djokkataja
Joined 14 years ago
Joined 14 years ago
> Importantly it was admitted that internal Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic.
If an Anthropic employee is doing independent research, but with models that aren't available to the public (because they're internal models), then . . . idk. It's not clear to me why that should necessarily require a refusal to cooperate between OpenAI and Anthropic employees who are excited about solving a problem like this.
For me, the bigger question here is what "internal models" means to these employees, especially in the context of the OpenAI employees repeatedly avoiding directly answering whether their model had been trained on Tristan's and Levent's ongoing work on the problem. It had always seemed like a loophole that AI companies might be tempted to exploit: yeah, they can say that they won't train on your data, but if an AI company doesn't care about ethics, they might go ahead and train a model for internal use only on everyone's data anyway, just to have as much data as possible and potentially gain an advantage in what the company can internally do. They could never publicly release any versions of a model like that, of course. And of course this is speculation.
Compared to what??
Actually, someone even commented in that thread about how it was similar to biological mechanisms: https://news.ycombinator.com/item?id=47390619
> A quick note: All of the data visualizations in this roundup are free to use as common content. You are welcome to share and republish them.
Plus if you want to make a robot which can do everything a human can do, without exception, you'll start running into weird edge cases if you make it with a fixed wheeled base. Like suppose you want it to climb a ladder or turn sideways to slip into a narrow space and retrieve something. Or maybe you want it to be able to climb in and out of vehicles designed for human occupants. Would you want to have to buy a special vehicle to bring your robot somewhere with you?
And judging by the name of the company and that they likely aspire towards more than what they've made so far, I'd guess that a long-term goal could be to also make something for people who realize the weakness of their flesh and crave the strength and certainty of steel.
For better or for worse, the equivalent race right now is in AI.
Also, on the graph you linked to, you can click on the line in the graph of population versus year to the right, and if you start back in the 1950s and work your way along to the present, you can see the big lump of the baby boomers getting older. That's why people say the United States has an aging population.
This seems almost comically lemming-like. Fear of missing out . . . on dying?
> Getting frozen and brought back in the distant future, even if we assume you'll be in great health, means all your friends and family are gone.
(Assuming none of your friends and family were also frozen.) But more importantly, I wouldn't suggest that people should aspire to death because of losing all their friends and family. If starting over (in what's likely an unfamiliar society and culture) is all one's got, that's still something.
Mainly I find it grotesque that it might be a way to slip past death, but only for rich people. But I can't bring myself to suggest that it would necessarily be a better universe if they took the normal death route instead.
Penrose tries to respond to this by saying that various things may affect the functioning of a brain and keep it from reliably perceiving such truths, but when brains are working properly, they can perceive the truth of things. Most people would recognize that there's a difference between an idealized version of what humans do and what humans actually do, but for Penrose, this is not an issue, because for him, this truth that humans perceive is an idealized Platonic level of reality which human mathematicians access via non-computational means:
> 6.4 Sometimes there may be errors, but the errors are correctable. What is important is the fact is that there is an impersonal (ideal) standard against which the errors can be measured. Human mathematicians have capabilities for perceiving this standard and they can normally tell, given enough time and perseverance, whether their arguments are indeed correct. How is it, if they themselves are mere computational entities, that they seem to have access to these non-computational ideal concepts? Indeed, the ultimate criterion as to mathematical correctness is measured in relation to this ideal. And it is an ideal that seems to require use of their conscious minds in order for them to relate to it.
> 6.5 However, some AI proponents seem to argue against the very existence of such an ideal . . .
Source:
https://journalpsyche.org/files/0xaa2c.pdf
Penrose is not the first person to try to use Gödel’s incompleteness theorems for this purpose, and as with the people who attempted this before him, the general consensus is that this approach doesn't work:
https://plato.stanford.edu/entries/goedel-incompleteness/#Gd...
Also I think in the US at least, religion plays into it. God over humanity is conceptually the ultimate hierarchy model that Christians buy into. So it seems like Christians often don't have as much issue with embracing the idea of one person being over another person as a reflection of that model. This seems a little bit funny given how anarchic Jesus was, but he never said, "Yo, check it out, I am literally an anarchist and you should be too," and so they seem to have missed that.
> Only on the outside, where they can be appreciated as a whole, will the impression of intelligence emerge. A human brain, too, does not exhibit the intelligence under a neurobiologist's microscope that it does participating in a lively conversation.
We only have fuzzy definitions of "intelligence", not any essential, unambiguous things we can point to at a minute level, like a specific arrangement of certain atoms.
Put another way, we've used the term "intelligent" to refer to people (or not) because we found it useful to describe a complex bundle of traits in a simple way. But now that we're training LLMs to do things that used to be assumed to be exclusively the capacity of humans, the term is getting stretched and twisted and losing some of its usefulness.
Maybe it would be more useful to subdivide the term a bit by referring to "human intelligence" versus "LLM intelligence". And when some new developments in AI seem like they're different from "LLM intelligence", we can call them by whatever distinguishes them, like "Q* intelligence", for example.