the vehicles start looking more like a wingless airplane than a car.

And what does the company's name mean? ;) (Hint: it's Greek)

It adds up to 40 miles per day, not 5. 5 would be a cloudy day.

I used to be anti-solar-panels-on-cars back when solar panels were expensive, and ones of reasonable efficiency were even more expensive - the argument was, "put it on your roof where it belongs". But that's just not the case any more. Adding solar is just not that much of a cost to the car. It adds some complexities, but mainly in the design / early manufacturing phase.

Also:

The average American drives 37 miles per day.

1) So if you're in a sunny climate, it covers all of said average-driver's driving. Otherwise, said average-driver has to plug in occasionally, but not nearly as often.

2) Most people drive less than the average (the average is skewed by a long-tail - small numbers of people who drive very far every year). What you actually should be meaning is the median US driver; the median drives 23 miles per day. Most Europeans, even less.

3) Even for said "average american", their daily average is skewed by long drives (e.g. road trips and similar). Wheren of course you're plugging in, you'd be plugging in even if the car was adding 80 miles a day. But when not on road trips, their daily average is lower.

4) Surely you can see the appeal of the tangential benefits, such as being unstrandable - where even if you run out in the middle of the desert 20 miles from the nearest town, you're still going to get there, just delayed (remember that EV ranges, if you drive very slowly, increase like 2x, so 40 miles a day becomes 80, so a 20 mile shortfall is only a ~4h delay on a sunny day).

5) Nobody is saying, "One car for everybody". Of course appeal varies by person and by location. Here in Iceland for example we have three problems. One, very little sun at all for a good chunk of the year. Two, even in the summer, when the days are long, the sun is mainly low and circles around you. Solar power just kinda sucks here in general. And three, the three-wheel config would mean that the centre wheel wouldn't align with tracks in the snow from other cars (although there is a slight advantage, in that it also wouldn't align with road ruts from studded tyres, which often fill with water in the rain and become hazardous).

But somewhere in the southern US, it's a great option.

For those who didn't follow it, it's not that it's a contact binary that is so neat in and of itself, it's that when they modeled it, they determined that, the collision that formed it was less than 5 meters per second (less than 11 mph / 18 kph). Like a parking lot fender bender, but with the cars being ~750 billion tonnes.

The increasing urbanization comes into it too. A stick shift in city traffic gets really annoying. A stick shift on the Winnemucca to Reno run is no problem at all, nor is it on the Albert Lea to Rapid City run.

And they finally fixed the 'can't figure out what gear to be in going up this hill' problem. That happened sometime between 2008 and 2020. Now if only GM can figure out how to build one that lasts for more than 80,000 miles.

Automatics still suck in the snow, but that's only a few times a year.

A clear sky being blue, the current sky is gray. ;-)

The 3AM thunderstorm did not knock out the local power, by the way.

No it's not a shortage of generating capacity. It's wild weather knocking down power poles. Hurricanes, tornadoes, derechos, ice storms in winter, thunderstorms, etc.

Then there is the squirrelian horde.

https://nebraskapublicmedia.or...

A squirrel managed to take down the power to the county seat a couple years ago. Then add in the transformers that are just plain old and the truck drivers who cut the corner a little too close and takes out the pole and power outages happen.

Yeah, there's two main problems:

1) People entering the wrong fields. For example, medicine really needs workers, at all levels, but not enough people are going into it.

2) Certain manual labour fields, like field work and home construction, because... well, I think we all know why there's a shortage of workers in those fields.

I noticed that the update rate in Mint seems quite elevated lately.

There is a lot of scrambling going on. AI does see, to have a value for slinging endproduct against the wall and targeting where ever something stuck.

I propose a continuous adjustment of clocks between summer and winter to avoid the step changes between daylight and standard time.

I mean this whole business of mean solar time has us meandering about when the sun rises and sets anyway,

Can it be programmed with a very large ax?

Just name it Wormtongue.

Or let's put this another way. Show of hands - how many of you "spicy autocorrect" / "stochastic parrot" people had "AI will start mass-solving Erdos problems" on your forecast list a couple years back? Huh, none of you? Fascinating!

Take some time to reassess your priors. And while you do so, understand that, yes, they are doing logic / reasoning.

They weren't discovered by an LLM. They were known conjectures that were proven by an automated solving language that was linked to an LLM.

I'll take "Things That Didn't Happen For $200", Alex.

Only a handful of meaningful proofs have ever been done by automated formal theorem solvers (the Four Colour Theorem being the most noteworthy example - but its proof is so long that humans can't verify it). By contrast, AI tools have been solving Erdos problems en masse. The majority of them just bog-standard commercial models. In case you need help, the only ones on that list that were hybrid (AI / non-AI) in the actual solving phase are:

1) AlphaProof / DeepMind Prover Agent / AlphaProof Nexus
2) Aristotle (Harmonic)
3) Seed Prover / Seed Prover 1.5 (ByteDance)
4) AxiomProver (Axiom Math)

In each of the above, LLMs come up with the lemmas / strategies but then use Monte Carlo search ("brute force") or likewise to investigate what they came up with. These are a minority. In the "AI Standalone" category, these "hybrid" tools made up only ~20% of attempts and successful proofs. Hybrid tools actually made more of a contribution in the "AI Alongside Literature" (related literature found afterward) and even more of the "AI Building On Literature" (related literature known beforehand) categories, which is the opposite of what people like you expect.

And even with the hybrid tools, it's still the AI doing the heavy lifting when it comes to strategy. Non-AI theorem solvers, again, don't have a spectacular record for churning out novel proofs to unsolved problems. Tools like Lean are more about mathematical rigour - a passive environment that requires a driver (a human or AI) to feed it actual strategies, lemmas, and proof steps. And no, you cannot brute force "strategy" in the vast majority of cases, which is, again, why automated theorem solvers don't have much of a track record with unsolved mathematical problems.

Let's take a random example: the disproof of the unit distance conjecture. It was solved purely by a general purpose commercial GPT model, not custom-trained to mathematics, with no external tools. Read what the various mathematicians reviewing / commenting on it have to say (sections #3 and onward). Seriously, don't skip reading them, actually read them. This was one of Erdos's favourite problems. He mentioned it commonly in his lectures. Essentially every mathematician working in complex geometry has thought about this problem. The approach that the model came up with was highly novel approach, based on CM-fields and class field towers.

I know you don't want to accept this reality, but it is the reality, so you better improve your ability to accept it,. The field of mathematics is already doing so.

Dang, link didn't post.

Ah, good 'ol "Model Collapse" theory that people have been pounding on for years now, predicting an imminent collapse in model capabilities. How has that been working out for you?