> Would you trust a ML self-driving algorithm trained on a "digital twin" of a city? I would.
No, just as I wouldn't trust a surgeon who studied medicine by playing Operation. A gross approximation is not a substitute for real life.
No, just as I wouldn't trust a surgeon who studied medicine by playing Operation. A gross approximation is not a substitute for real life.
I could've had the nurse close me up and leave me with a scar, which she admitted would happen with her practice, or I could have someone with extensive experience treating wounds so that they'd heal in cosmetically appealing way do it. I opted for the latter.
How it is tested and validated is what matters.
There are lots of ways to train on synthetic data, and synthetic data can have advantages as well as disadvantages over natural data.
Creative use of synthetic data is going to lead to many cases where we find it is good enough. Or even better than natural data.
Similarly, when this doctor sees something new, will they just write it off as something they've seen before and confidently work from that assumption?