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posted by
martyb
on Thursday July 26 2018, @08:01AM
from the if-it-walks-like-a-duck,-sinks-like-a-duck,-oh,-wait... dept.
from the if-it-walks-like-a-duck,-sinks-like-a-duck,-oh,-wait... dept.
The Los Angeles Times reports:
The duck boat that sank in a Missouri lake last week, killing 17 people, was built based on a design by a self-taught entrepreneur who had no engineering training, according to court records reviewed by the Los Angeles Times.
The designer, entrepreneur Robert McDowell, completed only two years of college and had no background, training or certification in mechanics when he came up with the design for "stretch" duck boats more than two decades ago, according to a lawsuit filed over a roadway disaster in Seattle involving a similar duck boat in 2015.
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Duck Boat in Missouri Disaster was Designed by Entrepreneur With no Engineering Training
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(Score: 2) by tibman on Thursday July 26 2018, @07:46PM (1 child)
Ranting on NN without even recognizing what it's good for. It's a fuzzy matching system so it's far far superior to a deterministic expert logic system when dealing with fuzzy problems. It does approximate pattern recognition. This widget coming off the product line is 15% different than the reference picture, kick it out for a human to examine. See a face in a high security zone that isn't on the clearance list, notify security. NN does basically what a human does. Humans are allowed to do stuff in warehouses, factories, refineries, and so on. But you wouldn't use a human as your control system. They'd take a short break and something would catch fire.
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(Score: 2) by Knowledge Troll on Friday July 27 2018, @02:52AM
I think the way to state this is that the neural network can solve problems that are not solvable well or at all with classic control theory. This is specifically because the NN is always an approximation of a function that achieves the goal and can be represented in a smaller space (less code, less memory, less everything) than a function that can be proven to work correctly or optimally. That has a lot of utility and I recognize that.
What I don't recognize is the cost vs benefit of using a NN in a space like the robot cars. I do recognize that the problem is most likely so complex that normal control theory can't handle it. Restating it simply: NN or other AI is the only way that robot cars can ever work.
That's frighting and I can't see how the NN control system is fit for this purpose in any way.
I think at the very least that the robot car control system is trying to solve a problem so complex that it will always be marginal. I have this theory that there are problems that get to a sufficient level of complexity such that no (practical?) system can solve them. Our brains are such a system - we need a ton of heuristics or we couldn't make it through a day. The robot needs a ton of heuristics or it can't move.
We already have highly heuristic AI control systems in cars: humans. It would not surprise me at all if the robot car winds up never safer than or no more safe than a human.