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Tesla, TSLA & the Investment World: the Perpetual Investors' Roundtable

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Sounds like Bernie Sanders. Short sighted attempt to appeal to selfish greed and social envy plus a dose of right wing fear of somebody taking from you. Strategically this would cement Chinas gaining of the upper hand in electrification and the economic advantaged that come with it. If it were not for Tesla, the US carmakers wouldn't even pretend to try to compete.
/rant off
Not much impact on Tesla, but damaging to the US for sure, holding back and yielding innovation to others. 'Hybrids' lol
TFA said this is the Republicans (not Bernie Sanders) "appealing to selfish greed and social envy plus a dose of right wing fear..."
 
Is there a thread on this forum where Rivian financials are discussed? Asking for a friend. (No, really 😀)

Here you go:

 
I’ve only Supercharged twice, but neither time did I have to drop the trailer. Superchargers are so underutilized here in the Midwest, I’m able to swing in and charge while still leaving access to several chargers. I stay close by so I can move the rig if need be, but so far it hasn’t been a problem. And people seem to be more than willing to accommodate me. At my first stop in Richmond IN Thursday, I was there for about 45 minutes and talked to 20-30 people. I only needed to charge for about 15 minutes, but I couldn’t get away because of all the people! It was nuts!!
Do you feel all this attention on the Cybertruck is from potential EV buyers, or is it just mostly curious people?
 
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I hear a few people misunderstanding what Tesla and Elon are saying. In ER Elon said they aim to do useful work in the factory in the end of 2024. In this video the show the bot "useful" work in the factory now. Tweets confirm that multiple bots are doing "useful" work in the factory.

So what do they mean? Elon means useful=does the job better than a human. Better=cheaper and/or more reliable.
In the video they do "useful" work, ie they do an actual task that is "useful". But currently they need so many engineers/workers monitoring it that it costs more than just having a worker. Thus it's not useful yet. They hope to get there later this year.

The importance of this is that they are rapidly moving towards doing useful work. The first few bots will have cost hundreds of millions and save them hundreds of thousands, thus be terrible value. But once they scale, this cost is shared with many bots. The main importance is the speed of learning new jobs that is rapidly improving.

Current they are going working on getting from doing 0 to doing 1 useful job. This is a huge effort. Then they will use the results and learnings from this to go from 1 to 10 useful jobs. Then from 10 to 100. Each step the time it takes to adding an additional job will be going down. Eventually it will come to the point where a human only needs to demo the task once or some tasks will not even need to be demoed, the bot will just figure it out.



The impressive part here was imo that a single neural network was sorting all the batteries without any step by step guidance. It's a very long time horizon task. The normal way would have been having another stack counting the batteries and saying where each should go and the neural network doing this. Not the entire task done end2end.

For the navigation, I wonder if the neural network has gotten a path in a map and is autonomously following this path. I wonder if they have some positioning algorithm running to position itself in the map. Or if it was just walking in a circle forever as a task.

My guess is that they train one neural network to do all tasks and have some way to input which task is to be performed currently. If this is text based or just a number from a list of tasks would be interesting to know...

I'd take another slightly different angle on this. Before a humanoid robot, there are two other options for any job:
1. Have a human doing it. Pretty obvious.
2. Have a specialized automation doing it. This is actually what Optimus will be competing with. A good small team from a reputable university would be able to build an automation that does what Optimus is doing there in under a month. And it would be more reliable (much much simpler technologically) and cheaper to operate.

PS: I don't think they have the same neural net being trained to do all tasks. I don't see how that would work. What's your knowledge like in AI? I've taken a couple of courses and building some projects that involve various AI algorithms, but they're mostly hobby at this stage
 
Some blatant bot speculation:
One of the 'issues' for the bot, is that it does not have the data that FSD has. The sheer gigatonnage of video clips amassed by millions of tesla cars provides a huge amount of data that dojo can chunk through to train the FSD network for learning how to drive in all situations and circumstances. This has been key to FSD V12 and seems to be the holy grail of getting real-world AI. However, the bot does not have this data AT ALL, and even given today's video of a dozen or so employees wearing VR headsets, its definitely not going to be enough, Unless Tesla wants to hire 50,000 bot-trainers to wear VR headsets all day, which is never going to happen.

However there is a solution.

Human neural networks learn in first and third person. We learn how to catch a ball partly by watching lots of other people catch balls, but also, most helpfully, by trying and failing, again and again and again. In many ways the first person approach is better, because you start off with way more fails (disengagements) and the data is a one-to-one mapping to our own movements.

With FSD V12, the cars are overwhelmingly learning from third hand video clips, and from observing what humans do in each situation. Almost all the data is successes, where the car did not crash. Because the real world failure condition of driving is often death, the cars cannot be left to just experiment and see what happens.

The lack of huge datasets for each task means its likely that the bot learning may have to skew towards 'try it and see' rather than 'see how its done'. In a factory carrying stuff around, the failure condition isn't too lethal, so this is acceptable, and its all on company premises anyway. As a result, I think there will be a very rapid deployment of bots to work alongside humans at the factory. You might have one person unloading trucks full of of headlights, and 4 bots trying' to help with this task, and doing it really, really badly for quite a while.

Why does this matter?

Firstly we might see a lot of bots get produced and deployed on the factory floor. Videos may leak of this. We should not get too excited. This will be for training, and will NOT be either efficient, or a sign that sales are imminent.
Secondly, that might mean there is an actual production line for bots way in advance of them being useful. It might also mean a fair bit of capital expenditure. This will be seized by the excitable as sign that 'bot production is ramping up, but it will not mean much.

IF it turns out that Texas or Fremont has 500 bots working in the factory in a years time, don't get excited. That may be just a complete clown car of rubbish bots dropping stuff and walking into doors. This is to be expected, but any leaked videos will be a FUD bonanza. Don't fall for it.

IMHO there is a big difference between FSD and bot: FSD is designed to be used on public roads and has to deal with lots and lots of crazy edge cases that come along once in 10 years or so. To make it safe for those, the training requires tons of driving data because such cases have to be included.

For the bots, on the other hand, the most likely (and still possibly very profitable) use case is working in a well defined factory environment, where they are only trained to do one job as seen in the video. That requires massively less training data. Also, as you said such jobs usually don´t put anyones life at threat when things go wrong, so you can do much more trial and error which reduces the time to get the bots to work even more. You don´t need one bot that can work on lots of different jobs without new training, while FSD has to do traffic circles, unprotected lefts, blinking red lights, emergency vehicles, construction areas, rain, snow... you get the idea - in one single piece of software.

Regulatory problems should be much easier to as the bots will likely not be working im public places accessible to anyone (at least in the beginning).