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NotebookLM's automatically generated podcasts are surprisingly effective

simonwillison.net

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Re: NotebookLM's automatically generated podcasts are surprisingly effective

#501
post #490

Earlier quoted context omitted.

Your comment implies that there is an existing piece of music, which can subsitute the generated music. While subsitutability varies from person to person, your original statement implies for me that each generated music has an accompanying original music that you can listen to instead (of which it was "stolen" from), since it is similar enough. I think we both know that that is not the case. I know that you likely i…

You don't have to be a big fucking nerd about it, you know what I meant. The generated music wouldn't exist without the foundation of stolen music made by people.

No, I didn't know what you meant. Communication is hard, and there are multiple ways to interpret your statements. It is better to be specific.

To be more specific about the second sentence, if there are any readers in doubt:

> The generated music wouldn't exist without the foundation of stolen music made by people.

The word "stolen" is a value judgement that is not shared by all. It is a word meant to invoke an emotional response in the reader. For example, Stallman has argued that the data could not have been stolen, or else it would not be there anymore. So, removing this word gives you:

> The generated music wouldn't exist without the foundation of existing music made by people.

Which is a true fact that has never been in debate.

However, this is not relevant to the main point that not all generated music has a suitable handcrafted substitute, and that there is no actual need to choose exclusively to listen to generated or human crafted music. Furthermore, the conversation has turned uncivil (the first sentence). Therefore, goodbye.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#502

Earlier quoted context omitted.

If your argument is "they can't reason" (plus some other stuff about how they work), what reasoning test has an LLM failed for you to conclude that they can't reason? Whenever I've given an LLM a reasoning test, it seems to do fine, so it really does sound to me like the argument is "they can't really reason, because ".

That isn't the argument. I've stated the argument twice. My longer response to you starts by stating the core of the argument as succinctly and clearly as I can. That's the first paragraph of the post. Not only are you still not getting it. You're also twisting what I wrote into claims I have not made. I'm not going to explain myself a third time. I'll instead say this: if you think these models must be reasoning whe…

You're right, but my argument is this:

You said:

> I'm not saying "they predict tokens; therefore, they can't reason." I'm saying "something that can't reason can predict tokens, so prediction isn't evidence of reasoning."

This is true. Reasoning is evidence of reasoning, and LLMs do pass reasoning tests. Yes, the way they work doesn't imply that they can reason, the fact that they can reason implies that.

You also said:

> These models deal with tokens similarly. They don't know what a token is or represents -- or we have no reason to think they do.

I have no reason to think that other people know what concepts are or what they represent, just that they can convincingly output a stream of words when asked to explain a context.

The argument bugs me because you can replace "they predict the next token" with "they are collections of neurons producing output voltages in response to input voltages" and you'll have the exact same argument about humans.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#503

Earlier quoted context omitted.

That isn't the argument. I've stated the argument twice. My longer response to you starts by stating the core of the argument as succinctly and clearly as I can. That's the first paragraph of the post. Not only are you still not getting it. You're also twisting what I wrote into claims I have not made. I'm not going to explain myself a third time. I'll instead say this: if you think these models must be reasoning whe…

You're right, but my argument is this: You said: > I'm not saying "they predict tokens; therefore, they can't reason." I'm saying "something that can't reason can predict tokens, so prediction isn't evidence of reasoning." This is true. Reasoning is evidence of reasoning, and LLMs do pass reasoning tests. Yes, the way they work doesn't imply that they can reason, the fact that they can reason implies that. You also s…

Thanks for explaining. I see what you're getting at now.

Here I think it's helpful to distinguish between what something is and how it's known. When we see something that resembles reasoning, we very reasonably deduce that reasoning has taken place. But 'it looks like reasoning' is not equivalent to 'it is reasoning.'

To approach the same idea from a different direction:

> I have no reason to think that other people know what concepts are or what they represent, just that they can convincingly output a stream of words when asked to explain a context.

You absolutely do have reason to think this. You're the reason. You're the best available evidence, because you have an internal life, have concepts and ideas, have intentions, and perform acts of reasoning that you experience as acts of reasoning -- and all of that takes place inside a body that, you have every reason to think, works the same way and produces the experiences the same way in other people.

