7 cameras x 36fps x 5Mpx x 30s
48kHz audio
Nav maps and route for next few miles
100Hz kinematics (speed, IMU, odometry, etc)
Also, integration effort went down but it never disappeared. Meanwhile, opportunity cost skyrocketed when vision started working. Which layers would you carve resources away from to make room? How far back would you be willing to send the training + validation schedule to accommodate the change? If you saw your vision-only stack take off and blow past human performance on the march of 9s, would you land the plane just because red paint became available and you wanted to paint it red?
I wouldn't completely discount ego either, but IMO there's more ego in the "LIDAR is necessary" case than the "LIDAR isn't necessary" at this point. FWIW, I used to be an outspoken LIDAR-head before 2021 when monocular depth estimation became a solved problem. It was funny watching everyone around me convert in the opposite direction at around the same time, probably driven by politics. I get it, I hate Elon's politics too, I just try very hard to keep his shitty behavior from influencing my opinions on machine learning.
It's still rather weak and true monocular depth estimation really wasn't spectacularly anything in 2021. It's fundamentally ill posed and any priors you use to get around that will come to bite you in the long tail of things some driver will encounter on the road.
The way it got good is by using camera overlap in space and over time while in motion to figure out metric depth over the entire image. Which is, humorously enough, sensor fusion.
I do some tangent work from this field for applications in robotics, and I would consider (metric) depth estimation (and 3D reconstruction) starting to be solved only by 2025 thanks to a few select labs.
Car vision has some domain specificity (high similarity images from adjacent timestamps, relatively simpler priors, etc) that helps, indeed.
Source: not a computer vision engineer, but a childhood consumer of looney toons cartoons.
None of these technologies can ever be 100%, so we’re basically accepting a level of needless death.
Musk has even shrugged off FSD related deaths as, “progress”.
FSD: 2 deaths in 7 billion miles
Looks like FSD saves lives by a margin so fat it can probably survive most statistical games.
Your link agrees with me:
> 2 fatalities involving the use of FSD
No one wants these crappy cars anymore.
https://en.wikipedia.org/wiki/List_of_Tesla_Autopilot_crashe...
Your link agrees with me:
> two that NHTSA's Office of Defect Investigations determined as happening during the engagement of Full Self-Driving (FSD) after 2022.
"MacOS Tahoe has these cool features". "Yea but what about this wikipedia article on System 1. Look it has these issues."
That's how you come across
There are two deaths associated with FSD.
[*] Failing to solve the impossible situation FSD dropped them into, that is.
https://www.nhtsa.gov/laws-regulations/standing-general-orde...
If there's gamesmanship going on, I'd expect the antifan site linked below to have different numbers, but it agrees with the 2 deaths figure for FSD.
No customer would turn on FSD on an icy road, or on country lanes in the UK which are one lane but run in both directions; it's much harder to have a passenger fatality in stop-start traffic jams in downtown US cities.
Even if those numbers are genuine (2 vs 70) I wouldn't consider it apples-for-apples.
Public information campaigns and proper policing have a role to play in car safety, if that's the stated goal we don't necessarily need to sink billions into researching self driving