Note that I refer to Windows Mobile, before Windows Phone 7. I consider Windows Phone 7 their first vaguely credible attempt at a mobile centric UI, and then Windows 8 the consequence of trying to throw desktop/laptop under the bus for the sake of trying to popularize their take on mobile UI. Admittedly, I was never interested in bothering to give Windows Phone 7+ a chance, but some others I knew at least made me think it was a credibly usable multi-touch UI for handhelds.

If there was a possible strategy for Microsoft to get into the mobile game, this would have been it.

Their first pass failed to really optimize for mobile at all, so you had mobile devices with clunky interfaces.

Then when they finally saw that a more targeted UI for mobile was needed, they went the other way, screwing up desktop by trying to make it look like their vision of a mobile OS, all while having the phones still unable to use monitors so there wasn't really any 'synergy' between the platforms despite throwing the desktop experience under the bus.

Now I've seen samsung and motorola phones drive desktops, but good luck which ones actually support displayport alt-mode on the usb-c.... However not *too* much of a loss because they both have just utterly shitty window managers with no options to swap it out for anything vaguely more capable despite a plethora of options in the space.

I think Android has at least got *some* of the message with respect to applications, carrying over from the ChromeOS support for linux applications, however it was sad that even as a pure linux person who uses desktop linux without a hint of Windows, I actually thought using Linux under ChromeOS was even worse than WSL.

Now if by some miracle, I can have an Android phone with displayport that will let me run Plasma desktop in a normal way, they can take my money so fast. Of course, realistically speaking, they'll have like 3 or 4 people excited for that and wonder why they wasted money pandering to us..

While it may certainly reduce any sympathy, 'losing money' is still an apt term.

If I intercepted one of your paychecks, I think you'd fairly say that you 'lost money', despite having, presumably, some savings.

Now if you are a billionaire bemoaning losing a few thousand, I'm not going to be terribly moved by your plight, but I would still permit the phrase 'lost money'.

unless mobile gets full computer capabilities.

But I get why companies want you to only be able to use your computer the way they want you to.

But the phrasing should be about losing money, not "losing" cars.

Make piracy the better alternative in every way and people will pirate.

Make a legal transaction the better alternative in every way (ok, except money) and people will use that.

It really is so simple, even an executive should be able to understand it.

While that might be an interesting technical challenge, one has to wonder why. Just because something is "culture" doesn't mean it should be copied. Slavery was part of human culture for countless millenia. To the point where we haven't even gotten around to updating our "holy books" that all treat it as something perfectly normal. That's how normal slavery used to be.

(for the braindead: No, I'm not comparing Taarof to slavery. I'm just making a point with an extreme example.)

The thing is something called unintended consequences. So in order to teach an LLM Taarof you have to teach it to lie, to say things that don't mean what the words mean. And to hear something different from what the user says. Our current level of AI already has enough problems as it is. Do we really want to teach it to lie and to misread? Just because some people made that part of their culture?

Instead of treating LLMs like humans, how about just treating them as the machines they are? I'm pretty sure the Persians don't expect their light switches to haggle over whether to turn on the light or not, right? I stand corrected if light switches in Iran only turn on after toggling them at least three times, but I don't think so. In other words: This cultural expectation only extends to humans. Maybe just let the people complaining know that AIs are not actually human?

Nazism isn't an internet insult. It was an actual, real thing that happened in this world, with an actual, real ideology, and the core of this ideology was racial-based social Darwinism.

BTW, re: the Congo in particular: the most common traditional type of fishing is basket fishing with woven funnels suspended in the rapids. You sure as hell better know how to swim if you want to do that.

Famous angler Jeremy Wade referred to the local Congo fishermen as nearly suicidal, just diving into the rapids to get nets unstuck and the like.

SIGH.

There were 10 people chosen and people with dark skin in the USA make up about 1 out of 8 Americans.

1 in 8 is 12,5%.

African-American without mixed race in 2024 is estimated at 46,3M, or 14,2%
With mixed race, that rises to 51,6M, or 15,8% of the population.
Some hispanics have dark skin, some light. In 2023 there were 62,5%, representing 19% of the population (though there's a small overlap with black - doesn't affect the numbers much).
In 2023, Asians were 25,8M people, or 7,7% of the population. This is again a diverse group with mixed skin tones (for example, the Indian subcontinent)
In 2023, there were 1,6M people (0,49%) of pacific island ancestry and 3,3M native Americans - again, mixed skin tones.
People of Mediterranean European ancestry often have so-called "olive" complexions.

With a strict definition of dark skin, you're probably talking like 1 in 6 or so (~16,7%). With a looser definition, you could be talking upwards of 40% or more of the population.

The chances of the 10 people to be a perfect representation of the racial demographics of the USA is quite small.

