Humans don't use radar or ultrasound sense to drive. If we want cars that drive like humans drive they should use the same senses. For example, in the northern parts of the USA there is snow cover for much of the year and lanes are emergent from flocking without any absolute reference to the actual location of the lanes. The reasons everyone choses the same places to drive are that they see the same environment with the same senses. Even if autonomous driving with radar and ultrasound was made to work if it picks the correct lane position and all the humans pick the wrong new lane position then the car is wrong, not the humans.
Why Tesla removed radar and ultrasonic sensors [video]
191–200 of 483 posts
Re: Why Tesla removed radar and ultrasonic sensors [video]
#192Earlier 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 don't think it was your intent, but your statement makes it seems like all Tesla engineers are looking at Twitter code. I bet this number is closer to 4.
Tesla has ca. 1000 software engineers working in various capacities. The ca. 300 that work on car firmware and autonomous driving are probably not participating in the Twitter drama.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#193Earlier 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.
Uhh highest accuracy and bandwidth for what? You can have a camera that can see piece of steak at 100K resolution at 1000 FPS but doesn’t mean you can use a camera to replace a thermometer. Blows my mind how people eat up that cameras can replace every sensor in existence without even entertaining basic physics. ML is not omnipotent.
For the specific task of (for example) cooking a steak it’s not hard to envision a computer vision algorithm coupled with a model with a some basic knowledge of the system (ambient temperature, oven/stove temperature, time cooking, etc.) doing an excellent job.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#194I 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…
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…
Does it have electrolytes as well?
Nice tech and single photons and whatnot but it still runs into things that a radar with some really simple code wouldn't. ¯\_(ツ)_/¯
Re: Why Tesla removed radar and ultrasonic sensors [video]
#195Earlier 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".
The video has a more reasonable answer. The sensors are unreliable and expensive in terms of R&D. Having marginal parts which takes money from a finite R&D budget can easily result in a worse product. “They contribute noise and entropy into everything.” … “you’re investing fully into that [vision] and you can make that extremely good. You only have a finite amount of spend of focus across different facets of the syst…
Didn't they used to talk about how the Tesla radar could actually see the reflections of the car ahead of the one just in front of you? i.e. the radar reflection bouncing underneath the car just in front of you?
This is what doesn't add up to me. Either a lot of that previous wonder-talk was actually a lie, or there's something else going on here.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#196Andrej's argument about more sensors adding entropy strikes me as disingenuous considering that in the next question he then says that Tesla's biggest advantage over everyone else is "the fleet", which clearly introduces orders of magnitude more entropy into the system than anything else. Can you imagine the infrastructure required to gather video from "the fleet" anytime a car sees something unexpected? How about di…
You don't understand the term entropy.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#197I 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…
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…
Counting photons won't keep a camera from being "jammed." Unless you are using a physically perfect polarizing filter, such that each pixel on the sensor only receives photons from the exact angular window, traced back through the lenses, you have a camera that can ultimately be "jammed."
The human eye isn't so great on those terms. But humans can raise their hand to block the sun if it's straight at our eyes.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#198I 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…
I feel the other reason is that Tesla has not figured out a way to put Radar into their ML pipeline. If you take the Range-Doppler Map from the radar as the 'pixel' map, that data is inherently very dependent on the scenario and the radar sensor intrinsic parameters. This variability in what the radar sees in the RD space is what makes this a challenge for ML/AI pipelines. If Tesla were to 'fuse' information from the…
Its interesting, that kind of object level fusion is a fairly different problem to training visual perception, following some of the less in fashion robotics techniques. I wonder if its a case of the Tesla engineers focusing on the fad technologies (or just their strengths) more than its a hardware cost thing.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#199Earlier quoted context omitted.
> While it is true that humans do fine with only eyes We do not. Humans are terrible at driving. Traffic accidents are one of the leading causes of death in the developed world. Billions of dollars of property damage occur every year because humans are not up to the task. A self driving system that is as safe as an average human driver would be an absolute failure.
> Traffic accidents are one of the leading causes of death in the developed world. Not even close, really. A bit under 1%. You are more likely to die from an overdose, or suicide. And much, much, much more likely to die from cancer or heart disease. And that is without getting into the trade-offs. Cars at least have a significant utility value, which is not true of suicide, opiate addiction, cancer, or heart disease.…
I was not precise enough in the wording. Leading cause of accidental death. Obviously it is not beating out old age or heart disease. Doesn't change the fact that a self driving system with the record of a typical human would be considered unacceptable.
Re: Why Tesla removed radar and ultrasonic sensors [video]
#200Earlier quoted context omitted.
Two thoughts: 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 d…
> likely far simpler to just stick to stereoscopic vision data (the same thing the human genome decided!) Yeah and till we had reliable and powerful artificial lighting, it was highly unsafe to journey in low visibility/ darkness. We used to finish journeys when darkness fell. Animals that do require precise movement in low visibility (bats, dolphins) conditions often evolved ultrasound solutions. So should we licens…
Excellent points, I didn't think about the fact that even evolution couldn't come up with a vision system that works as well in the dark as it works in the daytime.