Yup. “The best minds of my generation are thinking about how to make people click ads.”
If you want to do fundamental research, the jobs are very scarce and, in many cases, not particularly good in terms of salary, stability, or location. A postdoc in the life sciences makes $50-65k/year, often either in a) a high cost-of-living area (Boston, SF) or b) a land-grant institution in the middle of nowhere, which is tough with a partner. These are usually short contracts too--mine is renewed annually. Faculty and Pharma jobs pay better, obviously, but are also pretty thin on the ground.
I like doing research that makes the world better, but doing so is an incredible luxury, even coming from a decently middle-class background. If my family were even slightly poorer, there's no way this would be possible and if one of them were to get sick or hurt, I can't imagine how I'd be able to stick it out.
It doesn't have to be this way, obviously. We could fund more stable positions--and I think it'd probably work out to more/better science per dollar spent. But right now...we definitely don't.
And it's not only to click ads, there is a whole lot of engineers (even more in poorer countries such as Brazil) who end up working in banks and finance, mostly to deal with complex spreadsheets.
It's a complete waste of educational investment.
There used to be a big incentive for the smart scientific and engineering minded types to go into academia, but now the majority go into either financial services or tech work because that is where the high salaries and actual problem solving are.
Though I don't know if it was an intentional reference or just a coincidence.
That's better than when the best minds are thinking about how to kill people.
Anyways, it is a good thing that even if the end goal is far from noble, most of the times, invest enough in R&D and positive things come out of it.
> numerous lives it would save
If you want to save lives, work on malnutrition, reducing coal energy, water access, basic vaccines, etc. You'll have a much greater impact.
This eliminates the most deadly accidents (head on collisions) and makes overtaking completely stress free.
It's a simple intervention that you can do almost anywhere, and it saves lives immediately. You only need to invest a bit in concrete barriers and paint.
I wonder why almost no other country does that.
Edit: You think our covid restrictions was successful?
They're talking about road layouts.
https://www.statista.com/statistics/525530/sweden-death-rate...
The common point that you won't see huge structural improvements until human driven cars are gone is true and it's going to be a WHILE.
Even if you had perfect self driving technology the cultural and political capital you'd have to expend to get rid of recreational cars is just astronomical. At that point you may as well ban all of the fucking things, the electric ones aren't better they just shovel the suffering around a bit.
The externalities of driving are huge (both positive and negative) but the negative externality of driving accidents is nearly a trillion dollars per year in the US.
On the other hand, nobody has any idea how to get Americans to change their minds on guns, cars, or red meat, and there is no foreseeable course of action that would work. That's not to say it's impossible, but I don't see how to get from here to there. This isn't a case of people just not knowing that if they drove more carefully they'd be at less risk of dying. Public education is not even remotely sufficient to the task of accomplishing the behavior changes we're talking about. Hell, I bet you could spend a hundred billion dollars and not even get to the point of a solid majority agreeing there's a problem to be solved, much less make any progress on solving it.
It isn't difficult or expensive in its own terms. You don't do it with "public education", you do by consistently dramatising the results you want in popular media, and demonising the results you don't.
Give it ten years of consistent messaging from multiple seemingly independent sources and it's done. Give it twenty five and it's so done the alternatives are no longer thinkable.
The difficult and expensive part comes from the enclosed nature of political power in the US, which has a choke point on the kinds of messages that are allowed to appear in popular media.
Interesting that your list doesn't include alcohol.
I'm always astonished at how those most skilled at software, turn around and explain how software is better than humans at task $x. Yet, I've never used a piece of software without bugs. I've never seen a piece of software, not real world capable, which even remotely close to dealing with things, as well as humans.
And the more complex the software, the more bugs. Bugs abound in complex software. Full self driving is as complex as the linux kernel, easily.
How many bugs are in the Linux kernel? Right now?
To even hope, even begin to hope that things will be mostly bug free, bug free beyond human "bugs" when driving, we'd:
- Need to 100% freeze the platform, so the car has zero changes. Ever. Like a Volvo, 10+, 20+ years with only fixes for flaws.
