I always thought they deliberately tried to contain the genie in the bottle as long as they could

[1]: https://research.google/blog/towards-a-conversational-agent-...

IMO the presence of safety drivers is just a sensible "as low as reasonably achievable" measure during the early rollout. I'm not sure that can be used as a point against them. I'm comfortably with Tesla "sparing no expense" for safety, since I think we all (including Tesla) understand that this isn't the ultimate implementation.

It sounds like they removed Lidar due to supplier issues and availability, not because they're trying to build self-driving cars and have determined they don't need it anymore.

Using vision only is so ignorant of what driving is all about: sound, vibration, vision, heat, cold...these are all clues on road condition. If the car isn't feeling all these things as part of the model, you're handicapping it. In a brilliant way Lidar is the missing piece of information a car needs without relying on multiple sensors, it's probably superior to what a human can do, where as vision only is clearly inferior.

The issue with lidar is that many of the difficult edge-cases of FSD are all visible-light vision problems. Lidar might be able to tell you there's a car up front, but it can't tell you that the car has it's hazard lights on and a flat tire. Lidar might see a human shaped thing in the road, but it cannot tell whether it's a mannequin leaning against a bin or a human about to cross the road.

Lidar gets you most of the way there when it comes to spatial awareness on the road, but you need cameras for most of the edge-cases because cameras provide the color data needed to understand the world.

You could never have FSD with just lidar, but you could have FSD with just cameras if you can overcome all of the hardware and software challenges with accurate 3D perception.

Given Lidar adds cost and complexity, and most edge cases in FSD are camera problems, I think camera-only probably helps to force engineers to focus their efforts in the right place rather than hitting bottlenecks from over depending on Lidar data. This isn't an argument for camera-only FSD, but from Tesla's perspective it does down costs and allows them to continue to produce appealing cars – which is obviously important if you're coming at FSD from the perspective of an auto marker trying to sell cars.

Finally, adding lidar as a redundancy once you've "solved" FSD with cameras isn't impossible. I personally suspect Tesla will eventually do this with their robotaxis.

That said, I have no real experience with self-driving cars. I've only worked on vision problems and while lidar is great if you need to measure distances and not hit things, it's the wrong tool if you need to comprehend the world around you.

I thought it was the Nazi salutes on stage and backing neo-nazi groups everywhere around the world, but you know, I guess the lidar thing too.

If that doesn't make it obvious what they can and cannot do then I can't respect the tranche of "hackers" who blindly cheer on this unchecked corporate dystopian nightmare.

Dictionary def: "a machine controlled by a computer that is used to perform jobs automatically."

You can also probably still use it for some kinds of evaluation as well since you can detect if two point clouds intersect presumably.

In much a similar way that LLMs are not perfect at translation but are widely used anyway for NMT.

And I'll add that it in practice it is not even that much unless you're doing some serious training, like a professional athlete. For most tasks, the accurate depth perception from this fades around the length of the arms.

Also subtle head and eye movements, which is something a lot of people like to ignore when discussing camera-based autonomy. Your eyes are always moving around which changes the perspective and gives a much better view of depth as we observe parallax effects. If you need a better view in a given direction you can turn or move your head. Fixed cameras mounted to a car's windshield can't do either of those things, so you need many more of them at higher resolutions to even come close to the amount of data the human eye can gather.

There have been a few attempts at solving this, but I assume that for some optical reason actual lenses need to be adjusted and it can't just be a change in the image? Meta had "Varifocal HMDs" being shown off for a bit, which I think literally moved the screen back and forth. There were a couple of "Multifocal" attempts with multiple stacked displays, but that seemed crazy. Computer Generated Holography sounded very promising, but I don't know if a good one has ever been built. A startup called Creal claimed to be able to use "digital light fields", which basically project stuff right onto the retina, which sounds kinda hogwashy to me but maybe it works?

More subtly, a lot of depth information comes from how big we expect things to be, since everyday life is full of things we intuitively know the sizes of, frames of reference in the form of people, vehicles, furniture, etc . This is why the forced perspective of theme park castles is so effective— our brains want to see those upper windows as full sized, so we see the thing as 2-3x bigger than it actually is. And in the other direction, a lot of buildings in Las Vegas are further away than they look because hotels like the Bellagio have large black boxes on them that group a 2x2 block of the actual room windows.

It's possible they get headaches from the focal length issues but that's different.

I don't.

That's why I said "variable cost of operations."

If a system doesn't generate enough revenue to cover the variable costs of operation, then every single new passenger drives the system closer to bankruptcy. The more "successful" the system is -- the more people depend on it -- the more likely it is to fail if anything happens to the underlying funding source, like a regular old local recession. This simple policy decision can create a downward economic spiral when a recession leads to service cuts, which leads to people unable to get to work reliably, which creates more economic pain, which leads to a bigger recession... rinse/repeat. This is why a public transit system should cover variable costs so that a successful system can grow -- and shrink -- sustainably.

When you aren't growing sustainably, you open yourself up to the whims of the business cycle literally destroying your transit system. It's literally happening right now with SF MUNI, where we've had so many funding problems, that they've consolidated bus lines. I use the 38R, and it's become extremely busy. These busses are getting so packed that people don't want to use them, but the point is they can't expand service because each expansion loses them more money, again, because the system doesn't actually cover those variable costs.

The public should be 100% completely covering the fixed capital costs of the system. Ideally, while there is a bit of wiggle room, the ridership should be 100% be covering the variable capital costs. That way the system can expand when it's successful, and contract when it's less popular. Right now in the Bay Area, you have the worst of both worlds, you have an underutilized system with absolutely spiraling costs, simply because there is zero connection between "people actually wanting to use the system" and "where the money comes from."

This isn't just happening in America. Train systems are in rough shape in the UK and Germany too.

Ebike shares are a much more sustainable system with a much lower cost, and achieve about 90% of the level of service in temperate regions of the country. Even the ski-lift guy in this thread has a much more reasonable approach to public transit, because they actually have extremely low cost for the level of service they provide. Their only real shortcoming is they they don't handle peak demand well, and are not flexible enough to handle their own success.

I think you'd be surprised. Look at the difference in cost per passenger mile.