I was waiting for an Apple Car, but after doing the math on how much my gas car was costing me, I bought a tesla last summer. Honestly the EV (and especially anti-tesla) distortion field shocked me.
It is so much more 'there' than any car I've ever driven (and I've driven some nice ones).
It's like the mid-2000s jump from a flip-phone to a smart-phone. People wondered why they'd ever want to spend $500 on a smart-phone instead of $200 on a flip-phone. Then once they bought the smartphone, everybody wondered why they were paying $200 for a dumb-phone!
It's no comparison. Night and day improvement across the board, and onto boards you never even looked at for a car.
On 99% of the things you used to measure how good a car is, my electric is WAY better. But MAN it does so much more. You get back into a gas car and it's very obviously last-century thinking and last-century tech. With obvious features just missing.
If you haven't done the TOTAL cost of ownership between an electric and your gas car (gas, maintenance, depreciation, etc), then do it. It'll pay for itself. Even at today's gas prices.
And you really don't have to buy a tesla. They have the tech and interface you'd expect from a tech company (not the bolt-on poor UIs that the legacy automakers have), and they have a MUCH more seamless roadtrip experience (which is only a TINY bit of my use for a car anyway).
I can't wait to see what Apple comes out with, because I imagine I'll heavily consider switching. Until then though my advice to everybody is just do the math on an electric. They're ready. And SO much better.
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Since I bought, I've been following the tech behind the self-driving (which is really unrelated to how good an electric is), and Tesla's just-releasing private-beta of FSD is truly is 8-10 years ahead of anybody, even Apple.
It all comes down to neural net training.
Between Tesla's current supercomputer (5th largest in the world), and their "Dojo" supercomputer coming online this month, which will be MUCH faster at NN training, Tesla has a 1-2y head-start on the infrastructure of self-driving training.
But what Tesla has that nobody is CLOSE to is the number of tagged road events harvested for training. They have the fleet of cars (even the ones without FSD) collecting a bajillion miles on every different kind of road.
But the uninteresting miles really don't help.
What they've also built is a Data Engine which uses a separate NN which runs in shadow-mode alongside the existing Autopilot (on all cars) and looks for specifically targeted events/clips which they want more training on. (They also have ANOTHER neural-net stack which auto-tags the clips, saving a ridiculous amount of human time in tagging, having them just verifying the auto-tags.)
The head of tesla's AI team mentioned they needed more work on identifying cars with canoes on the top, or identifying "Stop, except when turning right" signs. So they built a special targeting AI just to harvest any of those situations any Tesla comes across. They have 100+ of these special targets they're harvesting right now and can change them at any time.
This Data Engine, which absolutely NEEDS a fleet of cars encountering the zillion different weird-ass edge-cases is absolutely essential.
Without that NOBODY can get close to the "long tail of nines" that self-driving is required to solve.