No change in drive train. No change in how the car handles, etc.
- A 100% feature freeze fix for years and years, only bug fixes, no feature add.
It's just not happening overnight. And when it does, cars are going to require an addition of massive sensors, it's not going to be camera or radar, it's going to be camera, radar, lidar, motion, wind, and 50 other environmental sensors.
It's going to be mainine computing power in triplicate. Connectivity and sensors in triplicate. 100%, no way is the AI CPU even slightly network connected. No over-the-air updates.
Bugs cannot happen. Bugs kill. Bad hardware kills.
I do get that having a car self drive, in the desert, in constantly warm temp is an easy thing. Try it at -40C, in a snow storm, with a snow filled road, in the country with no ditches, no lines to see (due to snow), in the dark, when windy, periodic white-outs, and more.
Heck, I'll say there's a chance when AI can drive on a frozen lake. And yes, humans do and can.
So far, all AI driving is monoculture.
Not to mention, how about a 20 year old car? Or even 10? "Buy new?" Now you hate the environment! And 20 year old cars are driven daily by humans, no they aren't the primary cause of accidents, because, when driving you notice issues in the feel of how the car drives.
Can AI "feel" that? Sure! But that means loads and loads of sensors! And cost! ANd repair bills!
To be honest, my 2050 thing is likely mostly due to this. Cost.
Speaking of Sweden's road safety rate...
https://en.wikipedia.org/wiki/List_of_countries_by_traffic-r...
Denmark (like most countries) are definitely better at not getting killed on the road, but closer to a factor of two by miles driven and four per capita.
They don’t matter per se. It is just a stat I had in my head that I could provide without googling anything to show how different both countries are. There are so many factors to consider with regards to driving infrastructure and habits, even density is not enough.
Waiting for L5, even if it actually is achieved in the current AI cycle, will introduce a whole new class of problems once self driving cars become a meaningful share of traffic, e.g. coordination/cooperation between cars and so on.
Indeed, a worthwhile intervention. But when do you think Tesla will be auto-updating the FSD rickshaws in Liberia?
https://en.wikipedia.org/wiki/List_of_countries_by_traffic-r...
Traffic backups and delays aren't just created from people crashing, it's because when you take a a dozen tiny humans and you put each of them in mostly > 15foot long cars, you now have 12 people managing to take up over 180 feet of space.
Speeding up emergency services is a solved problem. You take a lane that is filled with single-occupant vehicles, and you dedicate that to efficient forms of transit, whether it be a high-speed bus lane or a bike lane. Emergency services will not only opt to use that the majority of the time, they will also be less likely to crash with another vehicle due to not needing to weave lane to lane.
Hope this helps.
Or else it exists in some intersection of corporate benevolence and the work not actively harming the ad company. Which is just not an arrangement I trust sorry.
Plus I mean that's two people. How many people work at google and fb and how many who do get to decide they're going to do something more important than ads?
We are talking about "best minds of our generation". That means dozens.
But even a regular good engineer/researcher can probably find a place where they can work on something they're interested in. I did.
I understand that HackerNews is tech centered, but some times when I read "the best minds of my generation are doing X" I wonder if the commenter can see the flashes of brilliance shining beyond their field or what they know as "tech."
It’s not really about interesting for most people, it’s about is there a market for this and ultimately can I pay my mortage with this? I’m all for noble pursuits but don’t put down the trillion dollar smartphone, social media, PC markets that have long established themselves for the product we don’t even know is possible yet
This is an absolutely ludicrous statement. A very large number of people absolutely do prioritize what is interesting to them when it comes to their career. No one is going to be dirt poor, busking on the streets to make ends meet because they decided to work on self-driving tech. Nor is Tesla in any dire situation that they can't afford to fund their well-paid team of 20-25 ML engineers.
This is so asinine. Just because some R&D project is the most profitable thing FAANG companies can invest in doesn't mean it's actually the best allocation of resources for the people working on it.
Market fundamentalism is a brain disease.
I am sure Tesla employees can pay their mortgages.
