Anthropic is the one that prohibits harnesses other than Claude Code on subscription plans and bans users for disobeying.

OpenAI officially allows that with subscriptions.

If you bother to look at the issue instead of whining and complaining, you will see the evidence.

When I disagree with the data: I will nitpick every last detail of methodology, any cross-corroboration is an anecdote, suddenly I demand a-priori levels of justification. All science is flawed anyways, it's not like mathematics, you can't get absolute certainty, so why bother? You're always going to be making base assumptions that can be challenged, you're necessarily going to abstract out the territory, the map is flawed.

When I agree with the data: I will boast about the victories of science and empiricism, we found the perfect set of natural abstractions that are necessary and sufficient to map out the territory that carve at the joints of the problem, any concern about assumptions is rebutted with generic "Well, we're just pragmatists; we're not perfect, but clearly we're converging on the right direction! You're clearly someone who just wants to nitpick and not get any work done."

My experience with certain hackernews commenters in a nutshell.

This is evidence of a bug, not the purposeful enshittification people are referencing

This reminds me of a time in COVID-health response when certain scientists said their evidence was real evidence and yours was not.

"There's no evidence to prove xyz" then they would say, as your evidence was never as rigorous as theirs. And since they were proclaimed to be the only authorized scientists in the room, by authority of big governing bodies, they were right.

So people will see whatever evidence they want, and whine and complain to dig into their side as tribalistic creatures.

Now this is the kind of honest snark I would hire.

What does this have to do with anything? Who are you talking to? This is Hacker News, not Anthropic support.

I think they’re just posing the question to other users reading these comments.

HN becoming anthropic support would certainly explain a lot of threads and comments I've seen here lately. Thank you for this.

Are you high?

168 meters above sea level

This is rather incoherent.

> OAuth is pretty simple, just read the spec.

You picked probably the only semi-straightforward thing about part of one of the OAuth specs, then hand-waved away the other 95% of the necessary related specs, knowledge, and experience for getting an implementation working robustly and securely for a non-trivial use case.

Great if you have fiber and live down the road from the datacenter.

I routinely use it over a 5G mobile connection, often while moving, far from any datacenter, and it's usually fine as long as my signal is good. They do a fantastic job out of squeezing what they can from your connection.

I'm actually some 200 miles from the data center, but Nvidia has been doing a stellar job in connecting to the backbones of all the major ISPs around. If I actually lived down the road from them, it would be as low as 1 to 2ms, as reported by plenty of users. This isn't uncommon, especially in the EU.

But yeah, you need a fiber.

We aren't talking about insect identification models from 2019.

What do you think are running on the T4 GPUs in AWS? A lot of the use cases I know of for them are mid-level computer vision models that don't need to be frontier level.

I can no longer edit this, but want to expand on my comment.

I've seen those vision researchers want to train on H100s at the time and being told know, wait for the T4s.

I've seen T4s running BERT models for document classification.

When there are enough Blackwells in data centers that H100s are useless for inference by your standards (I don't know if we've arrived there or not yet), there will be people who, say, want to run the Taco Bell ordering chatbot on them. There will be people who have applications that are just fine with Qwen 2.5 who will be happy renting them.

There seems to be this crazy consensus that hyperscalers are going to go into their datacenters and throw away their old GPUs. The reality is they have a ton of paying customers for them.

And there may be insect identification apps from 2019 that say "you know what? H100s have gotten cheap enough I can use a VLLM so the user can describe where they saw the insect too", or the McDonald's website support chatbot developers say "Hey, the bigger cheapers have gotten cheap enough we can upgrade our models to Qwen 2.5".

The frontier level GPUs in e.g. AWS have a huge premium. When the newer generations come out, they will be able to cut prices to a bit of a premium over the operational costs and still make a profit, and there are a ton of down-market customers who will be interested, who aren't willing to try to outbid Anthropic for Blackwells.