41–50 of 165 posts
IMHO, this is not too bad! But obviously, coming from the software product industry, everyone knows that building features isn't the same as operating in practice and optimizing based on the use case, which takes a ton of time. Waymo has a huge head start, and it is evident that the "fully autonomous" robotaxi date is far behind what Elon is saying publicly. They will do it, but it is not as close as the hype suggest…
When you have a CEO like Elon who swears up and down that you only need cameras for autonomous driving vehicles, and skimping out on crucial extras like Li-DAR, can anyone be surprised by this result? Tesla also likes to take the motto of "move fast and break things" to a fault.
The more I've looked into the topic the less I think the removal of lidar was a cost issue. I think there are a lot of benefits to simplifying your sensor tech stack, and while I won't pretend to know the best solution removing things like lidar and ultrasonic sensors seem to have been a decision about improving performance. By doubling down on cameras your technical team can remain focused on certain sensor technolo…
Earlier quoted context omitted.
The more I've looked into the topic the less I think the removal of lidar was a cost issue. I think there are a lot of benefits to simplifying your sensor tech stack, and while I won't pretend to know the best solution removing things like lidar and ultrasonic sensors seem to have been a decision about improving performance. By doubling down on cameras your technical team can remain focused on certain sensor technolo…
Having multiple sources of data is a benefit, not a problem. Entire signal processing and engineering domains exist to take advantage of this. Even the humble Kalyan filter lets you combine multiple noisy sources to get a more accurate result than would be possible if using any one source.
I will also add in my personal experience, while some filters work best together (like imu/gnss), we usually either used lidar or camera, not both. Part of the reason was combining them started requiring a lot more overhead and cross-sensor experts, and it took away from the actual problems we were trying to solve. While I suppose one could argue this is a cost issue (just hire more engineers!) I do think there's value in simplifying your tech stack whenever possible. The fewer independent parts you have the faster you can move and the more people can become an expert on one thing
Again Waymo's lead suggests this logic might be wrong but I think there is a solid engineering defense for moving towards just computer vision. Cameras are by far the best sensor, and there are tangible benefits other than just cost.
When you have a CEO like Elon who swears up and down that you only need cameras for autonomous driving vehicles, and skimping out on crucial extras like Li-DAR, can anyone be surprised by this result? Tesla also likes to take the motto of "move fast and break things" to a fault.
The more I've looked into the topic the less I think the removal of lidar was a cost issue. I think there are a lot of benefits to simplifying your sensor tech stack, and while I won't pretend to know the best solution removing things like lidar and ultrasonic sensors seem to have been a decision about improving performance. By doubling down on cameras your technical team can remain focused on certain sensor technolo…
Price is a factor. I’ve been using the free self driving promo month on my model Y (hardware version 4), and it’s pretty nice 99% of the time.
I wouldn’t pay for it, but I can see a person with more limited faculties, perhaps due to age, finding it worthwhile. And it is available now in a $40k vehicle.
It’s not full self driving, and Waymo is obviously technologically better, but I don’t think anyone is beating Tesla’s utility to price ratio right now.
FTA: "For comparison, the average human driver in the US crashes about once every 500,000 miles." Does anyone know what the cite for this might be? I'm coming up empty. To my knowledge, no one (except maybe insurance companies) tallies numbers for fender bender style accidents. This seems like a weirdly high number to me, it's very rare to find any vehicle that reaches 100k miles without at least one bump or two requ…
This is the sort of thing that occurs when the interests of the public become subordinate to the interests of a lawless aristocracy. Financial, social and public safety considerations are costs that can be transferred to the public to preserve the wealth of a few individuals.
Was there a time when the interests of the public weren't subordinate?
Earlier quoted context omitted.
Having multiple sources of data is a benefit, not a problem. Entire signal processing and engineering domains exist to take advantage of this. Even the humble Kalyan filter lets you combine multiple noisy sources to get a more accurate result than would be possible if using any one source.
What I've heard out of Elon and engineers on the team is that some of these variations of sensors create ambiguity, especially around faults. So if you have a camera and a radar sensor and they're providing conflicting information, it's much harder to tell which is correct compared to just having redundant camera sensors. I will also add in my personal experience, while some filters work best together (like imu/gnss)…
Who will save humanity from Elon Musk?
FTA: "For comparison, the average human driver in the US crashes about once every 500,000 miles." Does anyone know what the cite for this might be? I'm coming up empty. To my knowledge, no one (except maybe insurance companies) tallies numbers for fender bender style accidents. This seems like a weirdly high number to me, it's very rare to find any vehicle that reaches 100k miles without at least one bump or two requ…
Earlier quoted context omitted.
Having multiple sources of data is a benefit, not a problem. Entire signal processing and engineering domains exist to take advantage of this. Even the humble Kalyan filter lets you combine multiple noisy sources to get a more accurate result than would be possible if using any one source.
What I've heard out of Elon and engineers on the team is that some of these variations of sensors create ambiguity, especially around faults. So if you have a camera and a radar sensor and they're providing conflicting information, it's much harder to tell which is correct compared to just having redundant camera sensors. I will also add in my personal experience, while some filters work best together (like imu/gnss)…
> solid engineering defense for moving towards just computer vision
COUNTERPOINT: WAYMO