The reason why I don't believe they need a 70 billion dollar deal, is that Elon doesn't plan on buying himself out! And if they take the same structure as SpaceX, I would expect at least half of current shareholders to stay in the company, as well as most employees. That would then require 20-30 billion, on the high end. Far more feasible and a great strategy, really. Everyone's that's long stays, everyone that's medium to short term gets a nice bonus with the 420 payday, Every short dies, if everything goes as planned.
Readit NewsTesla is still maturing as a company; more to the point, they’re maturing as a manufacturer.
While other companies would order whole componants from vendors - Tesla will only order parts - and assemble in house. For instance - Toyota will order brake assemblies. While Tesla orders guards. Toyota will order a door - and Tesla a door panel. Even worse - Tesla has a history or delivering third parties sub-par China made tooling; and expecting 2-3x performance out of it - when in actuality their sub-par tooling will reduce efficiency. Trying to save money on tool manufacturing isn’t where mature companies cut corners. Trusting vendors to look after their own interests is a good practice (provided those vendors have a proven record)
Eventually Tesla will work it’s way into understanding that it’s core competencies are IP, design, and marketing - and leave the micro manufacturing to third parties.
A 6mo miss in production on one vehicle isn’t a sign of the times for a company with a 10yr road map. The markets aren’t super forgiving, but I think this will all get smoothed out as Tesla grows up.
One thing I don't see people mentioning too much, but tesla numbers are great for electric cars, but they're tiny, tiny compared to something like ford. I don't get why people assume tesla can negotiate similar prices for these things as other manufacturers can. I don't think they can. Who says it's cheaper for tesla to order like the big manufacturers do?
> Those in the know said electric cars in general were an unpractical waste of money.
Really? Who said that?
I would like to point out that you go to any article written about tesla from "the industry" viewpoint from at least 2008 to 2010. It's actually quite vitriolitic, actually.
So, based off the article, I don't agree with the idea of letting children at that age choose to drop topics because they aren't interested.
a) Interest often is triggered as you learn more about the subject.
If the argument is, it is the teachers responsibility to make topics interesting, I'd buy it. But allowing children at that age to drop topics seems like (to me) a disservice to the child
b) There are topics like history, geography, civics that (I believe) every child should learn. School is not just for trade skills, it's for learning to function as a part of the society, and these subjects are indispensable for understanding the larger world.
Having to run an "economy" or work in groups is not a suitable replacement for these "ideas" and skills.
In addition, at the risk of coming across as a traditional disciplinarian, I think there is merit in teaching children the discipline of forcing oneself to learn even when one is not interested in a topic. Ignoring the "it builds character" nonsense, the initial steps in most new things can seem tedious. But learning the basics allows one to explore a much larger world and choose what to develop mastery in.
Allowing such subject choice at such an young age, eliminating large parts of social sciences, etc. deprives children of these vital perspectives and opportunities, IMO. And being comfortable with tedium is important in its own right. That should not be the only thing one learns in a school (and I know that thats unfortunately too common in most schools), but doing away with it altogether is equally counter productive..
Student choice and voice can be incorporated in multiple ways, without eliminating entire subjects altogether..
Plugging one of my mentors here:
https://www.ted.com/speakers/kiran_sethi
What she has accomplished I think is a far more valuable contribution.
(Disclosure: I worked with her and designed the school's middle school (primary & middle school) science curriculum. )
Edit: added link to TED talk and subsequent disclaimer.
I would much rather drop something i had no interest in and pick up other interests and maybe later pick it up when interest flows there again, than be forced to wade trhough the hopelessness that is to sit a good portion of your day, learning something you hate. Schooling HAS wasted a lot of my lifetime, on things I HATED. Years on, I still resent this. I also dropped out of guitar after 1 week when I was young, but now, having rediscovered it in university, I do it with a renewed appreciation and vigour.I want it now. Now, not then. And that's just fine.
Ryudas commented on Building the Software 2.0 Stack by Andrej Karpathy [video] figure-eight.com/building... · Posted by u/fmihaila
Be afraid. Be very afraid.
If this guy was working on adtech, that would be fine. That's very error-tolerant. But this guy is working on automatic driving.
