I seem to remember you being a computer guy? I'm a computer scientist, too. Thanks for the lesson?
None of what you said invalidates anything I said.
We can make guesses about what the future of GAI programming will look like, but all we really know is what we're doing today: deep machine learning / neural net stuff like TensorFlow, support vector machines like PEGASOS, gradient boosting engines like Yahoo's search result ranker, and so on.
Still, I wouldn't put money on any kind of bet about when we'll see a true AGI breakthrough. You're right that we're nowhere near it. The experts are saying 40-120 years, but that means they just don't know.
But my point was that machine learning algorithms do not rely upon human instructors to gain their expertise. If you're saying that in the future, AGI will be born as a baby and have to be trained by humans the way children are, then you're making a wilder prediction than I am, and with less data.
I'm just saying that if AI research continues to progress even vaguely in the the direction it's going now, someday reaching AGI levels, then likely these programs will be able to run billions of trial simulations to learn, and thus they'll be able to learn beyond what humans can teach them, and thus they'll be able to surpass us.
A clever AGI from the 29th century or whatever will still have 2018's machine learning algorithms "in its pocket," writing custom neural nets to conquer specific problems. When the AGI needs to master cooking, it can learn the basics and then train a neural net or prune a gradient boosted tree or building a regression tree ensemble of its own devise to master the skill.
But I think "no completely automated taxis within 10 years" is a bad bet...
None of what you said invalidates anything I said.
We can make guesses about what the future of GAI programming will look like, but all we really know is what we're doing today: deep machine learning / neural net stuff like TensorFlow, support vector machines like PEGASOS, gradient boosting engines like Yahoo's search result ranker, and so on.
Still, I wouldn't put money on any kind of bet about when we'll see a true AGI breakthrough. You're right that we're nowhere near it. The experts are saying 40-120 years, but that means they just don't know.
But my point was that machine learning algorithms do not rely upon human instructors to gain their expertise. If you're saying that in the future, AGI will be born as a baby and have to be trained by humans the way children are, then you're making a wilder prediction than I am, and with less data.
I'm just saying that if AI research continues to progress even vaguely in the the direction it's going now, someday reaching AGI levels, then likely these programs will be able to run billions of trial simulations to learn, and thus they'll be able to learn beyond what humans can teach them, and thus they'll be able to surpass us.
A clever AGI from the 29th century or whatever will still have 2018's machine learning algorithms "in its pocket," writing custom neural nets to conquer specific problems. When the AGI needs to master cooking, it can learn the basics and then train a neural net or prune a gradient boosted tree or building a regression tree ensemble of its own devise to master the skill.
But I think "no completely automated taxis within 10 years" is a bad bet...