So, sure, it's true that you can't prove that other people have internal lives and reason the way you do. (And you're special, after all, because you're at the center of the universe -- just like me!) But you have good reason to think they do -- and to think they do it the way you do it and experience it the way you experience it.

In the case of these models, we have no such reason/evidence. In fact, we have good reason for thinking that something other than reasoning as we think of it takes place. We have good reason, that is, to think they work just like any other program. We don't think winzip, Windows calculator, a Quake bot, or a piece of malware performs acts of reasoning. And the fact that these models appear to be reasoning tells us something about the people observing them, not about the programs themselves. These models appear to be reasoning only because the output of the model is similar enough to 'the real thing' for us to have trouble saying with certainty that they aren't the real thing. They're simulations whose fidelity is high enough to create a feeling in us -- and to pass some tests. (In that sense, they're most similar to special effects.) (Edit: and that's not to say feelings are wrong, invalid, or incorrect. They're one of the key ways we experience the things we understand.)

Is reasoning taking place in these models? Sure, it's possible. Is there an awareness or being of some kind that does the reasoning? Sure, that's possible, too. We're matter that thinks. Why couldn't a program in a computer be matter that thinks? There's a great novel by Greg Egan, Permutation City, that deals partly with this: in one section, our distant descendants pass to another universe, where matter superficially appears to be random, disorganized, and low in enthalpy. When that random activity and apparent lack of life and complexity are analyzed in the right way, though, interference patterns are revealed, and these contain something that looks like a rich vista bursting with directed, deliberate activity and life. It contains patterns that, for all the world, look and act like the universe we know -- with things that are living and things that are not, with ecosystems, predators, prey, communities, reproduction, etc. These patterns aren't in, and aren't expressed in, the matter itself. They 'exist' only in the interference patterns that ripple through it.

That's 100% plausible, too. Why couldn't an interference pattern amount to a living thing, an organism, or an ecosystem? The boundary we draw between hard, physical stuff and those patterns is arbitrary. Material stuff is just another pattern.

My point isn't that reasoning doesn't take place in these models or can't. It's, first, that you and I do something we call reasoning, and the best available information tells us these models aren't doing that. Second, if they are doing something we can call reasoning, we have no idea whether our understanding of the model's output tells us what its reasoning actually is or is actually doing. Third, if we want to attribute reasoning to these models, we also have to attribute a reasoner or an interiority where reasoning can take place -- meaning we'd need to attribute something similar to consciousness or beinghood to these models. And that's fine, too. I have no problem with that. But if we make that attribution, then we, again, have no reason to attribute to it a beinghood that resembles ours. We don't know its internal life; we know ours.

Finally -- if we make any of these claims about the capabilities or nature of these models, we are necessarily making the exact same claims about all other programs, because those work the same way and do the same things as these models. Again, that's fine and reasonable (though, I'd argue, wrong), because you and I are evidence that stuff and electricity can have beinghood, consciousness, awareness, and intentions -- and that's exactly what programs are.

The point that I don't think is disputable is the following: these models aren't a special case. They aren't 'programs that reason, in contrast to programs that don't.' They aren't 'doing something we can do, in contrast to other programs, which don't.' And even if they're doing something we can (or should) call reasoning, reasoning requires interiority -- and we have no idea what that interiority looks or feels like. Indeed, we have no good reason to think there's any at all -- unless, again, we think other programs do as well.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#504

Earlier quoted context omitted.

You're right, but my argument is this: You said: > I'm not saying "they predict tokens; therefore, they can't reason." I'm saying "something that can't reason can predict tokens, so prediction isn't evidence of reasoning." This is true. Reasoning is evidence of reasoning, and LLMs do pass reasoning tests. Yes, the way they work doesn't imply that they can reason, the fact that they can reason implies that. You also s…

Thanks for explaining. I see what you're getting at now. Here I think it's helpful to distinguish between what something is and how it's known. When we see something that resembles reasoning, we very reasonably deduce that reasoning has taken place. But 'it looks like reasoning' is not equivalent to 'it is reasoning.' To approach the same idea from a different direction: > I have no reason to think that other people…

> Indeed, we have no good reason to think there's any at all -- unless, again, we think other programs do as well.

