I don't care even if you said you had 70% of the experience their team has, what you say can't sound reasonable or caring for actually improving safety in numbers.
I don't care even if you said you had 70% of the experience their team has, what you say can't sound reasonable or caring for actually improving safety in numbers.
With that out of the way, it's much easier to write a hardware safety case than one for software. It's easier to write a software safety case for a traditional software architecture than one based on ML. It's much easier to write a safety case for focused models than an E2E system. None of these should be controversial statements.
You're arguing that Tesla is deliberately jumping to the hardest safety case in order to avoid the simpler safety case. I know many people who have worked on the relevant teams at Tesla. I don't think they're ignorant of the difficulty of Tesla's choices or making decisions based on what's easier to validate.
Sensor fusion is not the difficult part. You only have to look at the fact that virtually every other company in the industry (even the ones using E2E and not using LIDAR like Wayve) does it. Either we have to accept that everyone else is stupid, or there are other factors involved in Tesla's decision-making.
For what it's worth, I'm not sure if I could write a safety case about Tesla's system that meets my own personal standards. It's pretty clear from their actions and the various regulatory/legal inquiries that they don't have what I consider an effective safety process regardless.
This is really no different from good code practices with a complex system. Most HN readers should be familiar with rot in codebases quite comparable to "adding a few extra features to make it better" which just became a maintenance burden and take away from core features.
If you knew the slightest of how Musk has actually stayed exactly the same since the beginnings of Tesla, you'd know his hard specs are always technology-based. People that know more have said that his capability of speccing systems relatively right deep in to the future is possibly his single greatest leadership feat.
>Once Musk is near-certain about one technology pathway over another, he’s not afraid to put massive amounts of resources into that path, while still staying flexible enough in the case that a new emerging technology disrupts that particular path. Because he’s willing to make enormous (and seemingly risky) bets on these pathways, he’s able to outpace his competitors. https://www.quora.com/Is-Elon-Musk-all-that-hes-cracked-up-t...
For an example of that in self-driving, Huawei uses vision, lidar, radar, and ultrasound. Out of Spec let it drive them around for an hour in busy traffic in a city in China. It looked about as good as FSD, without having had several million cars providing training data for years.
Clearly Tesla engineers will do the same