#8

after a little more consideration i’m a little embarrassed about posting this in the first place. the phrase “AI” seems to be used purely as clickbait here - for me (and probably for many people who will encounter headlines about this project), talking about “AI” takes me out of reality and into a sci-fi daydream almost immediately. it seems like it could be a cool ML tool, but i can’t help but feel the project is selling a lot of… snake oil. or at least it isn’t being honest about what’s really happening and is relying on the audience not thinking about it too much. and it seems to be working! this project seems to have been picked up by virtually every publication that covers music news.

note to self: think for another minute before posting (lol)

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#9

No, I’m sorry, because I’m just spamming my opinion here and by no means intended to delegitimatize your post or the work itself. I think the technology (both in the case of blockchain and ML) iis actually really interesting - what I don’t buy is when it’s sold as somehow “revolutionary”, especially by people who profit from it directly.

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#10

OK, thanks for this (I still need to digest the economic theory in the first part of your post as well as re-read Dryhurst’s article.) At least I think I understand where you’re coming from and agree more or less in spirit.

No, of course one can’t transform the essence of technology simply by developing better tools – one must first probe its essence, which is basically commodification; in other words, revealing everything as a manipulable, exchangeable resource to be either stockpiled or recirculated. This revealing also claims us - as “human resources”; as infinitely replaceable and AI has played an important role in this replaceability.

Again, the essence of technology is prior to actual technologies; this is why Philip K. Dick’s 1955 story “Autofac” perfectly predicts what will likely be the future of Amazon, and so on. This is also why James Ferraro or Jon Rafman can deliver potent critiques of the essence of AI without actually having to develop AI, and why Herndon’s gesture seems a bit superfluous here.

We don’t get our fundamental understanding from our tools; if so, we could just develop different ones and solve the problem then and there. This is the point Lanier constantly misses and it is always annoying. I detect that this is also how you read Dryhurst and for me the jury is still out, but I can see coming around to your position.

But there’s an interesting corollary which remains unaddressed in your critique. If the tools themselves are irrelevant to the understanding that forms the essence of technology (they only implement or reveal this understanding, but do not transform it, at least not by design), it also makes sense that existing tools such as AI and blockchain can and will be repurposed – they will come to reveal very different things about how we understand ourselves and the world. Since the tools themselves actually don’t matter, why not speculate as to potential future understandings which make use of these tools? You have to start somewhere in other words – not just “burn it down” and leave no resources with which to build in light of a new understanding. This speculation does not posit tools themselves as revolutionary. I think Herndon actually gets that AI is not revolutionary, and is looking towards how AI can mean something entirely different under a new understanding that is revolutionary.

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#11

Autechre on AI:

Sean Booth : I wouldn’t say it’s a living entity, really. It’s about as much like as an entity as a shit AI in a game is. That’s how intelligent it is, which is not intelligent at all, but it might at least resemble the way a person thinks. It’s funny, I’ve been reading about Markov models and Markov chains recently, the results from Markov Chains are remarkably similar to what you get out of Watson or DeepMind, these super advanced language modelling things. And this article was about how unwieldy that kind of mega-gigantic, expensive AI is, because you can actually achieve very close results using Markov chains, and they’re really fucking simple, they’re computationally really easy to deal with, they’re what people use for Twitterbots and things like that. So in some ways these simple conditional responses can resemble very high-end AI. Even though it’s very simple, the result is close enough not to matter.

From this interview.

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#12

The best “hard” AI in music I’ve heard is the Yasunao Tone ripper on mego:
http://editionsmego.com/release/EMEGO-241

Otherwise, I find AI music kind of unremarkable. The Actress/Young Paint thing, for example didn’t do much for me. Haven’t really unpacked why really. I seem to prefer the Autechre style “soft” AI - ‘it’s just a bunch of “if” statements’ type thing

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#13

this “Soft AI” was of course the lesson of Joseph Weizenbaum’s Eliza (1966)… Consciousness is relational, it is something achieved through the interaction of entities… not as something in the AI’s “head”… Eliza was a dead-simple “mirror” program…basically, repeat what the person says – yet people had much more meaningful experiences with Eliza vs. almost anything else at the time… (or vs. modern “assistants” such as Alexa/Siri… although the purpose was somewhat different…)

https://jerz.setonhill.edu/if/canon/eliza.htm

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#14

I was excited to see this thread pop up here, but a lot of the commentary has really heavily bummed me out. I get that AI is a bit buzzword bingo, but it’s 2018, not 1988; we should reasonably able to hold a coherent conversation about the field’s algorithms being applied to art without being sexist and dismissive.

And while the “snake oil salesman” comment may match your reality, it’s both aggravating and depressing that even here on lines, a woman’s work is reduced to criticisms about her partner’s.

There is so much more interesting potential to think about and discuss here than one of the artists’ boyfriend, or whether or not AI is an appropriate acronym to use in place of ML.

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#15

I agree that a discussion of the work shouldn’t devolve into sexism or unrelated comments about her partner, but I just wanted to add that I saw Herndon and Dryhurst (along with another collaborator whose name I can’t remember right now) discuss this exact work when it was still under wraps at CTM earlier this year and there was no doubt that it was a highly collaborative project. Yes, it’s been released under her name, but it was presented as a work in which the three of them had equal authorship and control.

#16

Now threads like this are (one of many reasons) why Lines is great!

I’ll have to write a proper response to this once I have a moment to sit down, but I’m all in favor or someone like Herndon using her position as the recipient of institutional support to further the conversation re: ML/AI + cultural production in the public sphere.

