Because there might be multiple different development approaches to solve the same problem. It makes sense to explore more than one of them.
Some cars don't use LIDAR (Tesla), some use end-to-end machine learning (geohot thing), some are more of an "assistant" systems and others aim at full autonomy. It's unclear which of these approaches will yield results long term.
Understood, but at the same time it's like multiple companies trying to fly to the Mars. They might never achieve such a huge goal without combining efforts. Instead, they're going to have their proprietary ways, patent them so no one else can use them and all solutions will be less than the best that's achievable.
I’m just saying there should be more collaboration instead of silos. Machine learning is advancing so much because mostly everything is shared openly via papers, talks, etc
Some cars don't use LIDAR (Tesla), some use end-to-end machine learning (geohot thing), some are more of an "assistant" systems and others aim at full autonomy. It's unclear which of these approaches will yield results long term.