I agree with everything you're saying; but even outside of Tesla, I'd just like to remind people that LIDAR as a complement to vision isn't at all straightforward. Sensor fusion adds real complexity in calibration, time sync, and modeling.

Both LIDAR and vision have edge cases where they fail. So you ideally want both, but then the challenge is reconciling disagreements with calibrated, and probabilistic fusion. People seem to be under the mistaken impression that vision is dirty input and LIDAR is somehow clean, when in reality both are noisy inputs with different strengths and weaknesses.

I guess my point is: Yes, 100% bring in LIDAR, I believe the future is LIDAR + vision. But when you do that, early iterations can regress significantly from vision-only until the fusion is tuned and calibration is tight, because you have to resolve contradictory data. Ultimately the payoff is higher robustness in exchange for more R&D and development workload (i.e. more cost).

The same reason why Tesla needed vision-only to work (cost & timeline) is the same reason why vision+LIDAR is so challenging.

Tesla has redundant front facing cameras on their cars. In my 2019 Model 3, there are three front facing cameras, each with varying angles of view, all three behind the rear view mirror, all encased in a small area lined with anti reflective material. Living in an extremely hot climate, that small area, with its anti reflective fuzz have degraded, depositing a film on the window, only in front of the cameras, obscuring all three cameras at the same time. Now, my Tesla just recently started complaining when the sensors were obscured with this deposit, but that wasn’t always the case. I used to be driving down the freeway with autopilot on, and it could barely track. Eventually I looked at the saved video footage and discovered my Tesla was virtually blind, while driving me down the freeway at 85mph. At least now, with recent updates, it warns me that it can’t see very well. However I question the resolution of the sensors. To drive legally in my state, you must have 20/40 vision. When I move my head around, I effectively have 20/40 vision all around my car. If I close 1 eye, I still have 20/40 vision. Does Tesla have effectively 20/40 vision in all 360 degrees? Maybe one of the front facing cameras has optical resolution equal to 20/40, but do the rest of them? I’m skeptical, and expect I’m being driven by what’s equivalent to a human who couldn’t pass the vision test, or at best, a human with just one eye that can pass the vision test. This isn’t even getting into redundancy in the electronics boards, connectivity from the electronics to the CPU, and redundancy in the processsing. We are being asked to put our faith/lives in these non redundant systems, but they’re not designed like Class-A flight critical systems on airplanes.

> Vision can fail for a multitude of reasons --- sunlight, rain, darkness, bad road markers, even glare from a dirty windshield. And when it fails, there is no backup plan

So like a human driver. Problem is, automatic drivers need to be substantially better than humans to be accepted.

Lidar is not a backup to vision, in a waymo both lidar and vision must be working, so you actually have less reliability as now you have two single points of failure.

Yeap. Same mistake that Boeing did with making redundancy optional upgrade on max8.

This. It's also the reason Waymo is ahead, they have tons of high quality training data being constantly fed into their pipeline.

I think LIDAR was and maybe still is way more expensive. Initially running 75k. Now they're more around 10k which is better.

Even if Tesla wasn't using LIDAR, I think they did still use radar and ultrasonic detection for a while, which I'm sure contributed to their models some.

Well I wish this was true. But loads of DEVs on here will claim LLMs are infallible.

And the general public?! No way. Most are completely unaware of the foibles of LLMs.

Lidar is being manufactured in china in the volume of millions a year by robosense, Huawei, and hesai. Bom cost is on the order of a few hundred dollars - slightly more than automotive radar. The situation is a lot different in 2025 than in 2017.

Pulse modulation.

https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-2-2013&id=5...

I think it can - I think it might encode something in the beam, use a slightly different wavelength or even just pulse the laser so that the returns don't overlap if timed right.

This is extremely narrow minded. As another commenter pointed out, you are driving on easy mode in terms of environment and where a majority of the training was done.

This is not a general solution, it is an SF one... at best.

Most humans also don't get in accidents or have problems with phantom breaking within the timeframe that you mentioned.

