Not trolling, but I'm actually curious how it gets "better" in this case? I mean was it ever meant to actually code?
As far as I can tell, until it actually understand what it is doing, it's just kind of "blending" what it thinks the most common response is based on thousands of other similar responses to similar questions.
I can imagine people tweaking it down to be more "right" in some cases, but then won't it just become more wrong in other cases?
I'm actually starting understand why AI is good at generating pictures, statistically it's just flipping bits to look like other bits it's seen relative to the input specified. Code on the other hand is something which needs/should to be more precise.
There's also the fact that the more people lean on this tech, the more mistakes will be perpetuated into the system and the less samples it will have available to learn from, as people are no longer feeding it new answers.
I guess like how DeepMind trained AlphaGo, it can code itself to learn, but I I do imagine the problem space for it to "play itself" against is practically infinite, even compared to go, the game, which is also a huge space.
I'm a software person, not an AI person, but I love thinking about it.
So it will go from generating toy code that usually compiles, to being able to one day reliably solve day 1 advent of code brain teasers, to generating useful software?
Is there domain limitation to this growth and performance? Medicine, theoretical physics, art, engineering, pure/applied maths, etc.?
I don't see how you guys are getting this from the current tech? Maybe there is an educational resource someone can suggest?
As far as I can tell, until it actually understand what it is doing, it's just kind of "blending" what it thinks the most common response is based on thousands of other similar responses to similar questions.
I can imagine people tweaking it down to be more "right" in some cases, but then won't it just become more wrong in other cases?
I'm actually starting understand why AI is good at generating pictures, statistically it's just flipping bits to look like other bits it's seen relative to the input specified. Code on the other hand is something which needs/should to be more precise.
There's also the fact that the more people lean on this tech, the more mistakes will be perpetuated into the system and the less samples it will have available to learn from, as people are no longer feeding it new answers.
I guess like how DeepMind trained AlphaGo, it can code itself to learn, but I I do imagine the problem space for it to "play itself" against is practically infinite, even compared to go, the game, which is also a huge space.
I'm a software person, not an AI person, but I love thinking about it.