adelie

it's a popular area for tourists and mountaineers, but also i think it's a lot easier to estimate missing/dead tourists since most of them will be there with tours/companies that have to keep track of exactly where they are.

adding easylist - annoyances (specifically the 'ai widgets' section) to your ublock filter lists should get rid of it! it doesn't catch it 100% of the time (the AI summary escapes when there's links above it in search results), but it gets rid of it most of the time.

hi! i live in SF. at trader joe's, these items would be priced at - $5 (bread loaf) + $5 (eggs) + $3 (yogurt) + $2 (onions) + $2 (tomatoes) + $1 (jalapeno) + $3 (parsley) = $21.

i'm rounding up on eggs and bread since you might be buying a more expensive variety, and guesstimating parsley because i haven't bought it from trader joe's before. everything else is pulled from my last few shopping trips.

if you're spending $50 on this, i would highly recommend finding a new grocery store.

my company (mid-size, publicly traded) is mandating [x] hours spent on AI per week. i have no idea how they're planning on measuring this, and as far as i can tell, neither does management.

suppose it's better than counting lines of code, though.

i'm a senior engineer at a mid-size, publicly traded company.

my team has largely avoided AI; our sister team has been quite gungho on it. i recently handed off a project to them that i'd scoped at about one sprint of work. they returned with a project design that involved four microservices, five new database tables, and an entirely new orchestration and observability layer. it took almost a week of back-and-forth to pare things down.

since then, they've spent several sprints delivering PRs that i now have to review. there's lots of things that don't work, don't make sense, or reinvent things we already have from scratch. almost half the code is dedicated to creating 'reusable' and 'modular' classes (read: boilerplate) for a project that was distinctly scoped as a one-off. as a result, this takes hours, and it's cut into my own sprint velocity. i'm doing all the hard work but receiving none of the credit.

management just told me that every engineer is now required to use AI. i'm tired.

because my company is mandating that we use motorboats instead of rowboats.

i can continue to row as a hobby, but i've been very lucky in that my work has always been something i genuinely enjoyed. now that it's become something that's actively burning me out, it's far harder to find time for hobbies and interests.

I'm not in translation, but a number of close friends are in the industry. Two trends I've noticed in the industry, which I think we're seeing mirrored in tech:

1. No one cares about quality. Even in fields you'd expect to require the 'human touch' (e.g. novel translation), publishers are replacing translators with AI. It doesn't matter if you have higher-level knowledge or skills if the company gains more from cutting your contract than it loses in sales.

2. Translation jobs have been replaced with jobs proofreading machine translations, which pays peanuts (since AI is 'doing most of the work') but in fact takes almost as much effort as translating from scratch (since AI is often wrong in very subtle ways). The comparison to PR reviews makes itself.

it feels good because we've turned coding into a gacha machine. you chase the high from when it works, and if it doesn't, you just throw more tokens at the problem.

i've seen this fairly often with internal libraries as well - a recent AI-assisted PR i reviewed included a complete reimplementation of our metrics collector interface.

suspect this happened because the reimplementation contained a number of standard/expected methods that we didn't have in our existing interface (because we didn't need them), so it was considered 'different' enough. but none of the code actually used those methods (because we didn't need them), so all this PR did was add a few hundred lines of cognitive overhead.

language-based professions like translation have been dying for years and no one has cared; they're not about to start now that the final nail's been put in the coffin.

generally speaking for han chinese folks, surnames are one character and given names are one or two characters (with two being more common, usually). so if you see a name that's 1-2 or 2-1 (i.e. liu yifei) and it's not one of the few known multi-character surnames, then you can safely assume that's their given name.

for a 1-1 name like yao ming, it's a little more difficult. some characters are definitely more common as surnames than others - the chinese term for 'common people' (百姓) actually refers to an old classic text where they compiled all the surnames they knew of! so when i see the name yao ming, i immediately recognize that 'yao' is a fairly common surname and 'ming' is not, and thus it's more likely (but not guaranteed!) that 'yao' is the surname here.

there's also some cases that are ambiguous when romanized, but not ambiguous in chinese. for example, consider the name 'wang chen,' where both 'wang' and 'chen' are common chinese surnames. however, if i saw it written out as 王, i would be able to recognize that 王 'wang' is a character that's primarily used for surnames, while 晨 'chen' is not.

chinese names can absolutely be gendered - for example, if i met a 璐, there's a 99% chance that name belongs to a woman because of its meaning (beautiful jade) and its character composition (王 radicals tend to be feminine). i feel like gender-ambiguous names have become more common in recent years, but maybe that's just me not keeping up with naming trends.

my understanding is that there's a bit of a catch-22 with data removal - if you request that a data broker remove ALL of your information, it's impossible for them to keep you from reappearing in their sources later on because that would require them to retain your information (so they can filter you out if you appear again).

my impression is that you can't replace competent programmers with chatGPT, but that hasn't stopped companies from trying (or simply accepting incompetency).