I drove 50 miles today and 90 miles yesterday to make up for your idleness.
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Tesla building generative AI models and starting Dojo production next month!
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I drove 50 miles today with one red hands of death and two disengagements and my car uploaded 17 GB. I'd say that the car includes video clips from all eight cameras.
How do you know how it uploaded 17GB of video/data? Is there something on the MCU to look at it?
Are you in a major city or out in the sticks? If you see Louis on the TMC podcasts he has a model S plaid and he barely goes anywhere (he works mostly at home)
My wifi router keeps track of data usage for each device on the network.
I live in the Dallas, TX area and I like FSDb to take me places. I let it drive in Urban, suburban, sticks and twigs. Some places I go likely see very, very few Teslas, let alone self driving ones!
VanFriscia
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Agreed, but I'm also convinced there are times when Tesla stops taking data. I've had drives that included multiple interventions and disengagements with audio logs on my part, but when I checked my router a couple days later, next to nothing had been uploaded. So, it seems that the Tesla mothership decides if/when it wants our videos. Most of the time, it does...but this has happened to me several times.
I'm sure that Tesla tasks the cars for what situations they need video and what situations they just want a report.
Here is a link to a possible advance over transformers. Liquid Neural Networks - LNN.
analyticsindiamag.com
Could something like this be stimulus for the full jump into AI by Elon?
Can LNNs Replace Transformers?
Daniela Rus, the director of CSAIL, recently demonstrated the use of LNNs in running a self-driving autonomous vehicle
analyticsindiamag.com
Could something like this be stimulus for the full jump into AI by Elon?
The LNN people are right that current approaches using brute force and scale won't get us closer to intelligence regardless of how much compute or data we toss at the problem. People in research understand this, and acknowledge there need to happen several break-throughs for AGI (and hence general autonomy) to happen.
Example:
"EZRA KLEIN: So when you think about the road from what we have now to these generally intelligent systems, do you think it’s simply more training data and more compute, like more processors, more stuff we feed into the training set? Or do you think that there are other innovations, other technologies that we’re going to need to figure out first? What’s between here and there?
DEMIS HASSABIS: I’m in the camp that both needed. I think that large multimodal models of the type we have now have a lot more improvement to go. So I think more data, more compute and better techniques will get result and a lot of gains and more interesting performance. But I do think there are probably one or two innovations, a handful of innovations, missing from the current systems that will deal with things that we talked about factuality, robustness, in the realm of planning and reasoning and memory that the current systems don’t have.
And that’s why they fall short, still, a lot of interesting things we would like them to do. So I think some new innovations are going to be needed there as well as pushing the existing techniques much further. So it’s clear to me, in terms of building an AGI system or general A.I. system, these large multimodal models are going to be a core component. So they’re definitely necessary, but I’m not sure they’ll be sufficient in and of themselves."
Transcript: Ezra Klein Interviews Demis Hassabis
The July 11, 2023, episode of “The Ezra Klein Show.”
These innovations may come over the next few years, next decade or never. Current Tesla cars will most likely never be robotaxis and there is no one coming to save Elon from his statements about L4 autonomy on budget sensors/hardware. The computer is not yet a brain so all the crutches are needed for a foreseeable future.
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