I've feel that neural nets might do a better job writing articles than people who do it cheaply on fiverr for content farms.
Jukebox
121–130 of 134 posts
Re: Jukebox
#122This might be onto something! Just listen to this from 30s: https://soundcloud.com/openai_audio/pop-rock-in-the-6355437/... Such coherent and pleasing melodic phrases in the style of Avril Lavigne. I thought it could be copying wholesale from a song unknown to me. Nope. Shazam doesn't get it. This can revolutionize song writing/composition/production and soon music listening/consumption.
Wow, that's a good one. Yeah, I'm actually blown away by so many of these, there are a ton of completely impressive original melodies, harmonies and phrases—especially with the vocal lines—that go beyond a predictable 4/4 verse chorus. The comments on this thread are so ridiculous, they're completely missing how insane this research is. You could take half of these and write new original music based on them and it'd be incredibly solid. As it is, I'm really tempted to just gank some of these for myself.
Re: Jukebox
#123This might be onto something! Just listen to this from 30s: https://soundcloud.com/openai_audio/pop-rock-in-the-6355437/... Such coherent and pleasing melodic phrases in the style of Avril Lavigne. I thought it could be copying wholesale from a song unknown to me. Nope. Shazam doesn't get it. This can revolutionize song writing/composition/production and soon music listening/consumption.
Note that the lyrics are part of the input to the Jukebox neural net, so I assume they used the lyrics of an existing song here. Nothing stops someone from using a lyric-generating neural net with Jukebox though. (It's probably more useful that the lyrics aren't produced by Jukebox because it means you can easily swap out the lyric-generation part or manually tweak the lyrics.)
The lyrics are generated by a separate model, but they're "co-written" (cherry-picked) by the authors.
Re: Jukebox
#124Earlier quoted context omitted.
Isn’t that superhuman? I would guess that on average, it takes a professional more than 36 hours ((4×60÷20)×3) to make a 4-minute audio track with original music based on given lyrics.
I don’t really see the point of this comparison. Composing, arranging, and producing a song is not a benchmark you can profile against; musicians are not performing some kind of music compute that produces a set number of music units per hour. Speaking from my own experience, I’ve had tracks that took months to complete, and I’ve had tracks that I got to probably 90% completion in under an hour. I would propose that…
Agreed. Although "professional" pop production does tend to be somewhat involved, it doesn't have to be, and total time spent could vary so radically as to have essentially no correlation to anything else.
Re: Jukebox
#125Boy, the comments on this thread are ridiculous. SO many people saying "bleh, this is terrible, music is obviously out of the reach of ANNs, etc etc etc." If you've been following this space, this research is nothing short of fucking mind-blowing. Can you use these outputs as final radio-ready songs? No, they're heavily bandpassed, and the overall composition either feels 'unfinished' or nonexistent. But criticizing it on those grounds completely misses the point.
There are so many people here saying "music can never be generated by AI because, I don't know, creativity requires magic and only human souls have magic". Really? I kind of wonder how many of these people have actually done something creative. Creativity is such an amazing example of a large, densely connected neural net in action, when you let it start making unusual associations via what is sometimes called "lateral thinking."
I feel like people have already lost sight of how utterly incredible it is that we can generate anything like this, or Deep Dream, at all. They are incredibly creative.
Re: Jukebox
#126Earlier quoted context omitted.
> It's hilarious how as soon as there's some new AI work done everyone starts wailing, "where's the humanity!" Lay-people think AI refers to ALife. Most of the talking heads would be immediately satisfied—giving none of these complaints—if they were shown an "AI" program that responds to stimuli by entering emotional states, and which learns to associate stimuli with the emotional states it has been in in the past, s…
So basically, most talking heads would be better off playing The Sims. They'll have agents there that enter emotional states in response to stimuli. Even though it's just a fuzzy state machine. Now, is A[rtificial] Life the correct term to use here? I feel it isn't - I'd expect ALife to be more concerned with implementing simulacra of bacteria or worms in silico, not with reasoning or emotions.
