Really, if that's the way you want to live, I say have at it. Other people having the option to live differently isn't going to stop you. It'll be decades before it starts getting hard to find gas stations, and by then EVs will have more range than you can handle.

It is pretty hard not to respond to the pure BS that anti-EV types spout. I know it rubs you the wrong way, but the alternative is to let people who don't know what they're talking about dominate public perceptions.

I wouldn't claim EVs are for everyone, but for many of us they are extremely convenient and economical to run. The corner cases where ICE is clearly more convenient are not a concern for everyone, and not a concern for a multi-car household considering making one of their cars an EV. We have an EV and a plug-in hybrid that runs as an EV probably 80% of the time. We hit the gas station with the plug-in about once every six weeks.

I heard an economist pose this question once. Why do companies have employees at all? Why not use contractors? Then you could hire just as much labor as you need, when you need it, then not pay for labor when you didn't need it.

His reason was the costs involved with finding contractors then negotiating agreements with them. I think there are other reasons, but for sure that's part of it.

But I think technology is pushing us into an intermediate position between the semi-permanent, often lifelong employment of a generation ago, and a world of contracting for everything. I think this is evidenced by a pattern I have seen where companies who are currently successful lay people off. It's not just in the tech world, this is happening in the service industry too.

When technology allows you to monitor the financial performance and cost of every department in an enterprise down to a fare-thee-well, it's easy to identify people you don't need so much in the upcoming quarters and let them go. Then with Internet hiring and automated application screening it's easy to hire those positions back in a year.

Now there's a lot of holes in this rosy (for management) scenario. Automated application screening is dog shit, for example. But you can do it, and you will find people; probably not the *best* people, but then you'll never know, in fact *nobody* will ever know. People will never get to know their jobs well, but again you won't ever know what you're missing. Most of all you will never have anything resembling loyalty from the people you hire; young people these days look at every job as transient. But you can't *measure* loyalty and in most cases, job competence with any precision. But you can track costs down to the penny.

In this case this wasn't about AI underperforming what was promised, but AI performance being exaggerated to cover the company's tracks as it offshored jobs to India. The intent was to use AI as an excuse to let Australian workers go, then to quietly replace them with Indian ones.

I don't think AI promises are "empty", but there is a lot of irrational enthusiasm out there getting ahead of the technology. I think for sure there are plenty of technical failures arising from technlogical hubris and naivite. And I think more instances where the technology is blamed for company failures or unpopular policies -- that practice goes back to the very early era of "computerizing" things like invoicing, so I don't see why this round of technological change would be any different.

But for sure, AI is coming for a lot of jobs. Past forms of automation haven't ended employment; they were just ways of increasing worker productivity. Companies still hired workers until the next marginal dollar spent wouldn't bring in a marginal dollar of revenue. But this time may be different. AI is replacing human thinking. It may be mediocre at thinking, but so are most humans. It may be an opportunity for companies to leverage a small number of humans with advanced cognitive skills, but I think for many companies the siren call of mediocre but really cheap will be too hard to resist.

I think this gets to the old debate about language learning vs acquisition. If you learn the gender of the noun âoe MÃdchenâ, that will prevent you from making errors, which is a good thing. But the language acquisition approach doesnâ(TM)t worry about you making mistakes. If youâ(TM)re exposed enough to the word being used correctly, âoedie MÃdchenâ eventually just sounds wrong. You will have acquired the gender of the noun without technically learning it. You donâ(TM)t even have to understand that nouns have gender.

It sounds great, but there is no way youâ(TM)re going to acquire enough German this way playing a game a few minutes a day to have a functional level of German in a short time, say for an upcoming trip. The company isnâ(TM)t as up front about this as they should be, but common sense should tell you that.

Duolingo is a way of putting time youâ(TM)re spending on useless phone activities like playing Candy Crush towards something useful. After say two years spending fifteen minutes a day on Duolingo French, youâ(TM)ll be able to read things like the train schedules in France, get the gist of simple newspaper articles, understand people who speak slowly and distinctly about things like directions to tourist sites. In other words a useful amount of French. Youâ(TM)ll have a leg up (I suppose) on more intensive ways of learning French.

But the idea you will reach B2 proficiency with Duolingo seems far fetched to me, given that Iâ(TM)m working on B1 and doubt I can pass the A2 exam. Youâ(TM)ll have covered the material by the end of the course, sure, but at this point itâ(TM)s pretty clear to me that actually mastering it requires actually communicating with fluent French speakers.

Which is fine. Nobody is stopping you from using more effective ways of learning. Duolingoâ(TM)s job, and its economic incentive, is to keep you engaged. This is why course content quality is important, and building courses out of AI slop is counterproductive. As a game, Duolingo isnâ(TM)t that much fun that youâ(TM)d play it even if the content is bad.

Thereâ(TM)s a huge difference in quality between Duolingo language courses. The flagship Spanish and French courses have by far the most material, human made material at that including native speaker voice actors. In about two years of studying both languages I have got to the point where I can follow along TV shows and read simple materials which I consider reasonable payback for effort I donâ(TM)t feel I got much out of the German course which I took at the same time, however German is a distant third in course quantity and quality. The AI features in the flagship courses are hit or miss, but generally good enough to be useful.

Reportedly the company is using AI generated content to pad out or even completely create less popular courses, but I literally havenâ(TM)t heard anyone who has good things to say about that stuff.

Judicious use of AI makes sense in an otherwise human deigned course (eg trying to respond to ad hoc user input conversationally). But betting the company on mostly AI generated courses does seem like a recipe for getting crushed by players like Google or OpenAI with vast and advanced models.