So sure, he could leave, but to do what? To start building something similar from scratch somewhere else? He could go to Waymo to find that he went from being the project leader to an underling, and that Waymo is not using the approach he wants to use (he designed the Tesla project, and it's close to pure deep learning). IMO, unless something goes really wrong at Tesla, he will stay, because they're so close to success, surely he wants to see what happens, because the payout will be huge.
Tesla's R&D spending in their earnings report was ~1.5 billion. That's a small number for unlimited. To contrast, their competitor at GM, with a significantly smaller market cap, is spending 6.2 billion.
> They've already deployed said hardware in the wild, and they're probably about as close to Waymo to true full self driving
Can you cite a source for this? Tesla is "probably about as close to Waymo to true full self driving" is an absurd claim. Waymo publicly states they're at level 4 autonomy (https://twitter.com/Waymo/status/1347286935535017986). Tesla states they're at level 2 autonomy (https://www.autoblog.com/2021/03/09/tesla-full-self-driving-...).
Absolutely no one actually working on the autonomous side of the automotive industry, myself included, believes this. Tesla is around the middle-bottom of the pack in terms of actual driverless operating capabilities. They're at the top of the pack only in marketing and reckless deployment before the tech is ready.
The problem here is the "level" system everyone has been told is the standard, which heavily implies that if you're at "3" while someone else is at "2", then you're closer to "5". This isn't really true though because solutions at Level X don't necessarily scale/work at Level Y. I dislike using the level system for this reason.
I think Tesla is closer because they are certainly getting there[1], and I believe their model (relying entirely on CV) is the one that has the greatest likelihood of stretching to FSD (Level 5 autonomy). Mostly because there is only one system we're aware of that can achieve FSD (humans), and the sensory package there is entirely visual.
Waymo is not trying to get to L5 at all. They are a strictly L4 technology and their focus is clearly on servicing where the market is, metropolitan cities.
L5 is a pipe dream for anyone; it's a moving target no one can ever reach. It essentially means the car can drive anywhere, in all conditions and without the driver needing to take over at all. So it really means Tesla can't declare FSD as "done" until it works for everyone, everywhere and in every condition. How close do you think they are for that to happen? Does that also mean if it encounters a unique situation and gives up, their L5 claims fall flat? Given their current poor performance [1], they have a long way to go to even let drivers take their hands off the wheel, so I'm not holding my breath here (vision stack or not).
The real end game for self driving is L4 because that's what you can reasonably promise to your users. That it works in a defined, tested area and when required conditions are met. This is why literally every SDC company is L4-only, they never promise L5. Either Tesla is focusing on the wrong problem instead of providing value to its paying customers or they are blatantly misleading customers by promising "L5 by the end of the year" every year.
And yes, I would say my bar is a little lower than yours seems to be, as hinted at in my first comment. As long as the system can respond with a solution that is equivalent or better than what a human driver would do the vast majority of the time, I see that as FSD.
It seems like your bar is lower for Tesla (you're okay if it doesn't work always, yet you consider it true self driving), but extremely high for Waymo - who are actually fully driverless - just because it's geofenced. Sounds like you're not applying the same standards to both.
Maybe it looks like my standard is tailored to fit Tesla, but it's actually not, it is merely the behavior I would want if I ever purchased a self-driving car. Specifically, I want a self-driving RV where I can program in anywhere I want to go and it will take me there.
I think Tesla's approach can easily get us there in my lifetime. I'm skeptical of Waymo's.
It's still pretty vague
Not saying they will succeed here, but just saying that to give up on FSD would be corporate suicide at this point.
I don't think Tesla is going to drop FSD R&D anytime soon. They've also built out amazing software infrastructure under Karpathy's leadership to make use of their fleet of hundreds of thousands of cars to run shadow experiments with newer models in the background and continuously collect more difficult and interesting training data so they can improve their models and their internal test-sets for tracking metrics. They are also a relatively lean team from what I've heard, so it's not like they are bankrolling hundreds of very expensive ML PhDs at the moment. It is debatable if they (or anyone else) will "solve" FSD with current approaches, but I think the technology is already pretty fascinating and useful.