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In their Comment, Dennler et al.1 submit that they have discovered limitations affecting some of the conclusions drawn in our 2020 paper, ‘Rapid online learning and robust recall in a neuromorphic olfactory circuit’2. Specifically, they assert (1) that the public dataset we used suffers from sensor drift and a non-randomized measurement protocol, (2) that our neuromorphic external plexiform layer (EPL) network is limited in its ability to generalize over repeated presentations of an odourant, and (3) that our EPL network results can be performance matched by using a more computationally efficient distance measure. Although they are correct in their description of the limitations of that public dataset3, they do not acknowledge in their first two assertions how our utilization of those data sidestepped these limitations. Their third claim arises from flaws in the method used to generate their distance measure. We respond below to each of these three claims in turn.