You're basically driving on easy mode, in the Bay Area. Dry climate, sunshine all year round, pretty solid developed country infrastructure.

OK so you believe "Elon was right" and people should "ignore the comments" Hmm very interesting.

> politicization

How is it politicization when TESLA THE COMPANY is saying Full Self Driving doesn't mean "Full" "Self" Driving?

If it is as good as you claim, why doesn't Tesla claim it's Full Self Driving?

>> it drives me 95% of the time now

But what is the point to use it everywhere if you still need to pay attention to the road, keep hands on the steering wheel?

HW4 is really a game changer. I was absolutely floored by HW4 FSD during a recent test drive. Tesla is accomplishing some truly groundbreaking technical achievements here. But you wouldn't know it through all the Elon Musk noise (pro and con). I'd encourage anyone to take a test drive and put FSD through its paces. I went in with a super critical mindset and walked away stunned.

What lead? They are way behind Waymo.

Why would anyone listen to the opinion of someone who bought a Tesla in 2025?

The only people still buying them are musk fanboys.

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Waymo sensor pods are mounted at the corners of the vehicle allowing it to see things that a driver can't. (E.g. when pulling out of an alley)

Is this like the same BS as Elon on an investor call recently?

One analyst asked about the reliability of Tesla’s cameras when confronting sun glare, fog, or dust. Musk claimed that the company’s vision system bypasses image processing and instead uses direct photon counting to account for “noise” like glare or dust.

This... is horseshit. Photon counting is not something you can do with a regular camera or any camera installed on a Tesla. A photon counting camera doesn't produce imagery that is useful for vision. Even beyond that, it requires a closed environment so that you can you know, count them in a controlled manner, not an open outside atmosphere.

It's bullshit. And Elon knows it. He just thinks that you are too stupid to know it and instead think "Oh, yeah, that makes sense, what an awesome idea, why is only Tesla doing this?" and are wowed by Elon's brilliance.

Sterling Anderson was the first autopilot director, and he was fired for insisting on Lidar. Elon sued Sterling Anderson, then hired the bootlick Karpathy to help him grease chumps.

For decisions of this scale (ie, tens of years of development time, committing multiple products to a single unproven technology), the CEO really should be involved. Maybe they’ll just decide to take the recommendation of the SMEs, but it’s hard for me to imagine Elon had no say in it.

I suspect so too, but is it factual?

That's an interesting take on this. Can you share the source?

Musk said it himself: https://www.youtube.com/watch?v=HmjuEikY4ew&t=502s

(For those who don't want to click through "LIDAR is a fool's errand, and anyone relying on LIDAR is doomed."

There's multiple comments in this thread pointing to Chinese car manufacturers paying under $200 for their LIDAR hardware.

Investments into re-engineering production to bring down cost is done when there is a market large enough for said product.

True self-driving is still a baby that needs to grow and cannot even compete against an adult human with 30+ years of experience. As self driving actually forms to that level the market will grown.

"Just git pull, and latest fixes it" is not reassuring in this context. Engineers evaluating your claims need real data, not marketing copy.

Meanwhile, the competition who is using LiDAR has FSD cars. You're understating the importance of this sensor.

You can train a DL model to act like a LiDAR based on only camera inputs (the data collection is easy if you already have LiDAR cars driving around). If they could get this to work reliably, I'm sure the competition would do it and ditch the LiDAR, but they don't, so that tells us something.

I think you might be under-estimating the importance of not hitting things.

If you look at the statistics on fatal car accidents, 85%+ involve collisions with stationary objects or other road users.

Nobody's suggesting getting rid of machine vision or ML - just that if you've got an ML+vision system that gets in 1 serious accident per 200,000 miles, adding LIDAR could improve that to 1 serious accident per 2,000,000 miles.

It's an extra sensor you'd add into the mix, you'd still have cameras. Like the radar sensors. I think the reason Teslas don't have it, is because the sensor hardware was expensive a few years back. I assume they are much cheaper now.

