But the fact is that the current tech is massively overrated and often ascribed almost magical capabilities.
Wouldn't some of the "lower tech" collision avoidance technology (the type you can already get on production cars) have noticed the bicyclist at all, and at least have started to brake?
Wouldn't some of the "lower tech" collision avoidance technology (the type you can already get on production cars) have noticed the bicyclist at all, and at least have started to brake?
Next time read with comprehension, mate. He explicitly talks about the AI algorithms doing the "thinking" and that LIDAR only feeds the data in!
Most of the text is about how the system needs to balance data from multiple sensors.
I would say he has more clue about what he is talking about than most, given that he is working directly in the field. What is your background to judge the article as "nonsense"?
Wouldn't some of the "lower tech" collision avoidance technology (the type you can already get on production cars) have noticed the bicyclist at all, and at least have started to brake?
Not sure whether this has been posted already, but it is a pretty good analysis of how these technologies work and what can realistically be expected (e.g. LIDAR may not have saved the day even if it was installed and was working):
https://medium.com/@rebane/could-ai-have-saved-the-cyclist-had-i-programmed-the-uber-car-6e899067fefe
Dont know what background author has, but I stopped reading after few paragraphs of nonsense.
Lidar doesnt "think" and doesnt do classification, it just provides additional data points to classification algorithm, plus this dude keeps using dashcap footage as a proof :/
Next time read with comprehension, mate. He explicitly talks about the AI algorithms doing the "thinking" and that LIDAR only feeds the data in! Most of the text is about how the system needs to balance data from multiple sensors.
And re his background - if I am not mistaken, it is this dude:
https://www.researchgate.net/profile/Martin_Rebane
I would say he has more clue about what he is talking about than most, given that he is working directly in the field. What is your background to judge the article as "nonsense"?
But the fact is that the current tech is massively overrated and often ascribed almost magical capabilities.
Wouldn't some of the "lower tech" collision avoidance technology (the type you can already get on production cars) have noticed the bicyclist at all, and at least have started to brake?
The article reads like a series of excuses, rather than an analysis. The car wasn't slowing, even as it hit the bicycle. It looks like the car's awareness of its situation was so weak that it would have continued on its journey with the cyclist and cycle stuck to the front grill, as if nothing had happened. It seems only the "driver" caused the car to react. Situational awareness issues are one of the major reasons people fail driving tests, and there are sounds reasons for that. A vehicle with such poor situational awareness doesn't belong on public roads.
Next time read with comprehension, mate. He explicitly talks about the AI algorithms doing the "thinking" and that LIDAR only feeds the data in!
does he now? whats this then: "now one of them thinks it’s a dog" as if sensor did image classification, or as if someone used object classification on lidar output alone.
Modern CA systems are operating with memory, they have maps and registers of what they have seen. They keep track of recorded objects from image to image. If two seconds ago both sensors (or more precisely, the algorithms that interprets the sensor readings) agreed the object to be a lorry and now one of them thinks it’s a dog,
Most of the text is about how the system needs to balance data from multiple sensors.
First paragraphs I read seemed to be from distant past, not current state of the art AI, but 30 year old expert systems level of thinking. I guess in a sense author is right - AI couldnt save this pedestrian if HE was the one who programmed it.
1 he is not working in the field, he is a researcher at an university
2 its not my sole opinion, many people on hackernews had same sentiment.
3 Btw did Uber recruit in Talin?
btw "Intel Corp.’s Mobileye, which makes chips and sensors used in collision-avoidance systems and is a supplier to Aptiv, said Monday that it tested its own software after the crash by playing a video of the Uber incident on a television monitor. Mobileye said it was able to detect Herzberg one second before impact in its internal tests, despite the poor second-hand quality of the video relative to a direct connection to cameras equipped to the car."
Even Mobileye, famous Tesla decapitation platform, would be able to at least initiate braking with shitty chinese dashcam as a data source.
He has a commercial interest that a field which doesn't really deliver all that much commercial value stays as hot as it is.
The market only needs so many PhD's to datamine for advertising and security services.
I don't see why an Estonian machine learning PhD student would want to "make excuses" for the poor performance of the Uber's car they are not involved with
That's human nature, and you'll see it when flaws are pointed out with any technology being developed. You generally get two types of response:
- "Their system is flawed, but we have a robust fix for that flaw in our version."
- Replies like the one from the PhD student, because an attack on one of us is an attack on all of us.
Wouldn't some of the "lower tech" collision avoidance technology (the type you can already get on production cars) have noticed the bicyclist at all, and at least have started to brake?
Selective quoting without understanding, yay.
Here is the full quote:QuoteModern CA systems are operating with memory, they have maps and registers of what they have seen. They keep track of recorded objects from image to image. If two seconds ago both sensors (or more precisely, the algorithms that interprets the sensor readings) agreed the object to be a lorry and now one of them thinks it’s a dog,(emphasis mine).
So working in machine learning research and directly with the tech involved (e.g. LIDAR mapping) is not in the field. Where do you think companies like Waymo or Uber got their machine learning algorithms from?
2 its not my sole opinion, many people on hackernews had same sentiment.
3 Btw did Uber recruit in Talin?
How is that relevant?
Yes and Aptiv has also explicitly said that Uber has disabled their stuff on the Volvo as to not interfere with their own systems (Aptiv doesn't want to be tainted by the scandal). The poor performance of the Uber's car is not in dispute, get off your high horse.
So someone with "a commercial interest in the field" is going to spend53 years** in Tallinn in Estonia, slaving away for next to nothing (and likely accruing debt in the process) doing a PhD
Boots on the ground from Brian Kaufman
I live right by where the Uber self-driving accident
occurred, and the Uber released video showing that apparently no driver could
have avoided hitting that woman in a million years is totally misleading.
See my YouTube video below where I drive the
same path as the Uber autonomous car was on. The attached photos were
taken from the point of the accident.
https://www.theverge.com/2018/3/27/17168606/nvidia-suspends-self-driving-test-uber
And re his background - if I am not mistaken, it is this dude:
https://www.researchgate.net/profile/Martin_Rebane
I would say he has more clue about what he is talking about than most, given that he is working directly in the field. What is your background to judge the article as "nonsense"?
https://www.theverge.com/2018/3/27/17168606/nvidia-suspends-self-driving-test-uber
From this link is the attached picture of the "Brain" used by AVs. Does anyone know anything about the connectors?
thanks
If it was hacked that would be relatively easy to tell afterwards. Doubt it's the case here but if autonomous cars are networked they will likely be susceptible to hacking, which is a big problem imho. You can build unhackable systems in theory but it seems very hard to do in practice.
Everything is build down to a price. I don't necessarily see the problem with using LIDAR + stereo.
Stereo cameras in IR should be able to get a good depth picture near the car.