You have two main pessimisms
- computer vision problems (e.g. plane catches fire, how do you tell how much fire etc.)
- tracking other objects in 3d while in moving in 3d at high speed
The question is - can humans do this? If yes, computers can do it eventually. The only question is how long away is this. What we know from machine learning, is that data is important. If you can gather enough data you can do anything. So really, your problems are a question of data collection. It is not a technically difficult problem. (By the way, one of the problems you have in aerospace is, is that you're control theory heavy rather than pro-ai, which means you end up not being able to solve the difficult problems.)
Also, the eu 80s project ended around early 90s, and the grandle challenge win was only 15 years later, not 30. Had the challenge been tried 5 years earlier, it would have worked. The algorithms and hardware was already sufficient.
- computer vision problems (e.g. plane catches fire, how do you tell how much fire etc.)
- tracking other objects in 3d while in moving in 3d at high speed
The question is - can humans do this? If yes, computers can do it eventually. The only question is how long away is this. What we know from machine learning, is that data is important. If you can gather enough data you can do anything. So really, your problems are a question of data collection. It is not a technically difficult problem. (By the way, one of the problems you have in aerospace is, is that you're control theory heavy rather than pro-ai, which means you end up not being able to solve the difficult problems.)
Also, the eu 80s project ended around early 90s, and the grandle challenge win was only 15 years later, not 30. Had the challenge been tried 5 years earlier, it would have worked. The algorithms and hardware was already sufficient.