I don't know about you but one of my primary goals when driving is not hitting into things

> showing Jay Bhattacharya that the old regime had put him on a trends blacklist, and all the other people who got banned for no reason

He's doing the exact same thing and worse to people he doesn't like.

Teslas do not use the rain sensors discussed in this video, they use cameras to detect rain.

That's how every non-Tesla works. Tesla's don't do this method which is why their auto wipers have always been so bad compared to everyone else.

Going from cameras to the human model, every morning on my way to work humans suddenly slam their brakes for the sun in their eyes: if you can't see, you can't see. I think it's another good example why cameras are not enough alone.

OP says nothing else???

> this tells me volumes about what's going on in the computer vision system

Emphasis:

> computer vision system

> The cold hard truth is that LIDARs are a crutch

The hard truth is there is no reason to limit machines to only the tools humans are biologically born with. Cars always have crutches that humans don't possess. For example, wheels.

> they're not strictly necessary. We know this because humans can drive without a LIDAR

and propellers on a plane are not strictly necessary because birds can fly without them? The history of machines show that while nature can sometimes inspire the _what_ of the machine, it is a very bad source of inspiration for the _how_.

> The cold hard truth is that LIDARs are a crutch, they're not strictly necessary. We know this because humans can drive without a LIDAR, however they are a super useful crutch.

Crutch for what? AI does not have human intelligence yet and let’s stop pretending it does. There is no shame in that as the word crutch implies.

LIDARs have the advantage that they allow detecting solid objects that have not been detected by a vision-only system. For example, some time ago, a Tesla crashed into an overturned truck, likely because it didn't detect it as an obstacle.

A system that's only based on cameras is only as good as its ability to recognize all road hazards, with no fall back if that fails. With LIDAR, the vehicle might not know what's the solid object in front of the vehicle using cameras, but it knows that it's there and should avoid running into it.

The big promise of autonomous self-driving was that it would be done safer than humans.

The assumption was that with similar sensors (or practically worse - digital cameras score worse than eyeballs in many concrete metrics), ‘AI’ could be dramatically better than humans.

At least with Tesla’s experience (and with some fudging based on things like actual fatal accident data) it isn’t clear that is actually what is possible. In fact, the systems seem to be prone to similar types of issues that human drivers are in many situations - and are incredibly, repeatedly, dumb in some situations many humans aren’t.

Waymo has gone full LiDAR/RADAR/Visual, and has had a much better track record. But their systems cost so much (or at least used to), that it isn’t clear the ‘replace every driver’ vision would ever make sense.

And that is before the downward pressure on the labor market started to happen post-COVID, which hurts the economics even more.

The current niche of Taxis kinda makes sense - centrally maintained and capitalized Taxis with outsourced labor has been a viable model for a long time, it lets them control/restrict the operating environment (important to avoid those bad edge cases!), and lets them continue to gather more and more data to identify and address the statistical outliers.

They are still targeting areas with good climates and relatively sane driving environments because even with all their models and sensors, heavy snow/rain, icy roads, etc. are still a real problem.

> Yes machine learning vision systems hallucinate, but so do humans.

When was the last time you had full attention on the road and a reflection of light made you super confused and suddenly drive crazy? When was the last time you experienced objects behaving erratically around you, jumping in and out of place, and perhaps morphing?

> Anyway, I don't think Tesla were wrong to not use LIDAR - they had good reasons to not go down that route. They were excessively expensive and the old style spinning LIDARs were not robust. You could not have sold them on a production car in 2018.

The correct move for Tesla would have been to split the difference and add LIDAR to some subset of their fleet, ideally targeted in the most difficult to debug environments.

Somewhat like Google/Waymo are doing with their Jaguars.

Don't LIDAR 100% of Teslas, but add it to >0%.

I want my self-driving car to be a better driver than any human. Sure we can drive without LIDAR, but just look up the amount of accidents caused by humans.

