Ah, I misread. So we agree then. On the other hand, I would not be surprised if the hippocampus was highly developed in chess players like Bobby Fischer which could translate into better spatial reasoning. Perhaps general intelligence is best trained by variance.... Not targeted training.
You could be right, and for the record I upvoted your comment for the contribution regarding you experience with high level chess players. I think the downvotes you’re getting are regrettable.
I appreciate your sentiment. This field is my focus right now. My bachelors is in BioChemMed but I am doing a master in CS and have finished many courses including the free ones by Hinton, LeCun, and Bengio.
Here is my strongest prediction:
AGI is only possible if the AGI is allowed to cause changes to its inputs.
Current ML needs to be grafted towards attention mechanisms and more boltzmann net / finite/infinite impulse response nets.
Both. Attention changes the source. Action interacts with the source, modifying it. But the environment will need to respond back. This is reminiscent of reinforcement training but is more traditional NN except where the input is dynamic and evolving with every batch not only in response to the agent but in response to differential equations or cellukar automata / some type of environment evolution. AGI should be able to change the environment in which it inhabits. Attention in some respects is a start - it is essentially equivalent to telling reality to move the page and watching it happen. Until we have attention AND data modification, we will keep getting the specialized NN we are used to.
