Part 7/8:
Despite the promising current state of Tesla's technology, Phil mentioned significant challenges related to the need for vast computational resources. As Tesla rolls out more sophisticated models with increased parameters, training time and resource allocation become critical factors. The conversation highlighted that computational bottlenecks serve as a key hurdle for Tesla and other manufacturers aiming to reach full self-driving capabilities.
While many believe that once Tesla achieves true autonomy, other manufacturers can simply replicate the technology, Phil asserted that the proprietary complexities, data selection efficiencies, and specialized computational infrastructure that Tesla has developed present virtually insurmountable barriers for competitors.