Exciting Paper

Response to “Can you describe a paper you’re excited about and say why it’s exciting?”

“Adversarial Examples Are Not Bugs, They Are Features” fascinates me because it reveals how neural networks exploit predictive patterns in what humans perceive as meaningless noise, suggesting fundamental limitations in our evolved perception that AI systems aren’t constrained by. Though it’s more of a nerdy curiosity than research I’d actively pursue, this paper points to something profound about the nature of information itself rather than just quirks of specific architectures. It connects beautifully with the more recent Platonic Representation Hypothesis, as both works suggest that learning systems might converge toward universal information-rich representations that transcend human intuition. I’m drawn to how these ideas challenge our understanding of intelligence and hint at AI capabilities that could develop by accessing and synthesizing information streams beyond our perceptual limitations.

A related post of mine: https://gatlen.blog/philosophy/heuristic-beings