It's hard to imagine anything worse than bombing an elementary school and yet people are still using Anthropic products as if nothing has happened.
Optics don't seem to matter much?
11,723 karma · joined June 5, 2012
It's hard to imagine anything worse than bombing an elementary school and yet people are still using Anthropic products as if nothing has happened.
Optics don't seem to matter much?
Given the political power they have, particularly now with the Trump administration, whatever "optics" exist on this forum seems completely insignificant
The reason most of the conversations are focused on benchmarks is because we are still in the age of weak AI.
Maybe I'm too boring but it seems quite pointless to have this same prediction game every time a new model is released.
I imagine this happens because we tend to conflate things that are similar, or maybe because it's not entirely clear which characteristics are being mapped in the metaphor?
The first book I ever read on ML (late 90s) dedicated the entire first or second chapter exploring the distinctions between artificial and biological neurons, and even talked a bit about the philosophy of modelling. I still remember thinking back then why would the authors spend so many pages on this but now I believe it was because they understood that a metaphor can be a double-edged sword.
The "AI is using a lot of resources" excuse was maybe acceptable last year but not in Q3 2026.
https://blogs.nvidia.com/blog/microsoft-azure-worlds-first-g...
They also show up in AbuseIPDB with multiple reports.
Another detail: the scraper did not attempt to access the endpoints immediately (as it did for hrefs in htmls) but it did it on the day after, twice.
https://developer.amazon.com/amazonbot/searchbot-ip-addresse...
By the way, they used false user-agents.
https://en.wikipedia.org/wiki/Futurama_%28New_York_World%27s...
It would also help if you could substantiate your initial claim (i.e. "internet training data is not where frontier capabilities come from")
That is only relevant in the US, and even there it is still not clear-cut whether the fair use doctrine applies on all these scenarios. Outside of the US the situation is also quite different: for example take a look at the recent ruling on GEMA vs OpenAI in Germany.
The reality is that the copyright issue with generative AI is very complex and reaching anything resembling a conclusion will take much more than a few opinion paragraphs from an American district judge.
https://www.bloomberg.com/news/articles/2026-06-22/spacex-ki...
Why is that almost every LLM generated article sounds like a LinkedIn motivational post?
(this is not a rhetorical question, I would really like to know why, from all the writing styles, this is the most prevalent one)
https://www.heraldscotland.com/news/26188090.john-swinney-ta...
And in relation to your first comment, most sane people would agree that "tools" don't exist in isolation - neither come into existence out of nowhere.
This reductionist position of treating extremely complex machines with deep social interactions as a tool like any other is objectively wrong, and I believe the reasons are highly obvious but I can expand on this if you disagree.
If GP has access to this dataset it would be interesting to know how sparse is the data in that area.
A tiny bit hyperbolic for someone who's not a fan maybe? :)