I think its mainly a software/use case problem as opposed to an architectural problem.
Right now AI systems are built top to bottom to learn in development, and be deployed as a static asset. This isn't because online learning isn't doable, its because there isn't a great use case for current limitations. Either the algorithms are too slow, or computers are too slow, take your pick.
Chain of Thought is basically a more constrained version of in situ learning, only the knowledge has a lifetime bound to the task. Propagating the information into the model would be too resource hungry, and too unpredictable to productize. Honestly, taking the result of Chain of thought, and feeding that back into training offline is probably where a lot of the progress on these kinds of tasks is coming from.
Right now AI systems are built top to bottom to learn in development, and be deployed as a static asset. This isn't because online learning isn't doable, its because there isn't a great use case for current limitations. Either the algorithms are too slow, or computers are too slow, take your pick.
Chain of Thought is basically a more constrained version of in situ learning, only the knowledge has a lifetime bound to the task. Propagating the information into the model would be too resource hungry, and too unpredictable to productize. Honestly, taking the result of Chain of thought, and feeding that back into training offline is probably where a lot of the progress on these kinds of tasks is coming from.