111–120 of 483 posts
Earlier quoted context omitted.
Lack of focus is a major problem for companies and we all know that tech debt leads to increased bug counts. Team focus on vision which is by far the highest accuracy and bandwidth sensor allows for a faster rate of safety innovation given a constant team size.
Tesla engineers are currently doing post-commit review of Twitter source code. Focus is the last thing I would credit them with.
I thought it was telling that Andrej immediately "reframed" the question because Lex asked the "wrong question". This is a classic evasion technique one learns from experience and/or media training. Lex's comment immediately after was a clever and gentle dig at Andrej's response. It seemed like all the "full cost" negatives Andrej mentioned were related to Tesla's ability to execute, and not what would actually produ…
It was an ominous answer. We really should be focusing on what is the best solution and trying to solve price issues through existing techniques e.g. economies of scale, competition, miniaturisation. Instead they are trying to build whatever solution they can that fits in a pre-defined cost window. Except this isn't a new phone or sneakers we are trying to take to market it's something that will directly impact peopl…
Earlier quoted context omitted.
That was hilarious. Basically (unless this needs a reframing/realignment/repositioning/reorienting): Q: "are less sensors less safe/effective?" A: "well more sensors are costly to the organization and add more tech debt so safety is orthogonal and not worth answering".
Lack of focus is a major problem for companies and we all know that tech debt leads to increased bug counts. Team focus on vision which is by far the highest accuracy and bandwidth sensor allows for a faster rate of safety innovation given a constant team size.
The bottom line seems to be that the part shortages would have slowed production and cost cutting. The rest of the story seems like a fable to me. It was pretty clear Tesla removed the radar because it couldn't get enough radars.
The interview didn't really impress me. I'm sure Andrej is bound by NDA and not wanting to sour his relationship with Tesla/Elon but a lot of the answers were weak. (On Tesla and some of the other topics, like AGI).
I thought it was telling that Andrej immediately "reframed" the question because Lex asked the "wrong question". This is a classic evasion technique one learns from experience and/or media training. Lex's comment immediately after was a clever and gentle dig at Andrej's response. It seemed like all the "full cost" negatives Andrej mentioned were related to Tesla's ability to execute, and not what would actually produ…
1) He's not touching on the software cost of integrating different sensor data into the same trained machine learning model; it is likely far simpler to just stick to stereoscopic vision data (the same thing the human genome decided!)
2) That said, it seems at least theoretically advantageous to have a sensory system that exceeds that which humans are limited to; things like LIDAR can work in complete darkness and potentially spot, for example, pedestrians crossing a dark road without any reflective clothing on, where a vision-based system would fail (perhaps add infrared sensation?)
Anyway, doesn't AEB (automatic emergency braking) have to be installed in every car, by law, in the US, around now? And wouldn't that be less reliable if done via vision?
Earlier quoted context omitted.
I think one should distinguish between 'all necessary information is already in the pixel-space' vs 'we already know how to extract all the information needed from pixel-space' The fact that (most) humans manage to drive around safely and successfully in current roads proves that the information needed exists in the pixel-space (not just current image, but say current + history). We don't yet have stacks that can suc…
bleh. auto accidents are the #1 preventable cause of death for kids: https://en.wikipedia.org/wiki/Preventable_causes_of_death#Am...
https://capitolfax.com/2021/01/26/aaa-wants-us-to-stop-calli...
I didn't find his answers particularly convincing. His answer focused on costs mainly, and how "the best part is no part". We have already seen multiple accidents caused by camera's limitations [1] which would not have happened if Tesla used Lidars. Cameras have poor dynamic range and can be easily blinded by bright surfaces. While it is true that humans do fine with only eyes, our eyes are significantly better than…
Earlier quoted context omitted.
The dynamic range is the reason Tesla know counts photons rather than use traditional camera processing. They basically remove the concept of exposure entirely and simply pass the sensor photon counts to the neural net. This approach not only simpler as it removes photo processing/encoding but the result is that the NN can operate with a very high dynamic range similar to the human eye and in many cases can be sensit…
But it doesn't appear to be helping. Here's an example accident where depth data from Lidar would have helped: "Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky." https://www.nytimes.com/2021/12/06/technology/tesla-autopilo...
Earlier quoted context omitted.
> It is not sufficient if, in aggregate, self-driving cars have fewer accidents It would be sufficient if it would be the case. With actual proof. Reality is that in limited abstract situations, self driving card maybe have some advantages. But, that is all that we can claim. And when self driving fails, somehow human is always the cause.
I disagree, but mainly because of the way humans perceive risk. From a public standpoint I don’t think it’s sufficient because there’s inherent trust lacking in an automated system. With ape-driven systems we have a certain amount of trust because we can more accurately intuit what the other ape is reasonably thinking. This is not the case with autonomous driving which leads to a wider amount of uncertainty. Not unli…
Earlier quoted context omitted.
You're right to note the advantages of lidar and (narrow range of) contrast problem for cameras (they arent eyes.) This is why the Uber human driver shouldn't have trusted the machine at night, in particular. But you still have to address his system argument, which was that adding geegaws that added little would actually increase overall risks along the supply chain (plus maintenance) while distracting the team and a…
They cannot actually believe that.
I certainly was skeptical until alphago and alphafold happened.
What is it that makes Lidar so expensive? Is it something intrinsic to the technology that prevents costs from coming down?