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I was thinking the same way a year ago and telling my fanboy tesla friend how stupid it was removing lidars etc., but being open minded and always looking to be

I was thinking the same way a year ago and telling my fanboy tesla friend how stupid it was removing lidars etc., but being open minded and always looking to be challenged, I started researching what they are doing and how they are doing it, watch their AI day video (its old in AI terms but gives a good insight), and I eventually got what they’ve meant when saying lidar introduces noise compared to what they are doing right now. TLDR is they convert photons into a multistereoscopic camera and reconstructing the brain’s behavior towards objects and motion…the way they transform the image data into high quality 3d point clouds is really mindblowing, people outside of the 3d ecosystem cannot fully appreciate that, and its kind of sad. The camera performance is like the newer starlight sensors in terms of seeing in the dark, and they seem to process from raw data. Essentially, once they crack all the quirks, I am now a firm beleiver that it will better than the average joe with limited angulars vision+rotating head vs. surround stereoscopic vision. Not saying I 100% agree with launching a beta program in the wild like this, but to their defense, given the current government driving paperwork and legislation to insane levels of unproductivity, innovators and challengers kinda have to play it out like that if they want to disrupt sectors (in the end) for the better. Not saying the end justifies the means, but I can understand the logic.

boboche 4y ago
Wow lots of moderation hatred when writing a simple tsla comment ;)
PragmaticPulp 4y ago
> TLDR is they convert photons into a multistereoscopic camera and reconstructing the brain’s behavior towards objects and motion… I think maybe someone dazzled you with some excessive jargon. Extracting point clouds from stereoscopic cameras isn't a Tesla invention, even though they've invested a lot into trying to make theirs work. This is some computer vision 101 stuff, but nobody calls it "converting photons". > Essentially, once they crack all the quirks, I am now a firm beleiver Well obviously if they solve all of the problems then we'd all be believers too.
- moogly 4y ago
  It wasn't even new when Microsoft Kinect did it... let's see... 12 years ago.
  - boboche 4y ago
    Moogly from amiga? Kinect point cloud was a total mess, never worked with more than a few cameras and had a LOT of restriction and artifacts, what I meant by impressive, imagine a moving 6 camera kinect with clean signals, that doesn't fail on specific texture or reflection because it track in 4D + AI. Probably the people downrating are the same thinking the Tesla FSD AI is a kinect contraption.
yababa_y 4y ago
> TLDR is they convert photons into a multistereoscopic camera and reconstructing the brain’s behavior towards objects and motion… I just spent the time watching the vision segment of that video, and while the presenter uses the brain as a simile to motivate neural network architecture, it actually is not modeled at all on how primate visual cortex works. Seems some tweeps also got caught up in this hype. I think those few slides were really just to show the complexity of the problem. For parties interested in actual models of biological vision, https://serre-lab.clps.brown.edu/wp-content/uploads/2014/10/Serre-encyclopedia_revised.pdf https://serre-lab.clps.brown.edu/wp-content/uploads/2014/10/... is a good resource.
- boboche 4y ago
  Like I said, that was a while ago, If you watch all the follow-up interviews, including the recent TED talk with prior interview with the host, he does mention the process of thinking having solved it, exponential gains, then hitting a ceiling and having to change the approach. The biggest problem I see is not if they will solve it (that's just a question of time), its how they communicate their optimism and "almost there" but always pushing further. That's more than annoying (at best) and contributing extensively to the negativity. I guess they are trying to get people excited, attract talent, etc.
giantrobot 4y ago
Humans don't just use vision when driving a car. Our eyes also aren't fixed in our heads. They can gimbal independently of our heads. Our torsos also give our heads more degrees of freedom than just our necks. Human senses are actually fairly good. The main issue with vision-only FSD is that visual artifacts don't convey high degrees of certainty about the solid nature of things. If the AI doesn't recognize an object as being an object it can't add it to the list of things to worry about. If it's augmented with LIDAR and radar it doesn't need to recognize an airplane to know there's a solid object in its path. It's dumb edge cases that cause problems. Vision-only FSD leaves a lot of edge cases on the table with the hope that AI magic will save the day.

boboche 4y ago

Wow lots of moderation hatred when writing a simple tsla comment ;)

PragmaticPulp 4y ago

> TLDR is they convert photons into a multistereoscopic camera and reconstructing the brain’s behavior towards objects and motion… I think maybe someone dazzled you with some excessive jargon. Extracting point clouds from stereoscopic cameras isn't a Tesla invention, even though they've invested a lot into trying to make theirs work. This is some computer vision 101 stuff, but nobody calls it "converting photons". > Essentially, once they crack all the quirks, I am now a firm beleiver Well obviously if they solve all of the problems then we'd all be believers too.

moogly 4y ago
It wasn't even new when Microsoft Kinect did it... let's see... 12 years ago.
- boboche 4y ago
  Moogly from amiga? Kinect point cloud was a total mess, never worked with more than a few cameras and had a LOT of restriction and artifacts, what I meant by impressive, imagine a moving 6 camera kinect with clean signals, that doesn't fail on specific texture or reflection because it track in 4D + AI. Probably the people downrating are the same thinking the Tesla FSD AI is a kinect contraption.

yababa_y 4y ago

> TLDR is they convert photons into a multistereoscopic camera and reconstructing the brain’s behavior towards objects and motion… I just spent the time watching the vision segment of that video, and while the presenter uses the brain as a simile to motivate neural network architecture, it actually is not modeled at all on how primate visual cortex works. Seems some tweeps also got caught up in this hype. I think those few slides were really just to show the complexity of the problem. For parties interested in actual models of biological vision, https://serre-lab.clps.brown.edu/wp-content/uploads/2014/10/Serre-encyclopedia_revised.pdf https://serre-lab.clps.brown.edu/wp-content/uploads/2014/10/... is a good resource.

boboche 4y ago
Like I said, that was a while ago, If you watch all the follow-up interviews, including the recent TED talk with prior interview with the host, he does mention the process of thinking having solved it, exponential gains, then hitting a ceiling and having to change the approach. The biggest problem I see is not if they will solve it (that's just a question of time), its how they communicate their optimism and "almost there" but always pushing further. That's more than annoying (at best) and contributing extensively to the negativity. I guess they are trying to get people excited, attract talent, etc.

giantrobot 4y ago

Humans don't just use vision when driving a car. Our eyes also aren't fixed in our heads. They can gimbal independently of our heads. Our torsos also give our heads more degrees of freedom than just our necks. Human senses are actually fairly good. The main issue with vision-only FSD is that visual artifacts don't convey high degrees of certainty about the solid nature of things. If the AI doesn't recognize an object as being an object it can't add it to the list of things to worry about. If it's augmented with LIDAR and radar it doesn't need to recognize an airplane to know there's a solid object in its path. It's dumb edge cases that cause problems. Vision-only FSD leaves a lot of edge cases on the table with the hope that AI magic will save the day.