And this is equivalent to saying there's a dog in my computer when I open a photo of a dog. It treats the simulation, the data, the program -- whatever you want to call it -- as if it were the thing itself.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#505

Earlier quoted context omitted.

I'm not sure what you're getting at. Could you explain?

That "they predict the next token" doesn't necessarily imply "they can't reason".

Of course, because the statement "they can reason" is an extraordinary one, requiring rather extraordinary evidence.

Therefore I think it's reasonable to say they cannot, until someone actually comes up with that evidence.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#506

Earlier quoted context omitted.

I'm not saying "they predict tokens; therefore, they can't reason." I'm saying "something that can't reason can predict tokens, so prediction isn't evidence of reasoning." More specifically, my comment aims to meet the challenge posed by the person I answered: > I highly recommend letting that fact be a little bit impressive, someday. There’s no way you live through any event that’s more historically significant, oth…

If your argument is "they can't reason" (plus some other stuff about how they work), what reasoning test has an LLM failed for you to conclude that they can't reason? Whenever I've given an LLM a reasoning test, it seems to do fine, so it really does sound to me like the argument is "they can't really reason, because ".

Would you say that SHRDLU is capable of reasoning then?

https://en.wikipedia.org/wiki/SHRDLU

Because, whenever you give it a reasoning test, it also seems to do fine.

That is what I meant in my other post, I don't really think that "it seems to do fine" is enough evidence for the extraordinary claim that it can reason.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#507
post #425

Earlier quoted context omitted.

> > the people getting ripped off Nobody is getting "ripped off" by ML models any more than by other humans. When a human wants to launch a high-quality podcast, they survey the market, listen to a lot of other high quality podcasts, and then set to creating their own derivative work. What ML models are doing is really no different. It's just much, much faster. Everything humans create is derivative of other works. S…

The only difference between cracking a 4-bit private key and a 512-bit private key is speed, too. So are private keys of those sizes qualitatively the same thing? Or is it that, at some nebulous point, a difference in speed between two things impacts the way humans choose to direct their efforts to such a great extent that, for all intents and purposes, the two things are qualitatively different?

> The only difference between cracking a 4-bit private key and a 512-bit private key is speed, too. So are private keys of those sizes qualitatively the same thing?

That's like sayin "The only difference between drinking 1 gallon of water and 100 gallons of water is death." Yes, the quantity of something for a given use-case is bound to give different results.

What the parent comment was commenting is that the actions being taken by these models should not be morally classified as wrong in abundance just as humans following the same process would never be regardless of the output they produced.

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#508

Earlier quoted context omitted.

> As a podcast listener, I lose interest if I can tell the audio is AI-generated... I've never naturally come across a podcast that's AI generated to have this reaction.

Youtube is full of AI generated glurge now, though.

I hate those videos so much. It would be awesome to have all AI crap removed from the paid version of YouTube

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#509

Earlier quoted context omitted.

The only difference between cracking a 4-bit private key and a 512-bit private key is speed, too. So are private keys of those sizes qualitatively the same thing? Or is it that, at some nebulous point, a difference in speed between two things impacts the way humans choose to direct their efforts to such a great extent that, for all intents and purposes, the two things are qualitatively different?

> The only difference between cracking a 4-bit private key and a 512-bit private key is speed, too. So are private keys of those sizes qualitatively the same thing? That's like sayin "The only difference between drinking 1 gallon of water and 100 gallons of water is death." Yes, the quantity of something for a given use-case is bound to give different results. What the parent comment was commenting is that the action…

I disagree about what the parent is trying to claim.

>What ML models are doing is really no different. It's just much, much faster.

I take this argument to be that (a) what the ML models are doing is fundamentally the same as what humans already do (I agree with this part), (b) that we have no moral problem with humans doing this already (I agree again), and that (c) the fact that AI does it much faster is not sufficient to cause any moral difference (I disagree with this part, and gave a counterexample to show how, in general, a difference in speed can make a moral difference, because that speed difference can have a large impact on how other people decide to behave).

Re: NotebookLM's automatically generated podcasts are surprisingly effective

#510

The podcast about the comments in this thread :) https://notebooklm.google.com/notebook/7973d9a3-87a1-4d88-98...

"and with over four hundred comments" not quite! Currently 295 comments.

Seems like it can also predict the future. Almost 500 now.
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