Tenobrus

what basis do you have for assuming an LLM is fundamentally incapable of doing this?

o1 has a METR time horizon of around 40 minutes, opus 4.7 has an implied horizon of 18 hours based on its ECI score. this study is on a model that's several generations behind wrt the kind of tasks it can complete. it would be shocking if this number were anywhere near as low with GPT 5.5, to the point it seems nearly totally irrelevant to talk about these results

"Japanese soldier who kept fighting 29 years after World War 2"

those two stipulations were always their only ones, and they were included explicitly in their original contract with the DoW.

some ai detectors work now. pangram detects this as 57% AI written, and the parts it thinks are human are.... the ascii diagrams / screenshots. all the actual text it detects as generated.

strongly think you should go read the thread to get a sense of the level of expertise and amount of effort put in by the humans involved: https://www.erdosproblems.com/forum/thread/728#post-2852

ai detectors are never totally accurate but this one is quite good and it suggests something like 80% of this article is llm generated. honestly idk how you didn't get that just by reading it tho, maybe you haven't been exposed to much modern llm-generated content?

https://www.pangram.com/history/5cec2f02-6fd6-4c97-8e71-d509...

A lot of people forget how whimsical and strange and beautiful the old smaller GPT models and the original 3 base model pre-RHLF could be. Nowadays hundreds of millions of people have talked to heavily assistant tuned 4 or 5, but comparatively very few people have ever even seen GPT-1 outputs. It's cheap to run so I threw up a simple interface + single server hosting it.

It looks like the person who added the backdoor is in fact the current co-maintainer of the project (and the more active of the two): https://tukaani.org/about.html

it is very clear to me that humans do in fact have a recursive self-improvement ability, and i'm confused why you think otherwise

all this capability was already easily available in GPT-3 with some prompt engineering, this mostly just changed it from few-shot to zero-shot.

You're talking the US first amendment and how freedom of speech relates to governments, but that's only a limited subset of the general concept of free speech. Obviously discussions around platforms involve more complexity, but for example if AT&T started refusing to send my texts based on what kinds of ideas I was arguing for then this is a serious attempt to limit speech and discussion which is morally incorrect, regardless of legalities.

The main interesting thing about GPT-3 is that prompt engineering turns it into an incredibly general tool. This summary was likely generated with a prompt something like:

Here's an article about x: <text of sample article>

A quick summary of the article, focusing on the main relevant points and keeping critical detail: <sample summary>

as an example, then duplicating that with the real article and text.

That's the "few shot learning" from the original paper. It could also be that it's good enough at summarizing specifically that you don't need an example, just the right framing prompt around the article text. Either way, that kind of prompt engineering is how you get "text completion" to perform basically any text processing task, generate code or play tic tac toe, so on

I find stable diffusion requires a lot more prompt engineering than either midjourney or dalle, but has a higher ceiling of quality if you do put in that effort. I wouldn't expect just using exactly the same prompt for all three models would work very well, need at least a little tuning per-model.

I mean in practice what it tends to mean is the logs only had a 3 month ttl so really could be either way. "no evidence" implies there is at least a place there could have been evidence, they looked, and didn't find any, which is a weak but nonzero update towards it having not happened. It would be nice if they clarified exactly what they checked.

This isn't the case with (long-standing, extremely well tested) ZK technology like Monero, and future applications like privacy-focused ZK rollups. In these chains there's no feasible way to track even single transactions.

No actual blockchain will be able to (even in theory) take down DMCA'd data. There is no mechanism whatsoever for complying with such requests, anymore than there's a mechanism for reversing transactions associated with activity a government deems illegal.

Individuals running IPFS gateways or nodes may be directly targeted and asked to take down data, but there's no mechanism for "the network as a whole" to remove data. It's exactly the same as bittorrent. So long as one individual in some hard-to-reach jurisdiction continues hosting the data, nothing can be done.

It's simply privileging calldata with lower gas (changing a constant) plus adding a cap on the maximum amount of calldata that can be in a given block to prevent crazy state bloat. It's effectively baking in L2s as something the protocol wants to encourage by giving them a "tax break". Note that the gas market is still in effect, so this is "tuning call data against the other costly aspects of ETH tx processing" rather than some "magic price reduction".

You're misunderstanding, the numbers show 4990 million in 2021 vs 3444 million in 2020.

The /r/ethfinance daily is much more focused on interesting technical and social developments and has a higher level of discourse than any other crypto sub I'm aware of. Still some price talk/memes, but there's some consistently thoughtful and well informed posters there, and I'd recommend checking it out.

An alternate progression could involve exponential height growth, leading to every suburb eventually looking like a cluster of space elevators (and beyond).

Actually this is no longer true. As of recently, the crypto ecosystem produced Dai (https://makerdao.com/en/), which is a fully decentralized stablecoin. I think it represents one end-state of the crypto ecosystem, blockchain transactions but with decentralized systems keeping volatility near zero.

But on the other hand a .org file would probably rank pretty highly on the [file extension trustworthiness scale](https://xkcd.com/1301/)

Does anyone know how I can filter out non-english posts from Mastodon? I set up an account and followed some people back in 2017, but it's unusable for me now since I can't read 70% of the content in any of my timelines.

Why does your argument not show that cars would have a similar lifetime?

An extremely avoidable tragedy. I can't imagine why NYT wouldn't be flexible about this, they have countless articles about a wide variety of people (actors/performers, other authors with pen names, people with chosen names for a variety of personal reasons, etc) in which they respect the subject's wishes. It seems so arbitrary for them to refuse in this case.

Which you almost certainly can do with Home Assistant

This isn't really true. Anyone can make comets, which are low-trust entities but still can use the network without any parent at all. Stars and planets can move between their parent galaxy/stars respectively. There's so many stars it's very unlikely planets will be unable to find a host they're OK with, and while there's fewer galaxies, they've been distributed reasonably widely, to the point that for sure not all are controlled by the original creators and there's at least plausibly variation in thought among the owners. Beyond that it seems like your view of how stars/planets interact with their parents is more restrictive than reality, the intention is more infrastructure providers than the form of moderation you see in a subreddit.

The thing I think is most problematic is actually the numbers involved, specifically the fact that there's only 4 billion planets (still).

And in case anyone's interested, the relative locations the API gives are relative to https://media.britishmuseum.org/media

No, it's not. It's actually e ^ x_i / sum(e ^ x_j for x_j in x), which is in fact different. Simply dividing by the sum wouldn't work for "squashing to a probability distribution" in a large number of cases.