Actually, the biggest reason that adoption rates are much, much higher in Australia (despite lack of infrastructure), is that Australia has access to less expensive vehicles imported from China and SK.

The US, otoh, is too busy trying to protect its legacy automakers, who, much as they did in the 70s, decided to ignore trends and continue to sell oversized, overpriced, gas-guzzling vehicles for as long as they could convince the American market to buy them.

"You presume they have the available funds to update the household. It's an easy thing for early adopters who tend to be wealthier. Its another things for the mass market that is more budget conscious. And may also live in older homes that may need some modernization for the charger installation."

Level one charging can in fact be sufficient for those with commutes less than or equal to the national average. It even works for longer commutes to "top off" the battery during the week and hitting the afore-mentioned Walmart or other charger on the weekend while shopping.

"What is “local” is different in the US and EU.."

Again, you focused on the EU while ignoring China and Australia. Australia, in particular, almost exactly mirrors the US in regard to size and driving patterns. But again, local is local. The average commute in the US is 27min. It's 25min in the EU. Australia takes 63.7 minutes! (And before you start on transit, driving is the still most common way to get to work in Europe, with 59% of EU workers using private cars as their primary mode of transportation,)

"They’ve done far better with the public infrastructure required "

Nope. The United States has a significantly more extensive and robust public charging infrastructure than Australia. The US benefits from a massive rollout of Tesla Superchargers open to all EVs, billions in federal NEVI (National Electric Vehicle Infrastructure) funding, and rapid deployment of high-voltage (800V) stations by networks like Electrify America and Ionna.

Your arguments are a couple of years out of date, and again keep focusing on how we're so "different" from the rest of the world.

We're not that exceptional.

As an EV owner, I have to disagree with most of what you said.

The U.S. driving pattern also isn’t nearly as unique as it’s often portrayed. Like Europe, most driving consists of commuting, errands, and local trips. Roughly 90% of Americans live in urban or suburban areas, and only a minority take multiple long-distance road trips each year.

Charging infrastructure has improved enormously in just the past few years. Companies like Shell and Walmart are building networks alongside Tesla, and even my local Walmart in the Midwest has chargers. Chargers continue to get faster, but even today’s charging times often line up with the rest stops or meal breaks I’d be making on a road trip anyway.

About two-thirds of U.S. households own their homes, giving them access to some form of home charging. The biggest challenge remains apartment dwellers, where charging infrastructure still lags. That’s a legitimate issue, but it’s an infrastructure problem, not a flaw inherent to EVs.

And it’s worth noting that EV adoption has surged in countries like China and Australia, the latter having driving distances and population distribution that are often compared to the U.S.

I’m just tired of hearing that America is somehow “special,” and that technologies and solutions working successfully in much of the rest of the world are uniquely destined to fail here.

OK, which particular aspect of the LLM learning do you think doesn't exist in the human brain? Backprop exists (and the other training methods the brain uses has similar effects), embeddings more or less exists and seems to be very similar to the LLM embeddings (shown by brain activation in various areas linearly matching with embeddings) - see e.g. High-level visual representations in the human brain are aligned with large language models (Adrien Doerig et al, 2025), and speech/text generation by humans has similar error patterns as for LLMs.

They obviously don't learn in the EXACT same way, but there's also clearly a lot of bits that are the same, and I'm fairly sure nobody knows how much is similar yet, particularly not weighted by importance.
 

It is more than that. Americans are buying a few more EVs, but by and large most of the sales are going to oversized, overweight, fully automatic SUVs and pickup trucks.

On one hand they've bought into Detroit marketing that tells them that's what they want and need... and on the other, it may in fact be what they need since US obesity rates are at all time highs.

Many simply don't fit in small sedans and sport cars any more.

Correct, as anyone can see by looking at who they rounded up.

"Then they came for the Socialists
And I did not speak out
Because I was not a Socialist

Then they came for the trade unionists
And I did not speak out
Because I was not a trade unionist "

But in the next state over, the next company will also treat you as badly as they can get away with.

The natural model for a programmer's union is the Screen Actor's Guild. That's another field with a wide range of talent. SAG members can get the best pay their agents can negotiate, lots for stars. But everyone is protected from exploitation.

Where is one of the last places you'd expect a rear-view mirror?

The SR-71 had one.

The practical use case was checking the deployment of the landing parachute.

Speaking of forensics, if you're a law-abiding citizen who just wants to keep private information private, iOS lockdown mode will reported halt the Coruna forensics tool in its tracks. Source, Eva Galperin at EFF. It's a royal PITA to use though.

Or, as Robert Morris Sr. said about breaking confidential communications, "Look for plaintext. It comes up in the darnedest place", or words to that effect.

There's no ambiguity. Copyright is for humans. Period. Cory Doctorow goes into this pretty well.

https://pluralistic.net/2026/0...

Tell that to Elon.

"they are the ones for whom reasonable fact-based argument"

Perhaps, but when are we going to see one?

iOS is using on device machine learning models for text translation and dictation today.

Define AI. Modern smartphones use ML tools and models everywhere, from text prediction to touch detection to voice recognition to photo processing. They're not just limited to chat bots.