Here are the actual odds of selecting no dark-skinned people at different population percentages being "dark skinned", by one's definition of "dark":

15%: 1 in 4
20%: 1 in 8
25%: 1 in 17
30%: 1 in 34
35%: 1 in 73
40%: 1 in 165

Then consider that NASA astronauts are required to pass a swimming test

It is not a test of swimming prowess, just of an ability to not drown. You have to be able to do three lengths of a 25-meter pool without stopping, three lengths of the pool in a flight suit and tennis shoes, and tread water for 10 minutes while wearing a flight suit. This is not some massively imposing task. You don't have to be Michael Phelps to become an astronaut.

and as a general rule those with African ancestry tend to have less stamina in swimming than those with lighter skin

Yes, white athletes tend to have an advantage in swimming. A 1,5% advantage. While a 1,5% advantage may be of good relevance at the highest level of a sport, it's hardly meaningful in a "can you tread water with a flight suit on" test.

Think of the different races as just really big families

That is not how genetics work, and is instead the pseudoscience that drove fascist movements, and in particular, Nazism.

There is far more genetic diversity within a given "race" than between them. Certain genetic traits tend to have strong correlates - for example dark skin and sickle cell anemia - but that's not because races are some sort of genetic isolates, but rather for very practical reasons (dark skin is an adaptation to not die of skin cancer in the tropics, and sickle cell disease is a consequence of a genetic adaptation to not die of malaria which also happens to be found in such climates). But the vast majority of genes don't have such strong correlates.

The concept of "race" as a distinct biological category is not supported by modern genetics.

If we are to ignore skin color and just put one big family up against another big family on swimming ability then just due to random mutations, perhaps some Darwinian selection way back in the family tree, one family will swim better than the other

The main "racial difference" in swimming ability in the US is "inherited", that is, parents who don't know how to swim tend to not teach their kids how to swim. As a result, white children are 56% more likely to receive swimming lessons than black children. One can expect that to directly correspond to an advantage in adulthood. But again, the ability to tread water is not out there knocking 90% of astronaut candidates out of the race - especially given that astronaut candidates tend to be athletic and motivated to learn new skills.

People with light skin tend to have ancestors that had to go fishing for their protein

Utter tripe. Fish consumption has no correlation with skin colour. How much fish do you think your average herder or plains horseman ate? And fish is massively important in much of Africa - in coastal areas (Gabon, Ghana, Sierra Leone in particular note), along the Congo (it's literally the world's largest river, people have been fishing it since time immemorial), Lake Victoria, Lake Chad, the Niger Delta, etc etc. What sort of racist stereotype world are you living in where black people don't fish?

Having a large candidate pool relative to the number chosen makes it easier to show bias and still get high-quality candidaes, not harder.

For deaf, since one of the features is captioning a speaker.

On the one hand, I know all too well that the AI will screw it up some.

However, if you watch closed captioning, you know that the captions are already frequently messed up, long before even AI was a possible strategy. Usually the live captioned stuff had lower quality, but you'd see it in scripted shows too.

I also wonder about the converse, captioning someone using sign language for those that don't know it.

But that FOV is just so tiny....

It holds up in some cases, not in others, and calculating an average muddles that.

Personally, I use AI coding assists for two purposes quite successfully: a) more intelligent auto-complete and b) writing a piece of code using a common, well understood algorithm (i.e. lots of sources the AI could learn from) in the specific programming language or setup that I need.

It turns out that it is much faster and almost as reliable to have the AI do that then finding a few examples on github and stackoverflow, checking which ones are actually decent, and translating them myself.

Anything more complex than that and it starts being a coin toss. Sometimes it works, sometimes it's a waste of time. So I've stopped doing that because coding it myself is faster and the result better than babysitting an AI.

And when you need to optimize for a specific parameter - speed, memory, etc. - you can just about forget AI.

Hey, industry, I've got an idea: If you need specific, recent, skills (especially in the framework-of-the-month class), how about you train people in them?

That used to be the norm. Companies would hire apprentices, train them in the exact skills needed, then at the end hire them as proper employees. These days, though, the training part is outsourced to the education system. And that's just dumb in so many ways.

Universities should not train the flavour of the moment. Because by the time people graduate, that may have already shifted elsewhere. Universities train the basics and the thinking needed to grow into nearby fields. Yes, thinking is a skill that can be trained.

Case in point: When I was in university, there was one short course on cybersecurity. And yet that's been my profession for over two decades now. There were zero courses on AI. And yet there are whitepapers on AI with me as a co-author. And of the seven programming languages I learnt in university, I haven't used even one of them ever professionally and only one privately (C, of course. You can never go wrong learning C. If you have a university diploma in computer science and they didn't teach you C, demand your money back). Ok, if you count SQL as a programming language, it's eight and I did use that professionally a few times. But I consider none of them a waste of time. Ok, Haskell maybe. The actual skill acquired was "programming", not a particular language.

Should universities teach about AI? Yes, I think so. Should they teach how to prompt engineer for ChatGPT 4? Totally not. That'll be obsolete before they even graduate.

So if your company needs people who have a specific AI-related skill (like prompt engineering) and know a specific AI tool or model - find them or train them. Don't demand that other people train them for you.

FFS, we complain about freeloaders everywhere, but the industry has become a cesspool of freeloaders these days.

The number of people isn't the problem here.

The "started every" is.

How did they not catch that during development and found a solution? I mean, the meme's where a TV ad starts Alexa and orders 10 large pizzas are a decade old now.