It is definitely true that progress towards AGI is being made, if we count the indirect progress of more money being thrown at the problem, and importantly perceptual challenges being solved means that there is now going to be a greater ROI for symbolic AI progress.
A world with lots of stuff that is just waiting for AGI-tech to be plugged into it is a world where more people will try hard to make that AGI-tech. Examples of ‘stuff’ would include robots, drones, smart cars, better compute hardward, corporate interest in the problem/money, highly refined perceptual algorithms that are fast and easy to use, lots of datasets, things like deepmind’s universe, etc.
A lot of stuff that was created from 1960 to 1990 helped to create the conditions for machine learning; the internet, Moore’s law, databases, operating system, open source software, a computer science education system etc.
It is definitely true that progress towards AGI is being made, if we count the indirect progress of more money being thrown at the problem, and importantly perceptual challenges being solved means that there is now going to be a greater ROI for symbolic AI progress.
A world with lots of stuff that is just waiting for AGI-tech to be plugged into it is a world where more people will try hard to make that AGI-tech. Examples of ‘stuff’ would include robots, drones, smart cars, better compute hardward, corporate interest in the problem/money, highly refined perceptual algorithms that are fast and easy to use, lots of datasets, things like deepmind’s universe, etc.
A lot of stuff that was created from 1960 to 1990 helped to create the conditions for machine learning; the internet, Moore’s law, databases, operating system, open source software, a computer science education system etc.