I see how the term neuronal network reinforces this believe, but we (especially the researchers among us) should allow for the possibility that we are missing something.
For example, you can feed a neural net all the recipes of burgers to create a perfect burger. Great. But how does the same net invent the burger?
The burger, like many foods or accidental art, was invented as a result of scarcity, circumstance, experimentation, or just fortunate error. That sort of imperfection is very hard to achieve with AI, because it is designed to be either perfect or fail.
Wait....but it just....did? It took the information about all possible burger recipes and invented a new one out of these. Like, a human could only invent a new burger if they knew anything about burgers in the first place, at the very least that it's a bun with some filling in between, otherwise you'd have no context to invent anything.
As in, the neural net in this example is able to improvise a new burger recipe solely because it was given existing recipes to burgers as input; it did not come up with the notion of a burger and then produce a recipe that outputs something fulfilling that notion when followed.
Personally, I would argue that this distinction is not as clear-cut as the tone of the original comment seems to suggest. Humans didn't invent the burger from nothing either. We've been grilling meat and making bread for millennia, and sandwiches have been a thing for over a century.
A 'burger' is just another iteration of our biological neural nets' attempts to make food from ingredients already present in our physical reality. Given that we flow in a single direction through time, any food we make is in turn added to our list of ingredients for making food "the next time". One could argue it is only a matter of time once meat can be ground into patties and grains turned into bread that burgers start being made - given the relative benefits humans gain from consuming both.
This comes back to what others have expressed elsewhere in this thread, that the probable [most] important distinctions aren't between software vs hardware, or organic life vs silicon processors, but the environment & capacity to interact with said environment. Some sense of "innate tendency to experiment" (i.e. curiosity) is probably either equal in importance or a direct runner-up.
To this day they serve their burgers between two bread slices - not buns.
If you want to look it up, it's called LOUIS’ LUNCH.
AI my ass :D
Of course, an AI intended to play go isn't going to invent the burger. But I see no reason why, given a list of ingredients, their properties and a model of what human enjoy eating, a neural network couldn't invent the burger.
Creating a new recipe is just an optimization problem at its core.
I also recently heard an argument for why our ANN models won’t spontaneously become sentient: human brains don’t learn from just observation, but also interaction. A young child doesn’t learn abouthow blocks are stacked by looking at images of stacked boxes, they learn through experimentation, by stacking boxes and seeinghow their actions affect the world around them. For an AI, that means we either need to also work on robotics so the AI can interact with its environment, not just sense it, or we need to simulate an interactive virtual environment. Some people are working on this and making great strides, but your average toy ANN won’t exhibit human intelligence in isolation, in my opinion.
Combine those two things and we’re still quite a ways away from human-like intelligence or implementing a human (or animal)-like brain.
[1] http://nautil.us/blog/just-imagining-a-workout-can-make-you-...
Or, put another way, its my belief that you can “_improve_ your physical skills” by thinking, but to buildthe skill in the first place, interaction is necessary.
But even if its not true and interaction isn’t strictly necessary, I think (wrongly oerhaps) that few people would disagree that usually learning by doing is far superior that only learning by thinking/reading/listening/watching. So even if not neccesary, its at least more efficient (doing both together is probably most efficient).