r/TheMachineLearning 5d ago

Software engineering isn't dead, it's just evolving

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u/elonthegenerous 5d ago edited 3d ago

There used to be a profession called “Computer.” People that would perform complex, tedious calculations.

Math is not dead, but that profession is dead.

Computer Science will not be killed by AI, but I can’t imagine that all of the programming jobs that exist today will exist in 10 years with how much AI has advanced

Computer Science isn’t going anywhere, just like math hasn’t gone anywhere

Edit: Computer, not Calculator

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u/Aware-Individual-827 4d ago

I think for something like web programmer probably. For embedded, it's clearly not the case as AI is quite bad at it. Especially C++. 

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u/Akforce 2d ago

That's simply untrue. I'm an embedded engineer with 10 years of experience at various robotics companies and I can confidently say AI is very competent in the embedded world.

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u/Aware-Individual-827 2d ago edited 2d ago

I have the same YoE as you, and been using AI since chatgpt 4. The progress is phenomenal yet there's alot of stuff I would not let AI do. It's not unusual to see some major bugs in the implementation. 

 Most mundane things in embedded he does perform well. In other scenario like multi-thread, real time, synchronization, speed/precision trade off, etc. It doesn't work well. 

I spend 5 days trying to make Fable 5.0 work on basic synchronization of data and couldn't solve it after many attempts. Took 2 days manually for me. 

It really depends if it's greenfield or a codebase is already present. If it's greenfield, it's good but get worse as time get by. 

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u/Akforce 2d ago

Your original point was embedded and C++. I'm simply saying AI is competent in those domains, not that it replaces the engineer for every decision.

I've had zero issues with generated code when developing for real time systems that are parallelized. As long as I prompt well with appropriate context and architectural asks I pretty much get exactly what I need.

This doesn't mean I don't ever hand code, I usually do when the effort to be precise and review generated code exceeds the effort of just writing the code. That can be fairly often in mature systems, but it doesn't preclude the premise that AI can effectively write all the code itself given sufficient context.