I suspect most systems are a mix of your platinum, gold and silver (and kidding me).

If it's like other systems, it will resort to transit schedule estimations when data is missing and then try to sync as live data becomes available.

   > My TVs are on the IoT network so that I can control them from Home Assistant, but they're blocked from accessing the internet. NS lookups are redirected or blocked (53 redirected to my local DNS resolver, 853 blocked),[...]

Unfortunately, from LG's surveillance capitalism point of view, the 0.001% of LG owners that can even think about doing that isn't even a drop in the bucket. They don't care about any one individual, and the vast majority of individuals don't care or understand what LG is doing as long as they can watch TV.

It's only a matter of time before another Cambridge Analytica situation pops up, except with better tools and vastly more data. Or maybe something we can't even imagine yet enabled by simply re-purposing ad-tech into something political and malevolent? Some people will be wise to it, of course, but if enough are caught up in it, it won't matter, we all lose as a whole.

  >...vocation of choice is misaligned with your personality...

The OP mentioned they were doing systems engineering. That's a very particular hellscape of grinding details. It involves being comfortable constantly dealing with a lack of control and flow. The good news is there many different kinds of work. I hope they can find their path.

I think engineering curriculums “stop short” on mathematics just as it starts becoming interesting, more generalized and before connections start becoming easy to see and remember. Math is often handled as a bag of tricks.

A lot of engineers would do well to review mathematics at a deeper level than their undergrad days, and that can mean hitting up real analysis, abstract algebra and other topics from scratch in a proof theoretic way.

Once that mathematical fluency is achieved, it becomes possible to ingest other topics at higher levels of sophistication, IMHO.

The problem, IMHO, was that rampant "xml-abuse" in the naughts. ws-* standards and over-engineered garbage like SOAP ("complex object access protocol") made people loathe XML.

I did like JAXB in Java, XLST, schemas, XPATH. Never got into XSL, but it seemed like good thing too. It worked best when your tooling manipulated it for you or at least helped you in an intelligent way. Much of the hate for XML came from situations where you had to deal with someone's over-the-top-one-size-fits all schema without the benefit of tooling to at least hint you in the right direction.

It still survives in WPF and c# *.proj files. If it were just me, I would still use it for object serialization. But json is king now even though it's inferior.

   > I really do not think it’s a difficult language to learn.

Of course, everyone in HN is "advanced" so what do I know!

    > You can learn something like ~90% of useful SQL in an afternoon.

It's an ugly little language that one has to come back to and re-learn over and over at different levels of sophistication. Nothing wrong with that, but to suggest it's trivial is a gross mischaracterization.

I did have in mind something more like the Socratic method, asking pointed questions of your mentee, guiding them but not pushing them. I suppose that in a weird way that essay is the Hunter S Thompson idea of the socratic method.

I really do think it's important to give thought to HOW to give help.

Especially in the technical communities, there's such an over-emphasis in "asking correctly". It perhaps started with usenet (think Eric S Raymond's INSUFFERABLE FAQ on "How To Ask Questions The Smart Way"), and ended with the persnickety and now thankfully moribund stackoverflow gameified and toxic question-and-answer forum.

But what about advice for giving help to someone?

There's plenty of ways that giving someone help can go horribly wrong, and I think that it's not uncommon for people to be blindsided by such a request.

I think the point of this is not to make "a product". It's just a fun project that you can build yourself or participate in some way with it's creation and/or funding.

It's not practical. That's OK.

All of these things are 100% bullshit and always have been. It's tragic that Google actually had people believing them when they championed "don't be evil".

Did Alibaba perform "an attack" or were they taking advantage of resources and going beyond Anthropic's terms of service? Didn't Anthropic do the same kinds of things when building their models?

These are all interesting questions, but they don't have to be addressed in full by a news blurb about a letter Anthropic wrote to some senators.

It was a timely story from Reuters. They do fast news feeds, like APnews. Could it have been better or more accurate? Sure, they could have gone into why distillation may or may not be seen as "an attack". But then it would have been a more involved story, defeating the purpose of a news feed.

The Reuters piece was "good enough". Some other place like the NYTimes or WSJ can follow up with more detailed investigative coverage if it's a worthwhile story.

  > Regulate or not regulate, but the government should not pick winners and losers.

  > They were asking for regulation.

I've heard others call it a marketing ploy that AI companies keep coming back to-- the idea that "it's soooo dangerous, we have to be careful".

Sure, some folks are going to be fantastically wealthy, that's OK to a large extent.

But, we're on the precipice of trillionaire's existing in a country where literally half of the population is functionally illiterate (yes, that's the USA), where the middle class is dissolving, and where we are approaching a feudal level wealth inequality-- and all this stuff is accelerating.

I mean, I guess it's not that bad. We still have a democracy. It's not like we have billionaires re-arranging political power and public resources for their pleasure and benefit. Oh wait, we do!

In biology there's the notion of a growth curve. It starts out with the familiar "compound interest" exponential growth, but unlike Econ-101 textbooks, that curve then proceeds to resource depletion (overshoot), followed by "die-off", followed by extinction, where (N -> 0, where N is usually something like yeast-cell count, but if you're applying this model to something else, it could be stuff like well-being or money).