As a heavily sarcastic and often irreverent person myself, I think sarcasm translates very poorly to online communication in public forums. The main problem is the complete lack of context where you don't know where a commenter is actually coming from, so you lack the ability to interpret them making a particular statement as a deliberate absurdity.
So sure, maybe talking to friends I would find myself using the word "fair" that way as a punchline to a joke. But they'd know I'm not looking to normalize the new dynamic, rather than highlighting its perversity.
Then specifically here, OP doubled down on the argument rather than repudiating it. So I don't think it's really correct to call it sarcasm.
Thanks. It took 6 levels of comments to point the obvious sarcasm. May be I give too much credit to average HN'er skills at recognizing sarcasm without an explicit /s :)
I believe the thinking is serrated knives work best for things where the skin is tough, but the internal structure is weak. So crusty bread with a lot of air inside.
Also, surprisingly, tomatoes. Lots of people suggest small serrated knives (if you have them) for tomatoes.
I would say they are changing the promise, not breaking it. Breaking it would have been if they sold data with the old description (which is not the case, is it?).
Since they claim that they are not changing the promise, only being more clear about it, the implication is that they did sell data under the old description.
it does, but i dont use it much due to it being too slow and heavy on memory on my ryzen 5950x (32 threads) on windows. a couple seconds of tracing goes into tens of gigabytes of ram.
Yeah I had issues with the Tracy sampler. It didn’t “just work” the way Superluminal did.
My only issue with Superluminal is I can’t get proper callstacks for interpreted languages like Python. It treats all the CPP callstacks as the same. Not sure if Tracy can handle that nicely or not…
I don't see why some tokens could not get associated with "begins with A". The models are obviously not trained enough on such examples to do it consistently, but I would not say they are "blind".
