yessql

Well and customer retention and 0-60 times. Tesla owners love their cars more than any other brand.

What fancy computer model predicted this?

If they can't predict this, climate science must be wrong.

Of course global warming is real. But modeling the effects is very hard. I think deniers conflate the models with the trend.

Check out Venus.

400,000 reservations say it's enough info.

It's the batteries. Tesla has a big lead over other OEMs in battery cost. This is obvious in the energy storage space.

Also, if some new battery tech comes out, then Tesla will get their hands on it, being half the world's battery supply.

Because the valuation is insane. Tesla is worth as much as Nissan, yet has no sign of the ability to turn a profit.

I have a hundred shares. I wouldn't bet against Elon.

Tesla for the very low production run of Roadsters as well. (~2500)

Mobility is planned. Getting a ride somewhere via an app by an autonomous Tesla.

The only thing I can imagine is the Internet constellation. If retail consumers will be subscribing, then SpaceX doesn't really have a consumer presence yet. Seems like you could use Tesla to be the consumer facing company for the Internet. But Tesla could just buy exclusive access with resell rights...

They will do this. Tesla branded panels, inverters, batteries, car chargers, apps. All seamlessly integrated from one company. I'm curious whether they'll get into DC optimizers.

You could understand it as Civil Liberties in America. When the USA grants you permission to live here, and then takes it away midflight, then that's a problem with America, even if it is not a problem for "Americans".

It is definitely NOT public info that 2170's are low energy density. Elon even says they are the highest energy density and lowest cost cells.

https://electrek.co/2016/11/02/tesla-panasonic-2170-battery-...

The 2170 would be marginally less power dense. It would probably be easier just to use more 2170's than try to engineer some complicated mix.

Power density I can see. It would be harder to get the heat out of larger cylinders.

But how could the 2170 possibly be less energy dense? You have more active material per unit casing, so it almost certainly is more energy dense, based on geometry alone. Add the fact that you will have fewer connections, and the pack will be more energy dense as well.

With self-driving it is important to separate owning and using.

Why learn to walk when crawling is effective? When crawling you have hard guarantees that you won't fall down.

10 million square foot laser tag game.

It would probably be easiest to swap the cargo onto a charged tractor. Since there is no driver, you just have an automated station that swaps the tractors and the cargo goes on its way. Swapping a giant long haul battery would be very cumbersome.

I agree though that swapping and slower charging would make more sense than trying to charge at some multimegawatt level to reduce the cargo transit time.

Elon Musk says the world needs about 100 "gigafactories", so we need 3500 GWh of battery making capacity per year. At that rate it would take 7 years to reach 22 TWh of capacity.

You are conflating energy in kWh with storage capacity in kWh, so you are probably off by a couple orders of magnitude. If you had a long haul truck with a battery that can be recharged relatively quickly, it might get recharged a couple of times a day. So you have to multiply its capacity times recharges times number of days in service, so it could be used to store and release 1000x kWh nameplate capacity each year.

They moved oil prices a few percent. If they managed to move it much more, the US and other non OPEC countries are going to increase production, because more resources become economical.

On top of that, we now have a wide range of viable plug-in cars. If oil were to get up to $100/barrel again, lots of people would switch to a car that can cover 90%+ of their driving on electricity. $4/gallon gas really hurt our SUV market, but now we can make it a 20 kWh hybrid and avoid the pain at the pump.

I think this lack of demand for storage has prevented innovation. Why bother with grid storage, when day and night prices aren't much different? Well now there are times with negative prices, so there is going to be incentive to get paid to store electricity and sell it later. This incentive should grow as renewable penetration grows. If we have deep solar penetration, then there is the big problem that demand is very high in the early evening and the PV suddenly ramps down production as the sun sets. You can cycle your storage every buying dirt cheap solar and selling to the peak price a few hours later.

This is why Tesla's strategy is better than Google's. Tesla will get the data on those situations, because their data comes from every driver of their cars. Google gets data on Mountain View and downtown Austin.

Tesla is definitely behind Google now, but I'm saying their trajectory is orders of magnitude better, because they are collecting real world training data much faster. Humans show the minimal set of sensors needed for driving, and Tesla have a superset of that being delivered to customers today, which is being used to train their model. They get a lifetime of real world driving experience on those sensors every day.

That's a super conservative prediction which has zero growth from current sales numbers in it. Tesla grows has historically grown at about 50% per year.

That's the benefit of having 100,000 cars with all the sensors but humans performing all of the edge cases. Tesla can take data from all the cases where there was a deviation between what the car calculated it should do and what the driver did.

I don't think hand coded features are necessary. No one hand codes humans to drive.

Peak pricing can spread out demand a bit, and also, people can use much smaller vehicles most of the time. We buy cars for worst case size or conditions. Look around the parking lot of a white collar work place that is filled up with four wheel drive all terrain vehicles and pickup trucks.

Ride sharing for rush hour would use a ton of compact vehicles. Even if the number of vehicles is the same to account for peak usage, the majority of the vehicles will be much smaller and much less capable, and therefore much less profitable for manufacturers.

The argument is that if you aren't paying attention 99% of the time, that you wouldn't be capable of dropping whatever you are doing in order to take control. Also, these are meant to enable transportation for people incapable of driving.

Tesla will have 100,000 prototypes being trained in shadow mode for a billion miles per year across the globe within a year. Tesla will compare quite favorably

ML courses often start with linear regression, and if you build up complicated polynomials to find a nonintuitive model of your problem, I would definitely consider that machine learning.