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The Telsa autonomy investor day (which applied to the cars not the people) spent most of their time explaining their NN chip, ghost riding to correct prediction

The Telsa autonomy investor day (which applied to the cars not the people) spent most of their time explaining their NN chip, ghost riding to correct predictions etc. Definitely gave the impression that the network was doing a lot of the decision making.

xmprt 7y ago
Gives me the impression that Tesla made a small innovation which they're trying to overblow to investors since buzzwords like machine learning are more interesting than actual progress. I'm not saying Tesla isn't making massive progress but that anything they say to the press should be taken with a grain of salt.
- drcross 7y ago
  Why speculate? Watch the I vestor day video and see for yourself why it's not just hot air.
nostrademons 7y ago
Of course, because NNs are hot with investors now and Tesla wants their money. Companies frequently misrepresent how their technology works to the public. Typically they'll do some small portion with the hot technology for buzzword compliance, and then build the rest of it with an actually sensible, boring, and tailored-to-the-problem technology stack, oftentimes with a lot of proprietary legwork done by their data scientists and engineers. This way they get the best of all worlds: investment dollars from gullible investors, PR from journalists that want to hop on the next big thing, a product that actually works, and misdirection so competitors hop on approaches that aren't going to work anyway.
- TaylorAlexander 7y ago
  That doesn’t seem to be the case with Tesla. Their custom chip is almost entirely focused on being a neural network accelerator and they seem to be hugely reliant on neural networks. Notably Waymo is said to be less reliant on neural networks but Tesla definitely depends on them.
  - ehsankia 7y ago
    That doesn't really prove much. The classification is the heavy part that needs acceleration. The algorithmic side would probably not need an accelerator, as it's basically a decision tree. My original point was that the decision tree should hopefully degrade gracefully as the prediction quality goes down, and not have any brand that leads to an insane behavior. Now obviously, the better your predictions, the better the driving will be, which is why you'd want NN accelerators.

xmprt 7y ago

Gives me the impression that Tesla made a small innovation which they're trying to overblow to investors since buzzwords like machine learning are more interesting than actual progress. I'm not saying Tesla isn't making massive progress but that anything they say to the press should be taken with a grain of salt.

drcross 7y ago
Why speculate? Watch the I vestor day video and see for yourself why it's not just hot air.

nostrademons 7y ago

Of course, because NNs are hot with investors now and Tesla wants their money. Companies frequently misrepresent how their technology works to the public. Typically they'll do some small portion with the hot technology for buzzword compliance, and then build the rest of it with an actually sensible, boring, and tailored-to-the-problem technology stack, oftentimes with a lot of proprietary legwork done by their data scientists and engineers. This way they get the best of all worlds: investment dollars from gullible investors, PR from journalists that want to hop on the next big thing, a product that actually works, and misdirection so competitors hop on approaches that aren't going to work anyway.

TaylorAlexander 7y ago
That doesn’t seem to be the case with Tesla. Their custom chip is almost entirely focused on being a neural network accelerator and they seem to be hugely reliant on neural networks. Notably Waymo is said to be less reliant on neural networks but Tesla definitely depends on them.
- ehsankia 7y ago
  That doesn't really prove much. The classification is the heavy part that needs acceleration. The algorithmic side would probably not need an accelerator, as it's basically a decision tree. My original point was that the decision tree should hopefully degrade gracefully as the prediction quality goes down, and not have any brand that leads to an insane behavior. Now obviously, the better your predictions, the better the driving will be, which is why you'd want NN accelerators.