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
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.
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?
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
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".
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.