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AI Bots Pick The Hits of Tomorrow
Wolverine Inspector writes "The Music Industry uses a product called HSS (Hit Song Science) made by Spain's Polyphonic HMI. According to The Guardian "while no one's talking about it, it seems that the whole record industry is already using AI to choose hits. From unsigned acts dreaming in their garage, to multinationals such as Sony and Universal, everyone is clandestinely using a new and controversial technology to gain an edge on their competitors."
Even though it costs about $5,200 US/$6,500, many artists are starting to buy it to help them write succesfull songs."
This is not AI. The music companies are using clustering technology.
The basic idea is that you measure certain characteristics of a song,
such as voice quality, cadence, etc. I'm sure the actual
characteristics used are much more complicated, but the idea is the
same. Once you have your characteristics you can build a three
dimensional vector out of a song. After you have your three
dimensional vector, you can then use many different algorithms, one
such is the Bi-secting K-means algorithm to group the songs together.
After you have built your cluster, you take a new song, run it through
the process and check to see how close it falls to a "hit" cluster.
We use this same process for document classification at my work, and I
don't think it bears any relation on AI. As I stated above, it's a
rather simple grouping technique.
There is a downside to this technology though. By measuring how close a
song is to previous hits, you are guaranteeing that all new songs will
be similar to old hits. This type of system tends to minimize or
eliminate fresh new types of music.
(why the word wrapping? Emacs auto-fill-mode)
Doug Tolton
"The destruction of a value which is, will not bring value to that which isn't." -John Galt
This was discussed last November, which was a repeat of the same tech from February.
A quick search for "polyphonic" in the music category would've easily picked this up, they're the only 3 matches!
Oh really? Because many people are composing actual music today right? ...
Britney Spears, et al != Current Music
There is other music out there.
... are intricately related. Many AI techniques are forms of statistical inference or statistical classification techniques. Some neural nets implement grouping techniques not that different from k-means.
Any box which learns from a set of data in order to predict future data by implicitly extracting trends and patterns from that data is an implementation of some form of statistical inference algorithm and is subject to all of the general results statistics has to offer about such algorithms. Conversely, statistical inference algorithms are often implemented in ways associated with AI, for example as neural nets.
Given this situation, it's hard to define the boundaries that separate artificial intelligence, pattern recognition, statistical inference and classification and the rest. Of course, there is a legitimate question as to whether such techniques actually mimic genuine intelligence even in principle, and there are other approaches.
From the point of view of terminology, there is a huge range of techniques that can be called AI, and statistical inference is one of them. If you call a VLSI neural network implementing a statistical inference algorithm "AI", then why not call a normal computer implementing a statistical inference algorithm "AI"? Besides, AI sounds a hell of a lot sexier than statistics when you're trying to extract maximum dough from the ample coffers of the recording industry.
"The Milliard Gargantubrain? A mere abacus - mention it not."
In the field of machine learning, it's considered a major no-no to quote performance figures based on your training data.
The typical way to validate your results is called an N-way cross-validation. You split the data into N parts, and perform N training runs. Each run uses N-1 chunks to train, and tests on the remaining chunk. Then you average the results to get a general performance estimate, or you can use a T-test to compare the results against another algorithm.
This report would have been rejected immediately from any academic journal of any significance. It's a fucking joke.