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Tesla now using deep neural net for auto wipers (2019.40)

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In the release notes for 2019.40, Tesla confirms that it is using their first production deep neural net trained with over 1 million images of rain drops.

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Wondering if “manual adjustment” means to change from Auto to the I, II, III or IIII setting - or also includes pressing the stalk for single extra wipe
 
Tesla should pay us for having trained this neural net. Each time auto didn’t work and we did a manual wipe, we taught it.
Still a bull *sugar* implementation. Auto wipers were perfected decades ago and all this to save a few cents on a traditional sensor.
To boast about it takes great arrogance.
 
I knew this was coming. And why everyone should want HW3. I highly suspect auto high beam is also going to improve in the same way or already has in version 36. But I’ve been fooled before that it improved.

Look forward to this release.
 
I understand now, if the 3 uses its forward camera rather than a windscreen-mounted sensor, why the rain that settles overnight is not wiped off when I turn the car on in the morning. It presumably needs to see rain falling in front of the car before it will auto wipe.
 
????
If you are multiping the NN usage by the total population, you need to do the same for the other loads which puts you back where you started pencentage wise.

What does percentage have to do with it? Think CO2 emissions.

Even just the amount of energy wasted training the AI to spot rain... All for the sake of not fitting a $5 optical sensor that is more reliable anyway.
 
What does percentage have to do with it? Think CO2 emissions.

Even just the amount of energy wasted training the AI to spot rain... All for the sake of not fitting a $5 optical sensor that is more reliable anyway.
The optical sensor is not more reliable at detecting occusions in a different section of the windshield, it is useless for that.

$5 = 3kWh = 800 hours of operation at 3.6 W.
Edit dropped a decimal.
$5 = 30kWh = 8,000 hours of operation at 3.6 W.
Or, at 300k cars per year, Tesla saves $1.5 million to put toward other CO2 reducing initiatives like solar in GF1. Since solar is $1 a watt, that is a net reduction in emissions over an off the shelf sensor.


But, again, why pick on the rain sensor NN (which has a necessarily role) when there are much more power hungry drains on electricity which don't?
Radio - optional
Heated seats - optional
Heater steering wheel - optional
Clear view of the road - required, unless you want to drop the optional AP entirely which would save a lot more energy than 3.6W.
 
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Though I am very new to the Tesla model 3 I do know about neural networks. The training is done on a big computer somewhere. The error backpropagation algorithm for a deep NN is computationally intensive. But, once trained, the neural network can be deployed on low processing power devices, such as our Tesla 3 computer.

This assumes the rain in Spain is the same as the rain everywhere else, I suppose.
 
The optical sensor is not more reliable at detecting occusions in a different section of the windshield, it is useless for that.

$5 = 3kWh = 800 hours of operation at 3.6 W.
Edit dropped a decimal.
$5 = 30kWh = 8,000 hours of operation at 3.6 W.
Or, at 300k cars per year, Tesla saves $1.5 million to put toward other CO2 reducing initiatives like solar in GF1. Since solar is $1 a watt, that is a net reduction in emissions over an off the shelf sensor.


But, again, why pick on the rain sensor NN (which has a necessarily role) when there are much more power hungry drains on electricity which don't?
Radio - optional
Heated seats - optional
Heater steering wheel - optional
Clear view of the road - required, unless you want to drop the optional AP entirely which would save a lot more energy than 3.6W.

Jumping through hoops to save a $5 (maybe more?) sensor is actually pretty common in the auto industry. For example, General Motors has very sophisticated algorithms to estimate control air fuel ratio in their gasoline engines, so that they can use cheaper oxygen sensor (narrowband sensors). As you said it's millions of dollars and a lot of upfront work. If Tesla makes half a million cars next year it adds up.

The difference is, these kinds of neural nets need tons of real world data and the customer inevitably become beta testers.
 
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Jumping through hoops to save a $5 (maybe more?) sensor is actually pretty common in the auto industry. For example, General Motors has very sophisticated algorithms to estimate control air fuel ratio in their gasoline engines, so that they can use cheaper oxygen sensor (narrowband sensors). As you said it's millions of dollars and a lot of upfront work. If Tesla makes half a million cars next year it adds up.

The difference is, these kinds of neural nets need tons of real world data and the customer inevitably become beta testers.
Kid had a GM Flex Fuel car. Needed a tank of E85 every fall due to losing calibration.
Tesla isn't the only one with not reliable sw out there. At least T has OTA to fix it.
 
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The optical sensor is not more reliable at detecting occusions in a different section of the windshield, it is useless for that.

For those times when it's raining on one side of the window but not the other?

Most cars get around that extremely rare problem by having "tap to wipe" on one of the steering wheel stalks, along with the windscreen washer. No illegally messing with the touchscreen just to clean your window.

Or, at 300k cars per year, Tesla saves $1.5 million to put toward other CO2 reducing initiatives like solar in GF1.

Except they probably wasted 20x that amount getting it to work in the first place. How many man-hours and how many compute-hours on the training, which let's not forget they botched the first time and had to repeat and it still doesn't work very well.
 
Similar auto wiper sensors retail for $100-$300 on Amazon, so I suspect they cost OEMs at least $20. If correct, the ongoing BOM savings to Tesla is pretty significant.

I suspect that in hindsight they wish they'd included the rain sensor. The sensor omission is just one of many cost cutting measures employed in the M3, in order to build an "affordable" electric car. This one blew up in the test tube, but overall the strategy has been successful, IMO.
 
For those times when it's raining on one side of the window but not the other?

Most cars get around that extremely rare problem by having "tap to wipe" on one of the steering wheel stalks, along with the windscreen washer. No illegally messing with the touchscreen just to clean your window.

Uhh have you read the owner's manual? Press the button on the left stalk of the Model 3 and it is "tap to wipe" , and if you really press it in until it bottoms out, it turns on the windscreen washer.


Except they probably wasted 20x that amount getting it to work in the first place. How many man-hours and how many compute-hours on the training, which let's not forget they botched the first time and had to repeat and it still doesn't work very well.

That's not how it works. There's a saying in the automotive industry (where I work), "Software is free." It's a bit facetious but basically reducing piece cost has a much higher benefit financially than you think, because of the accounting. Software man hours are fungible, $5 per car at half a million a year is a big deal. It improves cash flow and feeds into the calculation of the profit margin a lot, something that public companies have to pay attention to. I've seen entire development programs (albeit smaller scale) to cost save sensors that cost a few dollars.

In the meantime, if the wipers annoy you, hit the button on the stalk.