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In a way, that is a good thing..haha. How much of a surprise is 10B from Solar roof and storage going to surprise people next year. Assuming 20K Solar roofs would be about billion dollars alone from something that did not exist just a year ago.
I agree with the green bolded sentence, but not the red bolded sentence - if that's your projection.
I expect the mix of $10B TE revenue in 2018 to be relatively even between 50% SolarRoof/Panels and 50% Powerpack/Powerwall.
Market participants are making the same mistake of linear/exponential projection with Solar Roof.
My contribution to TE this year....live update.
View attachment 253104
The hardware is and will be so cheap in 5 years, but it wont matter if you dont have the software. Any car company can buy nVidia hardware but not many can do the software.
For what it's worth, last time with Model X took them 5-6 months to mass production, from the moment they had couple hundreds made (Dec 31 '15 -June '16). Based on that it would be Feb-March.If Sept 26 marks the start of the production assembly line, will 2 months be sufficient for it to be
substantially debugged? Say at the rate of 1000 cars per week and accelerating by Nov 26.
2 months of debugging should get them considerably ahead is my hunch. In my view when that
becomes apparent the stock price should go higher.
Options expiring beyond that end of November would make more sense .
Thank you; this is helpful. Can you please elaborate on how you interpret this data? Is it useful for predicting the future?
My contribution to TE this year....live update.
View attachment 253104
I just had 9.5KW installed myself, but no Tesla here in Chicago land. I did however go with Panasonic 330W HIT panels so its as close as I could get. No powerwalls yet, because they have net metering that basically acts like a battery.
Responsible for part of the pop?
The Dutch government confirms plan to ban new petrol and diesel cars by 2030
The top layer software should be end-product specific, so I don’t think NVidia’s role at this level is anything beyond demonstrating a reference design.If I remember correctly nVidia helps develop the software for those who need it.
Elon Musk:
Exactly. Tesla is absurdly overvalued if based on the past, but that's irrelevant. A stock price represents risk-adjusted future cash flows.
I have struggled with this problem on NVDA. I am a programmer and I know a little bit...
NVidia was a sleeper hit... they make graphics cards that seemed like an unimportant PC subsystem... but it's turning out to be more important than the cpu... It can be used for games, crypto-currency mining, AR, VR and machine learning. The opportunity in front of them is huge. They may be bigger than Intel down the road.
Their advantage imho is CUDA. It's a proprietary api that runs on their cards and is considered superior (faster) to competitors and open standards like openCL/GL. A lot of open source machine learning software uses cuda at the lowest levels.... So it has an ecosystem around it that is going to be hard to overcome, much like windows operating system.
However, there may be competition. Currently AMD is their main competition. Intel also recently bought Nervana to compete with them.
Google has written TensorFlow, an open source machine learning library, which runs on cuda or on their own proprietary chips called TPUs. These chips are not available for sale but you can use them in the Google cloud. Google cloud has not really taken off yet and I dont know if it will.
Also, Tesla has been hiring people with expertise in chip making... so they may also build their own chips to process their self driving/machine learning apps. Tesla is buying chps from Nvidia in 2 ways. One way is in the cars... to do the self driving (inference) and the other way is the presumably have a data center that processes the (training) data from all the cars and generates the program that is downloaded to the cars. I suspect Tesla will also need the same chip technology in their factory automation.
Elon recently said that it was close when deciding between NVidia or competitors... I assume that was a bullshit statement for negotiation purposes... Here is a thread where machine learning programmers bemoan NVidia's dominance and links to papers that indicate CUDA is 4x faster than OpenCL
Deep learning is so dependent on nVidia. Are there any alternatives even on the horizon? • r/MachineLearning