The basic mindset here is to run image classifiers to classify the objects in an image, then use the classifier output to decide what to do. There's no geometric analysis. That's scary. Classifiers just aren't that good. See the earlier article today about adversarial attacks on classifiers. Classifiers pick obscure details of images and use them to make decisions. Nobody seems to know yet how to prevent that. This problem shrinks with larger data sets, where hopefully the irrelevant details cancel out as noise, but, as the speaker points out, that breaks down when you have few training cases of certain situations.
The Google/Waymo approach is to get a point cloud with LIDAR and radar, profile the terrain and obstacles, and figure out where it's physically possible to go. That's geometry based. In parallel, a classifier system is trying to tag objects in the scene, which feeds into a system which tries to predict what other road users are going to do.
With that approach, a classifier result of "not identified" is fine. The system will detect and avoid it, or stop for it, and make conservative assumptions about its expected behavior. Chris Urmson, in his SXSW talk, showed video of a woman in a powered wheelchair chasing a turkey with a broom. This was not identified by the classifier, but it was clearly an obstruction, so the vehicle stopped for it. That's essential here. It has to do something safe with unidentified or mis-identified objects.
At Tesla, Musk insisted that this could be done with a camera alone because humans can drive on vision alone.[1] So Tesla has people trying to make camera-only driving work. Not very successfully so far.
"November or December of this year (2017), we should be able to go from a parking lot in California to a parking lot in New York, no controls touched at any point during the entire journey." - Musk, in April 2017. This guy is saying what Musk wants to hear.
[1] https://blog.ted.com/what-will-the-future-look-like-elon-mus...
In April 2017 elon was planning to have 20 or 10k of model 3's per week by now. That was not the case as we all know. Maybe we should be receptive to the change of priorities that occur when a massive problem such as that one happen. The fate of Tesla as a company is very much ingrained on model 3 production, and just saying that this demonstration has had a massive delay in a vacuum, without the context of the situation is disingenuous. Also I would like to just put forth the question of who here drives everyday. The human body does not, as far as i'm aware, have a volumetric sensor such as lidar. I'm not saying that the use or not of the information isn't important, but we certainly can do it just fine. It's shortsighted that we're dictating the tools we should use to solve a problem before the fact. I shudder to think of the day where I reject an implementation of a system based on the tools used, and not actual performance. To say an approach is wrong because it doesn't use geometric analysis is short sighted, that Classifiers aren't that good is shortsighted.
Ryudas commented on Tesla Faces Accelerating Rate of Model 3 Refunds blog.secondmeasure.com/20... · Posted by u/artsandsci
Yet another quarter has almost passed and, according to the Bloomberg estimate [1], Tesla will yet again miss their goal of producing 5.000 cars a week -- by far. In the most recent week, it was about half that, 2.560.
I guess some some people are just fed up with waiting.
I must say the bloomberg tracker can be highly inaccurate and vary its values depending on your location. Likely not the best place to judge current tesla production capabilities.
I mean, it is though.
Consider the quality of life that could've been achieved with the same energy cost, material cost, and eventual environmental cost--all so that nerds can collect Merkle pogs.
Consider the quality of life that would be gained by having the same energy all these "gamer" nerds use, with their consoles and graphics power on these useless. silly games. Or consuming netflix. Or watching movies. Or doing anything that is not directly used on the survival of the human race. This is a pedantic argument.
Ryudas commented on Tesla issues strongest statement yet blaming driver for deadly crash abc7news.com/automotive/e... · Posted by u/otalp
Uh, yes, they do.
See, I'm not sure if you know this... but most people are not Pilots.. ( disclaimer, I'm not only a programmer, but also hold an A&P and avionics license, as well as a few engine ratings ).
It is ABSOLUTELY on a manufacturer to make sure their potentially life ending feature, is not named in a way that can confuse the target audience. You know. NON PILOT car drivers.
auto means "by itself, automatic"...
And yet, I don't recall ever in any documentary or so, having seen the pilots get up and leave once the autopilot is on? They have humongous checklists to parse, do they not?
I want you to go on wikipedia(is that not mainstream enough) and search for the term Autopilot. Reads its ACTUAL definition and come back.please.
We were told, repeatedly, that Tesla would be producing 10,000 Model 3s per week in 2019, with a single factory. Suddenly, now, they don't have the capacity at ~6,000 per week and need multiple factories on zero year-over-year growth?