I'm glad that you asserted that you do have potential hidden bias and say that you used an LLM to judge the tone of an article partly pertaining to AI usage in coding right after.
The main difference is (simple) calculators are deterministic and monotonic. Meaning it executes a set of instructions in a predetermined way to produce its output. Bringing LLMs to that level is a whole another ball game. But we'll see, perhaps the arithmetic nature of algorithms will be replaced by a whole lot of tensors in the near future.
I believe poisonous loops of non-sense text are the best choice in terms of LLM capabilities and human distinguishing potential; the next iteration could be non-sense with reasonably intact grammar and content. At the very least, show some content whilst doing the PoW (isn't the point rising computational costs? Give me something like YouTube video decryption instead of having me wait at least) OR use the PoW for some useful protein-folding, finding the next prime, or an alternative monetization scheme.
My guess is its an implementation error, not an hardware limitation. I have two 10-year-old devices and one passes instantaneously while the other halts for a good half minute every time.
Abuse such as this wasn't uncommon before, email platforms with lax ratelimits have always been abused through their clients' unsecured infrastructure. The only difference in post-LLM world is the amount of platforms as well as clients popping up in this space with dubious code quality that may lead to more attacks as;
a) having an email-sending product typically meant you had a project with a lot of effort invested into it as well as knowledge
b) the models, tokens spent and review done differs in the world of vibecoding and there is a race to the bottom to produce, produce, produce. Quantity > quality
I believe new (programming) languages will emerge both for LLMs to parse and take instructions from as well as for them to generate code in. The former is because English is a nuanced language evolved for human usage which the LLMs don't quite need, with the only advantage of it being a metric ton of training material. Same goes for Rust, Go and other languages LLMs do primarily well coding in, which all have concepts geared towards human convenience.
I agree. From the get-go, Bun was apparent in its design philosophy: we do everything you'd ever want; runtime, bundler, test suite, package manager, all in a new breaking patch each week. With each and every one blowing the established competition out, better, faster and stronger. But it was glaringly obvious that they'd do anything but Keep It Simple Stupid. It was obvious that the only production environment it would see the light of the day in the near future would be YC startups burning one after another at the speed of an accelerant. Now, they're past the point of no return.
Obscurity can be combined with security for much better results. Machines as well as AI in extension thrives off patterns and making illogical off-pattern decisions is usually to the benefit of the defender, not the attacker. As you said, the attacker has a wide attack surface to cover while the defender only has to fortify his home NAT. E.g. port knocking may very well throw off the hoard of scanners on the wide net simply because its not standart and the combination is known only to you. Similarly, fail2ban may not work as well on a standart SSH port, because every attacker is going to hammer that and one may get your misconfigured password root login right.
Now, in both instances, the obscurity provided does not necessarily cure your infrastructure's vulnerabilities, a dedicated attacker wouldn't have a single problem with either of these. But for someone who hammers the whole internet in a dim hope of finding another Wordpress server from 2017, or the latest flawed online security cam, your disguise is as good as perfect.