Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

Truly. I don't understand why Tesla fans think camera/lidar fusion is unsolvable but camera/camera fusion is a non-issue.


Because they bought a Tesla with only cameras on it.

Admitting this would be admitting their Tesla will never be self driving.


I bought mine with cameras and a radar, which they then deprecated and left an unused. Even though autopilot was better when it had radar. Then I realized that this thing would never be self-driving and that its CEO was throwing nazi salutes. Cut my losses and got rid of it. Gotta admit defeat sometimes.


Add a tow hitch to Waymos and any car can be autonomous!


Unsure if you’re trolling, but you haven’t listened to what Tesla are actually saying.

Having more sensors is complicating the matter, but yes sure you can do that if you want to. But just using vision simplifies training a huge amount. The more you think about it, the stronger this argument is. Synthesising data is a lot easier if you’re dealing with one fairly homogenous input.

But the real point is that cameras are cheap, so you can stick them in many many vehicles and gather vast amounts of data for training. This is why Waymo will lose - either to Tesla or more likely a Chinese car manufacturer.

I do not like Elon because I do not think nazi salutes or racism are cool, but I do think Tesla are correct here. Waymo wins for a while, then it dies.


Cameras are only "cheap" because of mobile phone camera development, radar/lidar is going through the same process with car and mobile robotics.

So the "we can train cheaply because of lots of cameras" falls down when, for example, BYD has all of its cars with lidar for ADAS but can collect the data for training as well as the vision from cameras and whatever other sensors like tyre pressures and suspension readings and all the other sensors that are on a modern car.

The argument that we can make the cars cheaper in the future by not collecting the additional data now has been proven wrong by the CN and KR manufacturers.

That's also independent of the whole EV side of things.


Chinese are going with lidars as well.

It's just that the cost of lidars are falling like crazy, with new automotive lidars using phased-array laser optics instead of what waymo started with (mechanically scanned lidars)


Tesla doesn't even use good cameras. Compare to https://waymo.com/blog/2026/02/ro-on-6th-gen-waymo-driver#:~...


That assumes that hardware was/is/will be more expensive than.. simply scaling up data collection and training?

Which seems like a very bad assumption, I'm not even sure it was ever true and is getting less and less true.


The data is key. You need a lot of homogenous data collected at vast scale over places and time, and you need to be able to synthesise data accurately.

Waymo gets limited data from very limited locations, and will have a harder time synthesising data than others.


Do Tesla fans think that? I've seen plenty of Tesla fans say that lidar is unnecessary (which I tend to agree with), but never that lidar is actively detrimental as Musk says there.


I mean, humans have only their eyes. And most of them intentionally distract themselves while driving by listening to music, podcasts, playing with their phones, or eating.


I get your point about camera vs lidar. Humans do have other senses in play while driving though. We have touch/vibration (feeling the road surface texture), hearing, proprioception / acceleration sense, etc. These are all involved for me when I drive a car.


To be fair, humans are fairly poor drivers and generally can't be trusted to drive millions of miles safely.


Humans are not good drivers when it comes to long, monotonous rides (because we get tired)

But (some) humans have the ability to handle difficult situations, and no autonomous system gets anywhere close to that. So this is more of a "robots handle the easy 80% better, but fail hard on the rest of the 20%". Humans have a possibly worse 80% performance, but shine in the 20%.


Actually humans are fairly good drivers. The average US driver goes almost 2 million miles between causing injury collisions. Take the drunks and drug users out and the numbers for humans look even better.


Incorrect. Humans are fairly good engineers, so cars are pretty safe nowadays.

If you include minor fender-benders and unreported incidents, estimates drop to around 100,000–200,000 miles between any collision event.

This is cataclysmically bad for a designed system, which is why targets are super-human, not human.


I don't think averages work that way




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: