The description of SmartSummon about halfway through the talk is interesting. One of the views looks like SLAM using a particle filter, but Andrej seems to say that it's done entirely within a neural net.
Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
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Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#172Earlier quoted context omitted.
Compared to the energy needed to move the car, everything else is pretty irrelevant. Power hungry features like Heating/AC only makes a few % difference to range.
From autonomy day hacker news comment: "Pegasus consumes about 500Watts, compared to under 100 Watts for Tesla's FSD computer. Elon in particular emphasized the performance per watt (as it's always possible to cram more chips to increase performance if you ignore cost and power consumption). The comparison made in the video: 500Watts for an hour consumes about 2-3 miles of range. In a city in slow traffic, going 12mp…
Good ol' velocity-cubed.
Increasing their compute per watt allows them to get more compute per watt, so they will pursue it lots, low speed energy savings are a way of making the range extension seem like a big deal when it isn't (maintaining highway speeds requires tens of kilowatts).
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#173The competition in this space is great but I can't help but wonder what would happen if instead all these companies pooled their resources and went after the goal collectively. There is so much duplication going on and the paths do not seem to me - as an outsider - to be all that divergent, which is usually a pre-condition for having a lot of independent efforts one of which will succeed. It's as if everybody wants t…
> The competition in this space is great but I can't help but wonder what would happen if instead all these companies pooled their resources and went after the goal collectively.
It would probably slow down. 9 women can't have a baby in 1 month. Besides that, the disagreements about approach, politics, or eventual competitive interests would probably bring things to a halt for a long time.
I don't think the solutions to this problem are resource-constrained. Many companies would happily find more resources in order to be first to market with this technology.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#174The competition in this space is great but I can't help but wonder what would happen if instead all these companies pooled their resources and went after the goal collectively. There is so much duplication going on and the paths do not seem to me - as an outsider - to be all that divergent, which is usually a pre-condition for having a lot of independent efforts one of which will succeed. It's as if everybody wants t…
> There is so much duplication going on
In the self-driving world, the duplication is necessary - different companies are taking different directions, and nobody really knows which will work out.
In the ML hardware world, the duplication is mostly unnecessary. People are developing their own inference hardware ASIC's because they're relatively simple (compared to designing a CPU from scratch, designing a TPU is pretty simple because there are so few operations, and no complex out-of-order execution), and you can't buy one off the shelf yet.
As soon as ML hardware becomes available to buy off the shelf without a massive price premium, everyone will switch to that.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#175Earlier quoted context omitted.
You can apply this line of reasoning on many markets, like the pharma or food industry which also have safety concerns. It strikes me as the kind initiatives EU attempts nowadays when realizing we are running behind on some tech and want to leverage the one possible advantage we have as a great centralizing power. Not too different from communist states, actually. I agree with the sentiment that redundancy seems wast…
I'm reminded of the Manhattan project and I don't think they would have succeeded in their goal if they had tried to run 10 of those at once. There just aren't that many really great scientists in a space this narrow.
Talk about twisting the argument. The Manhattan project was in competition with the Soviets and the Nazis, it was less a result of some unified front of all the smartest scientists in the world, and more of a result of "if we don't succeed first, someone much worse probably will".
Your logic of "if there were 10 of them simultaneously, it wouldn't have worked out" is flawed and self serving in that if you ignore all competition and just divide a single competitor into any number of smaller entities, of course at some point they'll be too small to be viable.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#176I'm still amazed that Teslas team isn't using a map... I know maps get outdated and are sometimes wrong, but having inaccurate knowledge of what's around the corner is far far more helpful than not having any clue whats around the corner.
The smart solution would be to consider a map a probabilistic thing, which neural networks are really good at handling.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#177I'm still amazed that Teslas team isn't using a map... I know maps get outdated and are sometimes wrong, but having inaccurate knowledge of what's around the corner is far far more helpful than not having any clue whats around the corner. The smart solution would be to consider a map a probabilistic thing, which neural networks are really good at handling.
I'm still amazed Tesla has decided not to use lidar and instead just stick with cheap cameras. Better sensors are there, they're available, they're cheap and they can probably "see" better than plain old cameras... it doesn't make too much sense not to use them IMHO. But then again, I am not coding NNs for Tesla...
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#178Earlier quoted context omitted.
Do you belittle everyone that gets second place in the Olympics because the winner is "way ahead"? Your comment just reeks of anger and hostility. It seems like you'd rather Tesla didn't try at all, and instead we all just give up and go back to the status quo.
Elon belittles lidar saying it is doomed and will never work yet Waymo and Cruise will probably be operating self driving taxi fleets in California next year. Tesla deserves getting dumped on for those comments because they are no where near self driving.
I live in San Francisco. Every time I see Cruise vehicles, the driver has his hands on the steering wheel.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#179I'm still amazed that Teslas team isn't using a map... I know maps get outdated and are sometimes wrong, but having inaccurate knowledge of what's around the corner is far far more helpful than not having any clue whats around the corner. The smart solution would be to consider a map a probabilistic thing, which neural networks are really good at handling.
I'm still amazed Tesla has decided not to use lidar and instead just stick with cheap cameras. Better sensors are there, they're available, they're cheap and they can probably "see" better than plain old cameras... it doesn't make too much sense not to use them IMHO. But then again, I am not coding NNs for Tesla...
I think they advertised self-driving as a future feature of the Model 3, so I think they are limited to whatever Model 3's currently have.
Re: Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
#180Earlier quoted context omitted.
>maybe not for everyone who can't afford/doesn't have a Tesla. Affordability is not as much of an issue as some make it out to be. Cost-wise it's like owning a Camry or an Accord, if you go for the lower end models. If you mean not everyone can afford a new car, then sure I agree with you. Edit: if you think I'm wrong about this, please explain or ask me to clarify anything?
As a small anecdote, my parents couldn't afford/didn't want to spent over $30k for a car. Surely we could've gotten a Tesla for $5k+ more, but given the relatively new infrastructure with electric charging stations (and the fact that none are available in the apartment I live in) my parents didn't find all the new cool features appealing and instead got a regular Toyota Sienna that has nothing fancy, just enough to t…
Thanks for the reply. Living in an apartment is not a big issue for me... we have two, live in an apartment with no charger.
That's interesting that you relate something you do in the AV industry to not ever getting a car... what's that about?
I do think that it's possible in the future the majority of people will never need to own a car.