"I just tested my hand in a mini version of this scanner. Images that are higher quality than MRI, whole body captured in <1 minute, virtually free to run. This is going to change medicine."
"As Alexander predicted in 'AI 2027,' OpenAI did release a major new model in 2025; unlike in his forecast, it’s been a damp squib. Advances seem to be plateauing; the conversation in tech circles is now less about superintelligence and more about the possibility of an AI bubble."
I'm not sure how many AI researchers would find this accurate. It seems to me that under conditions of ambiguity people often default to describing their preferred version of reality.
The comparison isn't really like-for-like. NHTSA SGO AV reports can include very minor, low-speed contact events that would often never show up as police-reported crashes for human drivers, meaning the Tesla crash count may be drawing from a broader category than the human baseline it's being compared to.
There's also a denominator problem. The mileage figure appears to be cumulative miles "as of November," while the crashes are drawn from a specific July-November window in Austin. It's not clear that those miles line up with the same geography and time period.
The sample size is tiny (nine crashes), uncertainty is huge, and the analysis doesn't distinguish between at-fault and not-at-fault incidents, or between preventable and non-preventable ones.
Also, the comparison to Waymo is stated without harmonizing crash definitions and reporting practices.