This is interesting. It seems like sidestepping a problem which needs to be attacked head-on: the amount of solar we need to build is more than what can be built in invisible areas isn't it? Perhaps this helps to get things going for now but can we actually build enough in areas with no visibility from residential?
The amount of land required isn't that high. Nate Lewis at Cal Tech once told me that "the amount of light falling on the numbered highways of the USA can generate more power than the US's entire generating capacity.
Of course he didn't mean that we should cover all the highways; it just says we could afford to build and maintain them all and have that much land area, so building an equivalent area of solar would be both cheaper and feasible.
That was over a decade ago; solar is both cheaper and more efficient. IIRC something small like a hundred km2 or so of desert would do the trick. We spend much more of that growing corn that we wastefully turn into fuel.
I think only if you ignore distribution and overall grid integration which would constrain where you can place solar plants and ignore that in the winter you’re not going to get much power production from the North East and PNW regions (and when you do it’s super spotty).
By that logic of ignoring constraints, nuclear takes 0 land area compared to solar and could generate more power than solar panels we’d ever produce.
Were you replying to my note? The point, as I noted, is not to say "just stick them where the roads are" but rather as a sort of Fermi estimate -- the cost of deployment is demonstrably quite feasible. Whether people want to do it or not is unrelated.
FWIW there are a lot of deserts and plains that can be used for year round generation.
My point is that the fermi approximation is flawed because HVDC is still extremely expensive to transmit power from places where solar is plentiful to where it’s needed. So there are significant real world implications that make the approximation off probably by an order of magnitude. There’s a lot of solar energy but effectively time and distance shifting it turns out to be extremely difficult and expensive. That’s why solar and wind continue struggling to replace fossil fuels in the grid (modulo places like California, Florida and Texas with abundant sunshine throughout the state) despite the generators themselves being cheaper than ever; all they’ve managed to do is absorb daytime energy growth. It’s something but our absolute fossil fuel consumption in the grid has continued to grow substantially even if as a percentage it managed to stagnate or marginally decrease. Nuclear continues to have far more success at actually replacing fossil fuels in the grid, has meaningfully less land footprint than solar, and while gen iii reactors require some work to maintain safety, it still remains remarkably safe per mwh comparable to solar and gen iv reactors have fail safe designs that don’t carry any of the same maintenance concerns. We gave up on nuclear fission too early and easily due to FUD from the coal industry and it still remains the better path to fix the grid’s contribution to global warming.
Does this work address a specious, disingenuous argument that is being put forth by NIMBYs to block solar installation, so does it address a real pain point?
I agree we should be able to build enough solar but does this work address a real bottleneck or a fake problem presented as real by people with ulterior motives?
We could easily find many many large expanses of land, and given the margins on farming, many in my local area are renting / selling / building solar farms on the corners or harder-to-reach areas of their fields. Since those areas tend to have trees around anyway .... But none of that is really a viewshed problem unless you've modelled trees.
Now in hillier areas or mountainous regions this gets more compliated.
My rural community has a solar farm going in, and it is not going over well.
Lots of NIMBYs that “did their own research” to conclude that solar is actually bad for the environment or uneconomical or whatever. But the real reason for their rage is that they see it as a physical manifestation of the spread of “progressive ideas” and for that reason alone it must be stopped
These cookies were very good, not God level. With a bit of investment and more modern techniques I think you could make quite a good recipe, perhaps doing better than any human. I think AI could make a recipe that wins in a very competitive bake-off, but it’s not possible or for anyone to win with all 100 judges.
You’re right about Elon but I’ve thought about it and it’s flawed reasoning. Humans don’t do it “with vision” we do it with five senses and the human brain. The computer is severely limited compared to the human brain, so in the context of things like LiDAR, the computer needs all the help it can get. And for rain sensing, the camera doesn’t see the windshield like a person does!
Vision and hearing are the main senses we use to driving, and touch a distant third. Using taste, smell or proprioception means something is probably wrong with your vehicle.
Personally, proprioception ranks ahead of hearing for me.
Vision is first, but proprioception is how assess nearly everything else. Braking speed, acceleration, throttle input, cornering, traction, hydroplaning, tire pressure (even in specific tires), alignment issues (down to the specific wheel), balance issues, toe rod issues, transmission issues, engines issues, wind, payload, towing, etc, etc, etc.
I could probably tell you within 100lbs how much and roughly where payload is in the vehicle simply by feeling how the car is driving.
I literally cannot do racing game because I can’t sense the vehicle. Flip side, I used to think professional racers were crazy for being able to call in subtle issues to their crew chief. Turns out when you drive a specific car enough, you learn how it out to feel.
