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Working out milestone tasks that we expect to be achieved before we reach AGI can be difficult. Some tasks, like "continuous learning" intuitively seem like they will need to be solved before someone builds AGI. Continuous learning is learning bit by bit, as you get more data. Current ML systems usually don't do this, instead learning everything at once from a big dataset. Because humans can do continuous learning, it seems like it might be required for AGI. However, you have to be careful with reasoning like this, because it is possible the first generally capable artificial intelligence will work quite differently to a human. It's possible the first AGI will be designed to avoid needing "continuous learning", maybe by being designed to do a big retraining process every day. This might still allow it to be as capable as humans at almost every task, but without solving the "continuous learning" problem.
Because of arguments like the above, it's not always clear whether a given task is "required" for AGI.
Some potential big milestone tasks might be:
This metaculus question has four very specific milestones that it considers to be requirements for "weak AGI".