I wonder if they realize that the money they get through deals like his are still subject to Congressional budgetary controls. The Reagan administration didnâ(TM)t either ( or chose to ignore the constitutional limits on presidential power) when they tried to use money from clandestine sales of arms to the Iranians to set up a fund they could use to spend without Congressional control.

In case you never took that course, the classical economist David Ricardo figured out that if you were a tenant farmer choosing between two lots of land, the difference in the productivity of the lands makes no difference to you. Thatâ(TM)s because if a piece of land yielded, say, ten thousand dollars more revenue per year, the landlord would simply be able to charge ten thousand more in rent. In essence landlords can demand all these economic advantages their land offers to the tenant.

All these tech companies are fighting to create platforms which you, in essence, rent from them. Why do you want to use these platforms? Because they promise convenience, to save you time. Why do the tech companies want to be in the business of renting platforms deeply embedded in peopleâ(TM)s lives? Because they see the time theyâ(TM)re supposedly saving you as theirs, not yours.

Sure, the technology *could* save you time, thatâ(TM)s what youâ(TM)d want it for, but the technology companies will inevitably enshittify their service to point itâ(TM)s barely worth using, or even beyond that if they can make it hard enough for customers to extract themselves.

You should be careful of taking the claims of the Chinese Communist Party at face value. China has universal health insurance, but it is administered in a way that many people canâ(TM)t access critical care *services*.

For example if you are a rural guest worker in a city, you have health insurance which covers cancer treatment, but it requires you to go back to your home village to get that treatment, which probably isnâ(TM)t available there. If you are unemployed you have a different health insurance program, but its reimbursement rate is so low that most unemployed people canâ(TM)t afford treatment.

Authoritarian governments work hard to manage appearances, not substance. This is a clear example. It sounds egalitarian to say everyone has the same health insurance, but the way they got there was to engineer a system that didnâ(TM)t require them to do the hard work of making medical care available to everyone.

If you want an example of universal healthcare, go across the strait to Taiwan, which instituted universal healthcare in the 90s and now has what many regard as the best system in the world.

The COVID mRNA vaccines were the culmination of decades of research into genetic vaccines that could be in essence engineered to target a selected antigen without the years of trial and error that are required by the methods we have been using since the 1950s. Within days of the virus genome being published, they had a vaccine design, the months it took to get to the public were taken up with studies of the safety and effectiveness of the heretofore untested technology, ramping up production, and preparing for the distribution of a medicine that required cryogenic storage.

It would be unreasonable not to give the Trump administration credit for not mucking up this process. But the unprecedented speed of development wasnâ(TM)t due to Trump employing some kind of magical Fuhrermojo. It was a stroke good fortune that when the global pandemic epidemiologists have been worried about arrived, mRNA technology was just at the point where you could use it. Had it arrived a decade earlier the consequences would have been far worse, no matter who was president.

The lesson isnâ(TM)t that Trump is some kind of divine figure who willed a vaccine into existence, itâ(TM)s that basic research that is decades from practical application is important.

I watch a lot of maritime disaster videos, so YouTubeâ(TM)s genius algorithm thinks Iâ(TM)d be interested in traveling on a cruise ship.

Well, your buying power would be crippled.

Sure, itâ(TM)s quite possible for two people to exchange offhand remarks about the local weather apropos of nothing, with no broader point in mind. It happens all the time, even, I suppose, right in the middle of a discussion of the impact of climate change on the very parameters they were discussing.

The thing to understand is we're talking about sixth tenths of a degree warming since 1990, when averaged over *the entire globe* for the *entire year*. If the change were actually distributed that way -- evenly everywhere over the whole year -- nobody would notice any change whatsoever; there would be no natural system disruption. The temperature rise would be nearly impossible to detect against the natural background variation.

That's the thinking of people who point out that the weather outside their doors is unusually cool despite global warming. And if that was what climate change models actually predicted, they'd be right. But that's not what the models predict. They predict a patchwork of some places experiencing unusual heat while others experience unusual coolness, a patchwork that is constantly shifting over time. Only when you do the massive statistical work of averaging *everywhere, all the time* out over the course of the year does it manifest unambiguously as "warming".

In the short term -- over the course of the coming decade for example, -- it's less misleading to think of the troposphere becoming more *energetic*. When you consider six tenths of a degree increase across the roughly 10^18 kg of the troposphere, that is as vast, almost unthinkable amount of energy increase. Note that this also accompanied by a *cooling* of the stratosphere. Together these produce a a series of extreme weather events, both extreme heat *and* extreme cold, that aggregated into an average increase that's meaningless as a predictor of what any location experiences at any point in time.

Sure but the advantage of crops is you can easily scale your solar collectors by planting more acres. There are soybean farms with a half million acres out there that would produce significant amounts of biodiesel if used for that purpose. Now algae is a lot more efficient in a physics sense, but an equivalent algae facility would be on the order of 100,000 acres. The water requirements and environmental impacts of open algae pools would be almost unimaginable. Solar powered bioreactors would increase yields and minimize environmental costs, at enormous financial costs, although possibly this would be offset by economies of scale.

Either way a facility that produces economically significant amounts of algae biodiesel would be an engineering megaproject with higher capital and operating costs than crop based biodiesel, but an algae based energy economy is a cool idea for sci fi worldbuilding. In reality where only the most immediately economically profitable technologies survive, I wouldnâ(TM)t count on it being more than a niche application.