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The auto labeling work (which has been partially described/presented at Tesla AI day events) seems more like engineering than research, a grab bag of techniques that I would guess the whole team must have contributed to. For example, they auto label low resolution/indeterminate objects (image segments) by temporal continuity... Something that is a low-res blob in the distance becomes a hi-res and easy to identify object when you drive by it, so by tracking objects backwards across frames you can learn how to more confidently label the lo-res blob. Things like this are useful, but it's the sort of stuff that engineers and developers are coming up with every day.

by ricardobeat6 hours ago|

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Not back in 2016.

by HarHarVeryFunny5 hours ago|

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You don't think that tracking objects from frame to frame is obvious ?!

I can guarantee you this was built-in from day #1

I'm guessing you're not a developer if you don't then automatically think of end cases like "what if car # 1 isn't in the preceding frame" ... (then you look at some relevant test data and see it was there, unlabelled ...)

by frays7 hours ago|

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Karpathy is also badmephisto, a name you might have heard of if you're into cubing.

http://badmephisto.com/

by mjg28 hours ago|

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Tesla still hasn't achieved their 2016 self-drive goal by their self imposed deadline of 2017, even now a decade later. So, politely, is that accolade merited?

by trollbridge7 hours ago|

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The current vehicles sure seem to come close. I'm not entirely clear on how they've missed this goal, but the current models can do full self driving where I live, including parking.

by derangedHorse6 hours ago|

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How does Elon's arbitrary deadlines impact whether the accolade is "merited"? Incredible progress was made in a fairly short amount of time. His accolade isn't based on his employer's ability to predict delivery dates, they're based on the quality of the systems that are actively deployed today.

by momojo11 hours ago|

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Add microgpt to that list

by 10xDev11 hours ago|

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It wasn't LSTMs, it was RNNs.

by davidatbu11 hours ago|

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Thanks for correcting the title I misremembered. Fwiw, the article did culminate with LSTMs: https://karpathy.github.io/2015/05/21/rnn-effectiveness/

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EDIT: It looks like you deleted the part of your post I quoted below. So feel free to ignore my question about it, I guess.

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Not sure what you mean by

> Shows how much you know

Do you mean that the fact that I misremembered a word on the title suggests that I know very little about Karpathy's contributions to the field of neural networks?

by kingkongjaffa11 hours ago|

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Thank you!

I was more looking for signal that him + Anthropic might yield something beyond a step-change from Opus 4.7 (disappointing so far). We have not gotten to use Mythos yet, I wonder if that will become Opus 5 or something.