; artificial intelligence could very well surpass human intelligence at some distant point.

AI-Made Music or Traditional Human-Music: Which Is More Attractive?

Contrary to the popular beliefs, computers are almost very perfect in what they do, and they can go as far as any human stops. But surely these robots need humans to survive and act on commands. Studies show that AI-made music is in fact as perfect as human-made music. Gaetan Hadjeres and François Pachet experimented the Sony Computer Science Laboratories in Paris. Therefore, proves that. That is the institution that gave us the first Artificial Intelligent pop song. (Though that had quite a bit of help from humans) and has used its AI music software FlowMachines to mimic musicians ranging from Mozart to the Beatles. [The Verge]

DeepBach’s (Hadjeres and Francois’s AI) compositions even fooled people. The team asked more than 1,600 people — a fourth of whom were professional musicians or music students — to listen to two distinct harmonies of the same melody. The results showed that more than half the listeners attributed DeepBach’s-generated harmonies to Bach. While 75% of listeners were able to identify Bach’s music. “We consider this to be a good score knowing the complexity of Bach’s compositions,” said Hadjeres and Francois.
We can’t indeed conclude if the AI-made music is more attractive than human-made music, but what we know for sure is that AI-made music is faster, easier to make, and incredibly reliable.

Conclusion



We conclude that it’s an iterative process. In fact, new technologies that make a difference in art take some time to figure out. AI-Made Music is similar to an electric guitar. Rickenbacker and Gibson electrified guitars so that they produce loud sounds enough to compete with other instruments onstage.

Jimi Hendrix, Joni Mitchell, Marc Ribot, St. Vincent and a thousand other guitarists pushed the envelope on how to play this instrument. We’re all using the instrument the wrong way, some said—retuning, distorting, bending strings, playing upside-down, using effects pedals, etc. No matter how fast machine learning advances regarding generative models, artists will work faster to push the boundaries of what’s possible there, too.

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