I had taken for granted that the cameras in the Tesla might be equivalent to human vision, but now I'm realizing that's probably laughable. I'm reading it's 8 cameras at 30fps and it sounds like the car's bus can only process about 36fps (so a total of 36fps, not 8x30 = 240fps theoretically available from the cameras, if they had a better memory bus.) It also seems plausible you would need at least 10,000 FPS to fully match human vision (especially taking into account that humans turn their heads which in a CV situation could be analogous to the CV algorithm having 32x30 = 960 FPS, but typically only processing 140 frames this second from cameras pointing in a specific direction.

So maybe LIDAR isn't necessary but also if Tesla were actually investing in cameras with a memory bus that could approximate the speed of human vision I doubt it would be cheaper than LIDAR to get the same result.

You might not have the classical guardrails, but you are providing the neural net with a lot more information. Even humans are starting to find it useful to get inputs from other sensor types in their cars.

I agree that Tesla may have made the right hardware decision when they started with this. It was probably a bad idea to lock themselves into that path by over-promising.

Humans have the most sophisticated processing unit in the known universe to handle the data from the eyes. Is the brain a crutch?

This impulse to limit robots to the capacities, and especially the form factors, of humans has severely limited our path to progress and a more convenient life.

Robots are supposed to make up for our limitations by doing things we can't do, not do the things we can already do, but differently. The latter only serves to replace humans, not augment them.

I'd rather cars have crutches than the people they run over.

Musk's argument "Humans don't have LIDAR, therefore LIDAR is useless" has always seemed pretty dumb to me. It ignores the possibility that LIDAR might be superhuman with superhuman performance. And we also know you can get superhuman performance on certain tasks with insect-scale brains. Musk's just spewing stoner marketing crap that stoners think is deep, not actual engineering savvy.

(and that's not even addressing that human vision is fundamentally a weird sensory mess full of strange evolutionary baggage that doesn't even make sense except for genetic legacy)

You could write a rant like this about 4 vs 3 wheels.

I wish I had radar eyes

> Vision systems were improving a lot back then so the idea you could have a FSD on vision alone was plausible.

This was only plausible to people who had no experience in robotics, autonomy, and vision systems.

Everyone knew LIDAR was the enabling technology thanks to the 2007 DARPA Urban challenge.

But the ignoramus Elon Musk decided he knew better and spent the last decade+ trashing the robotics industry. He set us back as far as safety protocols in research and development, caused the first death due to robotic cars, deployed them on public roads without the consent of the public by hoisting around his massive wealth, lied consistently for a DECADE about the capabilities of these machines, defrauded customers and shareholders while becoming richer and richer, all to finally admit defeat while he still maintains the growth story of for Tesla's future remains in robotics. The nerve of this fucking guy.

1. A human has a lot more options to deal with things like sun glare. We can move our head, use shade, etc. And when it comes to certain aspects around dynamic range the human eyes are still better than cameras. And most of all, if we loose nearly all vision we are intelligent enough to simulate the behaviour of most objects around us to react safe for the next few seconds. 2. Human intelligence is much deeper than machine vision. We can predict a lot of things that machine visions have no hope to achieve without some kind of incredibly advanced multi-modal model which is probably many years out.

The most important thing is that Tesla/Elon absolutely had no way to know, and no reason to believe (other than as a way to rationalise a dangerously risky bet) that machine vision would be able to solve all these issues in time to make good on their promise.

The human brain is the result of literal billions of years of evolution, across trillions of organisms. The "just" in your "just a matter of sufficient learning data and training" is doing a lot of work.

This comment is a perfect illustration of the hubris of this technology in general.

If you have cheat codes then why not just use it instead of insisting on principle that our eyes are good enough? We see Waymo use the cheat codes, oh no. We also only have binocular vision, so I guess Tesla is already okay with superhuman cheat codes.

We not only use our vision when driving but also our other senses. We can tell the sun is shining at us because it warms our skin. This all happened subconsciously. Humans are vastly superior drivers in general, it’s just that 50% of humans are bad drivers.

It's a big if, no? Humans do struggle with sun glare. It'd be great if cars were much better.