Merely scaling up a GAN and optimizing it's network structure and training procedure allowed GANs to create nearly realistic high resolution faces. If you can generate realistic faces, then you can likely also generate realistic action and thought sequences simply with an even larger model.
An action/thought sequence is just a 4D tensor with some outputs controlling actuators. Thinking is just production of actions while actuator output neurons are inhibited, which can simply be implemented by a product with some sigmoid activated neurons.
Coherent combinations of such sequences can be produced by feeding both the current sensory inputs and the preceding internal state as conditioning vector to both the generator and discriminator.
You simply need to find a way to train the discriminator not only to tell real from fake, but to determine the value of the generator's outputs and make it backpropagate those values in time during training over several generated episodes by TD.
As the GAN is conditioned on its own previous state, it can learn by trial and error how to combine the short action and thought sequences it produces, can thus learn to produce coherent ("real") language and logic.
Based on such intuitions, I'd say it is impossible to tell when AGI will come exactly, but currently technology looks damn promising.
Just checked my feed of recommended videos and it is still full of Tetris and excavator videos that I was into lately. It would be awesome to be surprised with some extraordinary lectures or documentaries similar to stuff I watched 5 years ago, or so.
How about employing 10 people of this massive platform to curate some channels that people can easily subscribe to? It could literally be advertised to be kids-friendly and not dumb etc.
An action/thought sequence is just a 4D tensor with some outputs controlling actuators. Thinking is just production of actions while actuator output neurons are inhibited, which can simply be implemented by a product with some sigmoid activated neurons.
Coherent combinations of such sequences can be produced by feeding both the current sensory inputs and the preceding internal state as conditioning vector to both the generator and discriminator.
You simply need to find a way to train the discriminator not only to tell real from fake, but to determine the value of the generator's outputs and make it backpropagate those values in time during training over several generated episodes by TD.
As the GAN is conditioned on its own previous state, it can learn by trial and error how to combine the short action and thought sequences it produces, can thus learn to produce coherent ("real") language and logic.
Based on such intuitions, I'd say it is impossible to tell when AGI will come exactly, but currently technology looks damn promising.