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Much of so called software engineering is about assembling/wrapping other API/libraries anyway. I don't see how ML change the scenario, instead of querying som

by eva1984 10y ago

Much of so called software engineering is about assembling/wrapping other API/libraries anyway. I don't see how ML change the scenario, instead of querying some db, you are now querying some trained models. Until we have an algorithm that could write correct code given requirement specified in natural language, the demand or prospect of software engineer as a profession will not be affected by ML/AI too much. However it is hard to predict when such technique will emerge, 10 years? 20 years? maybe 50 years.

rawnlq 10y ago
The blog post specifically mentioned Program Synthesis which is exactly what you're talking about. The article they published was called Neural Programmers but I haven't read it: https://arxiv.org/abs/1511.04834 https://arxiv.org/abs/1511.04834 So at the very least they are working on it!
- UncleMeat 10y ago
  Its been a field of study for decades, though, with pretty minimal success. Every hot field gets applied to it (genetic algorithms being the hot stuff 6-10 years ago). I wouldn't worry yet.
- eva1984 10y ago
  Yes, there are work on this field. But so far all are just like toy examples. The big barrier here is natural language understanding, so far we have limited success even with deep learning at hand. If eventually natural language understanding is solved, it is going to be a much bigger deal than programmer losing their jobs.
- primaryobjects 10y ago
  The paper references program synthesis via neural networks. Here is my take on it, using genetic algorithms. http://www.primaryobjects.com/2013/01/27/using-artificial-intelligence-to-write-self-modifying-improving-programs/ http://www.primaryobjects.com/2013/01/27/using-artificial-in...
pinouchon 10y ago
The jury is out on this one. The probability distribution would be the surface of a mattress with a peanut under it (very flat). This is the branch of IA/ML that turns me on the most. When we get there, it will redefine many jobs (as well as create an existential thread as a side effect). I think it is sad that the terms AI and Machine learning do not make a clear difference between narrow and strong AI, this is the source of much confusion.

by eva1984 10y ago

rawnlq 10y ago

The blog post specifically mentioned Program Synthesis which is exactly what you're talking about. The article they published was called Neural Programmers but I haven't read it: https://arxiv.org/abs/1511.04834 https://arxiv.org/abs/1511.04834 So at the very least they are working on it!

UncleMeat 10y ago
Its been a field of study for decades, though, with pretty minimal success. Every hot field gets applied to it (genetic algorithms being the hot stuff 6-10 years ago). I wouldn't worry yet.
eva1984 10y ago
Yes, there are work on this field. But so far all are just like toy examples. The big barrier here is natural language understanding, so far we have limited success even with deep learning at hand. If eventually natural language understanding is solved, it is going to be a much bigger deal than programmer losing their jobs.
primaryobjects 10y ago
The paper references program synthesis via neural networks. Here is my take on it, using genetic algorithms. http://www.primaryobjects.com/2013/01/27/using-artificial-intelligence-to-write-self-modifying-improving-programs/ http://www.primaryobjects.com/2013/01/27/using-artificial-in...

pinouchon 10y ago

The jury is out on this one. The probability distribution would be the surface of a mattress with a peanut under it (very flat). This is the branch of IA/ML that turns me on the most. When we get there, it will redefine many jobs (as well as create an existential thread as a side effect). I think it is sad that the terms AI and Machine learning do not make a clear difference between narrow and strong AI, this is the source of much confusion.