ALife is fundamentally concerned with the research on the kind of control systems that govern how organic life responds to stimuli, how those systems plan in order to maintain long-term homeostasis, how they select goals, how they allocate attention, etc.
One might say that ALife is to an event loop as AI is to a one-time query-response. AI can evaluate, but you need an ALife system in order to "think" in a continuous way.
There's really no sense in which an ALife researcher cares about recreating a full-fidelity model of biology in silico; the point is to specifically study the thinking and decision process of real agents, and figure out how to model those, in a way that the model makes the same series of decisions the real agent does in the same situations (and, therefore, must also be keeping and updating analogous internal state to the kind the real agent keeps.)
Some of those models are attempts to recreate real brains/nervous systems, but these models aren't fundamentally biological. A "low level" connectome simulation doesn't contain any model of cellular inflammatory response, cellular waste and its clearance, etc. It's basically just a brain-as-actor-model with neurons as stateful processes and electrochemical signals as messages.
An ALife researcher cares about as much about biology below the level of intracellular pharmacodynamics (sodium channels et al), as a race-car-chassis engineer cares about physics below the level of fluid dynamics. They don't need to go any lower, because they've found an encapsulating abstraction that makes all the predictions they're interested in making, without needing any lower-level information.
Re: Jukebox
#127I'm working on an IDE for music composition. http://ngrid.io Launching soon. Music is fundamentally unsolvable by AI. We'll have AI writing code before we'll have AI writing meaningful music.
I'm curious what this might be. I definitely like the sound of an "IDE for music composition," but your landing page gives me almost no idea at all of what it is. Screenshots or video? Or at least some description of what makes this different than all the other iOS apps that advertise "makes music easy! No experience necessary!" To me those are the biggest red flags that something is useless for actual musicians.
As a side note, I take huge issue with "Music is fundamentally unsolvable by AI". That's a ridiculous stance that sounds way too much like "humans have these soul things that are made out of magic and computers can't ever have them."
Re: Jukebox
#128Earlier quoted context omitted.
Note that the lyrics are part of the input to the Jukebox neural net, so I assume they used the lyrics of an existing song here. Nothing stops someone from using a lyric-generating neural net with Jukebox though. (It's probably more useful that the lyrics aren't produced by Jukebox because it means you can easily swap out the lyric-generation part or manually tweak the lyrics.)
The lyrics are generated by a separate model, but they're "co-written" (cherry-picked) by the authors.
Only one category of the samples on the main Jukebox page are described that way. The rest of the samples were pre-existing lyrics, so the song linked above might also have had pre-existing lyrics.
Re: Jukebox
#129Earlier quoted context omitted.
So it sounds like the old goalpost problem of AI. Once you realize an AI can do something then this something is no longer what it means to be human?
I think we will soon find that what really makes us "human" is the shared chemo-biological composition of our selves with the rest of the ecosystem and evolutionary hierarchy. When you cuddle a puppy you can actually smell the infant hormones on them... why... because we share evolutionary biology. How do you teach a computer to do that? You can think of the body as "data" and the brain as nothing more than a databas…
Good point about the necessity of embodiment. I would go one step further and consider the environment, which is the source of evolution and knowledge, a simple environment like Atari games can't even begin to compare with the human society and world we experience. What makes us human has a lot to do with the dynamics of interacting with the other humans, an AI would need to be part of society to experience that.
Re: Jukebox
#130Earlier quoted context omitted.
Just know that: much of the stuff OpenAI and other research orgs put out (including mine) are heavily cherry-picked. Most of the time its pumps out gibberish, but in the off chance it doesn't it gets used as marketing material.
All you have to do is click through to see all the samples and it becomes clear how incredibly cherry-picked the ones on the front page are. It is a cool project but it is very clear how much work this technology will need before it is useful in any application.
Cherry-picking is exactly what artists do best. They will want this technology as a new tool in their toolbox. I expect some future genre of music using it's successor (like autotune).