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Adversarial attacks are a bit more than just that : they reveal how much we don’t have any intuitive knowledge on what the algorithm understands. In the sense t
by bsaul 9y ago
Adversarial attacks are a bit more than just that : they reveal how much we don’t have any intuitive knowledge on what the algorithm understands. In the sense that we cannot build any intuition on what the 1% mistakes cognitive ML-based algorithms will be triggered by.
Aka : If a gun could be mistaken for an helicopter just by altering a few invisible pixels, then the behavior of that system is by definition not similar at all to « vision » in its common sense. And so if it’s not, then what is it ?
- hanbura 9y agoThey changed a lot of pixels in a way that led a human to classify the image as not notably changed but led one AI to classify it as a different type of object. Of course the same thing is possible with human and AI reversed, there are images that are obvious to some AI but that would be misclassified by humans. Humans do have the advantage that our vision system can draw on a huge repository of real-world knowledge and has been fed with decades of high resolution training data.
- ethbro 9y ago> Humans do have the advantage that our vision system can draw on a huge repository of real-world knowledge and has been fed with decades of high resolution training data. My impression was that ML image recognition systems have exactly the same to draw on, non?
- bsaul 9y agoHumans also have the advantage to understand what world they’re living in, and be capable of reasoning. The way you describe human cognition using ML terms makes me think you’re confusing the map with the territory.