svara
I.e. any task comes with the implicit meta task of amassing the resources and the power to do the task in the best possible way.
The point is made very well in the AI drives paper by Omohundro.
I didn't believe that myself at first but I've come around to it. I don't think it's inevitable though, but I think it's quite convincing that this tendency would naturally emerge through reinforcement learning.
This is a clear step change, I'm genuinely amazed.
Its answers are to-the-point, logically structured, clearly written. Like a really well made mini essay on your question.
It also really likes to build little simulations / models that you can tweak the parameters on. Amazing to explore how different assumptions affect economic scenarios, for example.
It's also great at picking (sourced) illustrations.
I'll be using this for everything that isn't coding from now on.
Secondly, in practice consciousness is rarely the criterion we use to make such moral judgments. Many people would think it's plausible that animals are conscious but still be fine with eating them.
It makes more sense to ask whether AIs have the ability to suffer. That's much more interesting, because we should be able to look into the models and discover 'neural correlates of suffering' - since they are artificial models, it is possible to specifically suppress that in training.
Even if you don't actually believe that suffering in AI is morally relevant because it wouldn't be consciously experienced, it seems that would be a good idea. Do you as a user really want to interact with an AI that gives you the feeling that it might be suffering in response to your prompts?
If you're not familiar, that's a document management system.
You can set up an ingest email address that you send photos or scans of your snail mail to and that you forward email with PDF attachments to.
With how good and affordable OCR is these days, you'll have a full text searchable archive of all correspondence you've ever received. (1)
You can set up plugins that use AI models to auto tag and sort the documents too.
(1) There are companies that you can mail stacks of documents to and that will turn them into PDFs if you want to do it retroactively.
I think we don't really understand why deep learning works as well as it does, the thinking around that is, as far as I can tell, mostly a collection of empirical observations.
A fundamental theory of learning that can be used to predict optimal network architectures might enable smaller models that consume less energy.
Tao is speaking of a very particular kind of mathematics, that done out of pure curiosity.
But maths, even at the highest levels, often finds applications sooner or later.
It will be economically impossible to justify boycotting correct mathematics that no humans understand on grounds only of purity.
This may happen very soon: one of the obvious applications of novel mathematical results is in building stronger AI models.
The argument goes that livestock have a capacity for suffering, but killing them for meat without causing them suffering is ethical.
You can disagree with the position, or with its implementation in practice, but it's a consistent position in principle.
The business that had those problems didn't become Apple.
I thought the Bengio blog post posted here the other day answered that question quite well (ignoring your timeline).
The argument is that in training for the capability to achieve certain goals, you may inadvertently also train for secondary instrumental goals you did not intend, such as aggressive behavior or deception.
I'm actually no sure I buy that this is particularly likely, or necessary, but I found that take reasonable and worth considering.
This is not something that's just true on its own; it's on us as a species to make sure that it remains that way, for the sake of our dignity.
However, this position will be extremely difficult to defend, against the economic value of not caring.
It's the small teams you need to pay attention to, the organizations that really were limited by engineering capacity. These are by definition also less visible - for now.
E.g. I've gotten pretty good at git thanks to AI because it forced me into more complex workflows. I still can't remember the commands but I really grok the concepts and terminology on a far deeper level than before, where I made a conscious effort to stay on the happy path lest I get into some odd state I don't understand. Pretty sure those "odd states" would seem quite clear to me now.
Culture can change surprisingly quickly, but it certainly won't change in ways you like if you're not doing your part.
Already, young people and the ways they use online media are quite different from people my age, and I'm not that old.
I see a lot of young parents reading to their children, making sure they grow up with a love of books, very concerned about their consumption of social media.
Backlash against the shallowness and divisiveness of social media is not niche anymore.
It needs a little more pushing, a little more time, a little more being an example for yourself and others.
What's certainly not going to help is throwing your arms in the air and submitting to the all powerful social media overlords.
Yes, true, but that's also very much a thing you can do something about by, well: reading books.
It's a technique we must preserve for the good of our culture, but, also, in a society full of people who have forgotten how to, an individual superpower.
I was similarly frustrated a few months ago, but have noticed I've started to learn the idiom.
Its use of "dense jargon" and "stilted metaphor" is actually surprisingly consistent - it's speaking its own dialect, and you get used to it.
After a while it gets much easier to read and even becomes somewhat efficient, I think, since the odd metaphors it uses often have a precise meaning in Opus-ese (Fable speaks a really similar dialect).
So why do people not like datacenters? Go figure.
Occasional fires, sure. But very clearly nothing approaching the current scale and frequency.
The last really big one in that region was in 2022; and there are currently not one but 2 parallel fires in the same forest.
Two of the large recent fires in the Landes region, including the most recent, have started from poorly maintained, spontaneously igniting cars. Those also have not suddenly started appearing out of nowhere.
The common thread is very dry forests, it just takes a spark for disaster.
A bit of a distinction without a difference. The climate is not changing back, it's the new normal. In that climate, this particular kind of agriculture (huge pine monocultures) has become a problem.
It breaks my heart to say this, I've spent nearly all my childhood summers in my family's summer house down there. This year, I left just a few days before the evacuation order would have come.
It's going to be burning every year now and if we want to be safe there, the forest can't stay the same.
For example, when studying maths or physics, it is very common to feel like you've understood everything, until you get to the exercises, and need to apply that understanding, and it's only then that you consolidate the knowledge and begin to truly understand in depth.
I like AI enhanced coding, but I do sometimes worry that we're not getting enough of that depth anymore.
I'm not enough of a designer to be able to point exactly at what makes it so, but Claude does seem to have a somewhat limited repertoire of styles.
Maybe if you could point more precisely at the required changes, you could discourage it?