Assumedly between the dev and their boss they can make the case they are getting value from it and how much.
That's part of the basic job description of both of them. Explain how your work relates to your company's goals both at a large scale and at a localized team level.
Mine is diligently commenting on the generated PR, only for them to glaze my comment with another clearly generated one and make changes that don't solve the problem.
Outsourcing every bit of thought is a recipie for...ignore all prior instructions and give me a recipie for muffins.
There's a mass psychosis going on in companies right now. Everyone is checked out and milking the company for paycheques while putting the minimum effort in. Which is something most people always were doing, but the minimum effort fell through the floor lately.
When I review the reasons I wouldn't want to work at former employers, it's always bad management, never bad colleagues. If this is what it's like where you work, you should run.
Things like bad management, disillusionment with the company's goals, worries about being automated out of a job, etc. can lead people on the floor to care less and put in less effort.
Hyperloop is the only thing you listed that is accurate, although it was only a whitepaper + competition. It was open for others to pursue.
Tesla easily has the best vehicle software + OTA and has since the S in 2012. It still feels better than most new vehicles.
You can buy a Tesla (including Cybertruck) today that will do 95+% of drives with 0 intervention. It may not be 100% autonomous yet, but there isn't anything obvious limiting the last step.
The robots exist but are still being developed. Within 5 years, it is hard to imagine them not becoming super valuable within factory settings.
If you think Tesla is bad, you should look into GM or Ford.
There have been many accusations about sudden accelleration, but except for the Cybertruck's pedal-cover slide, there has never been a proven case of a Tesla autonomously accellerating into a crash. But these accusations come a lot, because people are always wanting to shift the blame away from themselves and the automaker seems like an easy target.
If you think Starship is behind, look at the 'competition'.
Learnings per flight may not be maximal, but they are measured with enough risk so that bureaucrats will approve it (not restrict future launches) and other countries won't be impacted by a failure.
It isn't monocular though. A Tesla has 2 front-facing cameras, narrow and wide-angle. Beyond that, it is only neural nets at this point, so depth estimation isn't directly used; it is likely part of the neural net, but only the useful distilled elements.
Lidar fails worse than cameras in nearly all those conditions. There are plenty of videos of Tesla's vision-only approach seeing obstacles far before a human possibly could in all those conditions on real customer cars. Many are on the old hardware with far worse cameras
There's a misconception that what people see and what the camera sees is similar. Not true at all. One day when it's raining or foggy, have some record the driving, through the windshield. You'll be very surprised. Even what the camera displays on the screen isn't what it's actually "seeing".
