- Mar 2019
Same-different problems strain convolutional neural networks
Wow, this is fascinating. I wonder if SD problems could be the next major roadblock for AGI...
- Feb 2019
- May 2015
like this sketch
I like the graph. I have to follow the roots of this unlearning literature. Feeling a legacy of Piaget in this sense of "crisis" or "discomfort" that is required for deep learning.
I know I throw things when writing, yet there is also a sense of elation and drive.
I find the or strange. I wonder if It should be and. Many students put in time without effort and get no where.
I also think you can reach understanding instantaneously (though I think Sam refers to more designed learning than natural learning). I think about Kristeva and the abject. It isn't so much unlearning but a reversion.
My dabbling in this makes me wonder if we would need tools in the chart or the activity...wait we would be stuck with Engstrom's triangles again.
know more at precisely the same moment that you understand less.
Or is this a recognition that you have so much more to learn? Is understanding from this framework nothing more than the motivation from greater knowledge?
while not yet being able to meaningfully connect it to things you already know.
This puts deep learning in the hands of the individual I am beginning to wonder if understanding is something that belongs to the collective. It is too subjective in the individual.
The inability to connect a new piece of information with the world as we already know it--this is a classic problem of the unlearning that is required for deeper learning
It could be just not encountering enough variations across multiple case studies.
I also see many parallels to the idea of what we are calling synthesis here.
knowledge while losing understanding
I agree with this statement but I do not by into the science of unlearning. You are not "unlearning" when your perceptions shift. It is a movement or trajectory.
I need to explore this more but the field of research in misconceptions is much stronger in the hard sciences. I am not too comfortable with it, but ill-defined and well-defined domains do behave differently. Oops I just anthropomorphized knowledge. Mistake?
To me the idea that of starting with the learner is wrong is wrong. Deeper learning does not have to begin from here.