(a) AI on both the "red" and "blue" teams is useful. Blue team is basically brain storming.
(b) AlphaEvolve is an example of an explicit "red/blue team" approach in his sense, although they don't use those terms [0]. Tao was an advisor to that paper.
(c) This is also reminiscent of the "verifier/falsifier" division of labor in game semantics. This may be the way he's actually thinking about it, since he has previously said publicly that he thinks in these terms [0]. The "blue/red" wording may be adapting it for an audience of programmers.
(d) Nitpicking: a security system is not only as strong as its weakest link. This depends on whether there are layers of security or if the elements are in parallel. A corridor consisting of strong doors and weak doors (in series) is as strong as the strongest door. A fraud detection algorithm made by aggregating weak classifiers is often much better than the weakest classifier.
(a) AI on both the "red" and "blue" teams is useful. Blue team is basically brain storming.
(b) AlphaEvolve is an example of an explicit "red/blue team" approach in his sense, although they don't use those terms [0]. Tao was an advisor to that paper.
(c) This is also reminiscent of the "verifier/falsifier" division of labor in game semantics. This may be the way he's actually thinking about it, since he has previously said publicly that he thinks in these terms [0]. The "blue/red" wording may be adapting it for an audience of programmers.
(d) Nitpicking: a security system is not only as strong as its weakest link. This depends on whether there are layers of security or if the elements are in parallel. A corridor consisting of strong doors and weak doors (in series) is as strong as the strongest door. A fraud detection algorithm made by aggregating weak classifiers is often much better than the weakest classifier.
[0] https://storage.googleapis.com/deepmind-media/DeepMind.com/B...
[1] https://mathoverflow.net/questions/38639/thinking-and-explai...