I mean, I suppose I can appreciate the read of this ‘sensationalizing’ the AI element of this for HH’s own benefit, but I don’t buy that as the primarily motivating factor in the work or its publicization. (also it’s a banger, and jlin is amazing!)

Also, ditto @analogue01that the Yasunao Tone works are incredible (saw a performance of this at Gavin Brown Enterprise and pretty much ripped my face off).

With that being said though, my hunch is that HH’s intent with this work is a bit different, and I appreciate her using her ‘platform’ in an intentional + public way.

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#17

One more quick thought:

I think one of the reasons ‘fine art’ in the age of culture-as-content is still important is that it allows us to look into the poetics/problematics of new systems + spaces in a way that fosters critical dialogue and investigation.

This could be why folks like Ferraro or Rafman can contribute meaningfully to this dialogue without actually developing their own AI’s like @ht73 mentioned above (they’re dealing with the ‘affect’ of AI?)

I think HH + MD’s approach to this is different but equally important as members of the institution that also exist as public facing cultural producers rather than straight ahead academics or industry engineers.

Whether that overlap will bring actionable change, i donno, but fingers crossed i guess?

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#18

I see this slated as a bad joke by industry engineers over in twitter…as for them its clickbait for AI when its actually not, but for the eternal catchphrase of HH/MD and the 3.person nobody ever knows abt (yes, they always act as an entity,for gender conformity?) BUT what is that catchphrase? I still dont really get it. I like Herndons music per se, but i always had difficulties taking in their ‚constructive criticism‘ of the internet. To me this always ended in being outdated by the industry-never being able to actually get a point across before the industry crushes catchphrase technology enabling by non industry ppl…the blockchain/cryptomoney/copyright triangle is a very good example where so much did go wrong in so little time that it’s actually way better to call this a distopian semifuture and abandon the fact that we humans have to fight for integrity within the machine world. And yes this has been done by Ferraro in a very convincing human way. As for the video, i haven’t listened to it just now, i need a human that tells me ‚patrick i know your taste, you‘ll like it‘ because up to this point i see ppl hate or love it in this virtual world but it hasnt sprung to my ears yet…maybe this is HH/MD/3.s agenda?

#19

Check out AIVA (Artificial Intelligence Virtual Artist).

It’s an electronic composer that specialises in Classical and Symphonic music built on deep learning and reinforcement learning architectures.

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#20

The neural-network chip forms the heart of the synthesizer. It consists of 64 non-linear amplifiers (the electronic neurons on the chip) with 10240 programmable connections. Any input signal can be connected to any neuron, the output of which can be fed back to any input via on-chip or off-chip paths, each with variable connection strength. The same floating-gate devices used in EEPROMs (electrically erasable, programmable, read-only memories) are used in an analog mode of operation to store the strengths of the connections. The synthesizer adds R-C (resistance-capacitance) tank circuits on feedback paths for 16 of the 64 neurons to control the frequencies of oscillation. The R-C circuits produce relaxation oscillations. Interconnecting many relaxation oscillators rapidly produces complex sounds. Global gain and bias signals on the chip control the relative amplitudes of neuron oscillations. Near the onset of oscillation the neurons are sensitive to inherent thermal noise produced by random motions of electron groups moving through the monolithic silicon lattice. This thermal noise adds unpredictability to the synthesizer’s outputs, something David found especially appealing.
The synthesizer’s performance console controls the neural-network chip. R-C circuits, external feedback paths and output channels. The chip itself is not used to its full potential in this first synthesizer. It generates sound and routes signals but the role of learner, pattern-recognizer and responder is played by David, himself a vastly more complex neural network than the chip.

from http://www.lovely.com/albumnotes/notes1602.html

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#21

David Tudor rules. idk how I forgot about that one

#22

Interesting review on Xenogothic:

opens up AI intersection w/embodiment, in the context of the platform-centric feedback loops we were discussing earlier.

also

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#23

This is a fun take on using a RNN trained on rap lyrics.

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#24

It’s difficult to introduce ‘AI’ into a conversation without people spinning off into philosophical rabbit holes, but if we focus on music/culture, things become a lot simpler. Turing machines are an extremely powerful technology. They have already had a huge impact on music and utilizing more ‘novel’ algorithms(markov chains, neural nets, genetic algos, blah blah blah) is just a continuation of that.

Like any other tool(drum, piano, synthesizer, DAW), it is ultimately the job of the composer to use it creatively to write music. The fact that autechre can produce what they do using mostly if/then conditionals is a testimony the importance of this.

The only paradigm change I think ML brings to the table is that emulation of past works because almost trivial. I have already heard eerily spot-on examples of fake Beatles songs trained on a corpus of Beatles tracks. Humans are already very guilty of this mimicry(see most sub-genres of music), it’s now just becoming more efficient. Perhaps this will push us, as species, to prioritize originality more than we currently do?

Not to beat up on ML, of course. Again, like any technology, there’s nothing stopping people from using it in novel ways. How long before someone trains a convolution networks on a mixture of Taylor Swift and Merzbow?

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#25

To think of AI as some sort of objective process is wrong. AI is automation. So it is a way of making certain (complicated) tasks more efficient and reproducible. The task has to be defined by somebody and the inputs have to be defined by somebody and the output has to be judged by somebody.

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#26

Cover of Artificial Intelligence compilation on Warp Records, 1992
artifical inelligence.jpg600×598 120 KB

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#27

Musenet is “a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles.” The platform will be open for a few more weeks. I did an advanced generation of The Godfather Theme in the style of Journey for piano, strings, harp and bass.

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