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> embedded systems, which is where most safety critical code lives For how much longer? The machines running self-driving cars aren't tiny little processors r
by throwaway729 10y ago
> embedded systems, which is where most safety critical code lives
For how much longer?
The machines running self-driving cars aren't tiny little processors running single threaded code. They're basically full server racks worth of compute with multi-core cpus, gpus, and who knows what else.
The current approach of "use crufty-but-trustworthy hardware and never do anything too complex" doesn't scale to the next generation of "embedded".
- Qworg 10y agoSelf driving machine code is inherently unsafe, as we don't have observability for the neural networks that run the most advanced models. The safety critical portion of the code focuses around running the base functions of the car. One of the major hurdles to real Level 5 systems is proving their correctness.
- throwaway729 10y ago> The safety critical portion of the code focuses around running the base functions of the car. There's the rub. They don't meet the standards of safety-critical code, but they are safety critical. I'm not sure how this challenge will be addressed, but I doubt the answer is "write everything in C". That approach works when your code is relatively simple, but doesn't scale when the code is actually extremely complex.
- nerdponx 10y agoBut the deep networks and such that power a self-driving car aren't written in C anyway. Or are they?
- blackflame7000 10y agoThey most likely are written in C/C++ because the training algorithms are computationally intensive.
- Fricken 10y agoC++ skills are strongly desired by self driving car companies https://hackernoon.com/five-skills-self-driving-companies-need-8546d2aba7c1#.pu9wjnllj https://hackernoon.com/five-skills-self-driving-companies-ne...
- throwaway729 10y agoThey are but that doesn't make them analyzable... Dealing with C craziness AND dnn craziness is silly. And the latter craziness is essential.
- planteen 10y agoA team of PhDs using modern control theory can prove stability of an aerospace control loop across all different operating conditions. A team of software engineers can then implement that with static analyzers and run time checkers during development to give confidence to an implementation. Can you prove stability of a deep learning system across all possible operating conditions it may encounter?
- throwaway729 10y agoCan you do the perception tasks that self driving platforms do using only control theory?
- planteen 10y agoI'm not talking about self driving at all. I took your earlier comment to mean that the you thought the future of avionics control and other classical embedded problems would be using DNNs. Maybe that's not what you meant.
- throwaway729 10y agoNo. That would be crazy. Well maybe not really as planes become more autonomous and airspace more crowded, delivery drones and so on, but we are still a long way from that. I was thinking more of self driving though.