I thought about smell but actually vehicles do malfunction, and smell can be an important indicator. “Something is wrong with your vehicle” is a real scenario that actually happens pretty often.
I feel we must be using smell all the time to be able to detect when a burning odour begins to arise. It’s just that we’re not aware of it when nothing unusual happens.
Driving without proprioception is probably almost impossible. That's how you know where your hands are, how the steering wheel is turned, where your feet are, how to move your hand to the indicator lever, etc.
That is a reasonable argument that it is likely to be theoretically possible. It’s absolute madness to jump from “theoretically possible” to production without actually inventing and testing the technology. What is going on over there at Tesla? I suspect an emperors new clothes type of situation where employees are too terrified to state basic facts, like “we tested 20 ideas out but none worked, we haven’t figured out how to get this to work yet.” Not the kind of culture I want designing a 2 ton vehicle I’m trusting my families lives to.
> I suspect an emperors new clothes type of situation where employees are too terrified to state basic facts, like “we tested 20 ideas out but none worked
Or maybe the emperor is a "idea #16 is good enough for me" type of person?
Giving Musk the benefit of the doubt, probably his thinking is more along the lines of:
"I'd like to solve this with vision. Sure, we can ship a $5 part to do it the tried-and-true way, but if we do that then we're probably never gonna solve it with vision, because there will no longer be a pressing need to do so. So I'm gonna force us to not ship our cars with a proper rain sensor in the hope that it will continually push my teams to get this shit done and do the improbable".
There’s no doubt to give him the benefit of… even in your version they still decided to ship a basic feature that doesn’t work in a production automobile. Other car manufacturers push teams hard to develop new tech also, but they also test the heck out of them so they’re 100% functional before they would put it into production.
Piech was famous for outlandish demands on engineers at VW, but his demands took the form of the desired test results: the Phaeton had to be capable of being driven all day at 186 mph with an exterior temperature of 122 °F whilst maintaining the interior temperature at 72 °F. And they did it…
Fair point- that does seem like a likely explanation, I am just horrified that it would lead to putting broken systems on a mass produced production automobile.
That sounds so cool when a billionaire vision-guy says it. Too bad reality is that "pressing need" isn't magic, and sometimes just isn't enough. Like this time.
This is true in a sense, but humans incorporate so much more information. Like if I drive past a sprinkler, I know there will be a short burst of water hitting the window. But this requires a fairly complex assessment of the surrounding environment.
But it can be done better with more sensors. Why handicap the technology? It seems to me like the compromise isn’t worth it here.
My phone can take my face scan in a room that’s pitch black, because it uses infrared sensors and a projection of dots. It’s able to check who I am, regardless of the natural light in the environment. If that technology was limited to “only a camera” it would be way worse.
A camera is cheaper than LiDAR. But it’s also less capable.
As best I can tell. Other cars just use a dedicated infrared sensor to detect the water? Seems like a weird corner to cut. Seems like tesla cut those in favor of just having other cameras attempt to fill in? But seems like that isn’t working.
For seeing rain it's mostly that they are offset back from the windshield more. People over 50 barely have variable focus vision and it isn't really important in driving.
Gemini 1.5 Pro is on-par with GPT-4 and Opus in LMSys, and you can go try it for yourself in LMSys, and it's coming soon to Gemini Advanced (announced at I/O). Seems like GPT4O puts OpenAI in front again on LMSys
It says it may fall back to a worse model under load and there is no way to tell which you are getting. I think chatgpt has at times done something similar though.
The biggest reveal here is that they provide one of the clearest confirmations that Tesla has been lying about their crash statistics. Apparently they only log crashes with airbags and generally from police reports we know this is only 18% of crashes. They found and confirmed several instances of crashes that don’t show up in Teslas logs at all.
The number one search result for "Autopilot" on HN is still this 2017 article claiming a 40% reduction in crash rate: https://news.ycombinator.com/item?id=13437905 The subsequent revelations of the many flaws in this analysis never had one tenth the fanfare of course.
40% reduction in crash rate, not fatalities. It seems dubious that they could get fatality statistics wrong and get away with it. Creative statistics feels plausible with “crashes”.
I don't know the percentage, but the majority of minor collisions never result in a police report. The parties involved just deal with their insurers. When a guy scratched my bumper at a stoplight I didn't waste time calling the police.
Im surprised they didn’t try out Gemini. It’s a lot better than Google translate and in my experience this is one use case where Gemini outshines even other frontier models like ChatGPT4
