HALtheWise
Joined 8 years ago
Joined 8 years ago
None of this is impossible, but it could make it really expensive to produce an image that passes forensic analysis.
This sort of concern is presumably why Apple says "Using a neural network with hidden weights, PCC computes a confidence score for the photograph." I'm assuming that things like moire-patterns from pointing the camera at a screen would be caught by that check.
It's of course physically possible to fool the sensor, but at some point it becomes cheaper to just build a UFO and fly it over the actual Golden Gate Bridge.
This claim is situationally true, but not universally so like many people seem to believe. For example, Brightline rail service in Florida has been operating since 2017 and averages (by my math) 29.8 deaths / 100M passenger-miles, while the road system in Florida averages 0.89 deaths / 100M passenger-miles. Those deaths are mostly not suicides, and imo we should treat pedestrian deaths from trains as substantially more morally weighty than passenger deaths, since it's a victim that didn't opt-in to the risk.
For what it's worth, the unusual spike in Spain train crashes this year seems to have pushed them barely over the fatality numbers of Spanish cars (0.91 deaths/100M pax-mi vs 0.73 for cars) but that's pretty clearly an outlier.
If you measure per vehicle-mile rather than per passenger-mile I'm pretty sure trains are always way more dangerous, although that's a less fair comparison.
That ends up being a really powerful primitive for library authors to get users off of deprecated functions, as long as the old semantics are concisely expressible with the new features. It can even be used (and I'm hoping someone makes tooling to encourage this) to auto-migrate users to new semver-incompatible versions of widely used libraries by releasing a 1.x version that's implemented entirely in terms of thin wrappers around 2.x functions and go fix will automatically upgrade users when they run it.
I'm not aware of any statistics for how often children come into contact with human-driven cars.