The argument by Burkart et al. in the target article relates to fluid (not general) intelligence: a domain-general ability involved in complex, novel problem solving, and strongly related to working memory and executive functions. A formative framework, under which the general factor of intelligence is the common consequence, not the common cause of the covariance among tests is more in line with an evolutionary approach.

We question the free energy principle (FEP) as it is used in contemporary physics. If the FEP is incorrect in physics, then it cannot ground the authors' arguments. We also question the assumption that perception requires inference. We argue that perception (including perception of social affordances) can be direct, in which case inference is not required.

The Kalman filtering technique is considered as a part of concurrent data-processing techniques also related to detection, parameter evaluation, and identification. The adaptive properties of the filter are discussed as being related to symmetrical brain structures.

steels & belpaeme's (s&b's) simulations contain all the right components, but they are put together wrongly. color categories are unrepresentative of categories in general and language is not merely naming. language evolved because it provided a powerful new way to acquire categories (through instruction, rather than just the old way of other species, through trial-and-error experience). it did not evolve so that multiple agents looking at the same objects could let one another know which of the objects they had in mind, co-coining names for them on the fly.

Structural priming is a useful tool for investigating linguistics representations. We argue that structural priming can be extended to the investigation of pragmatic representations such as Gricean enrichments. That is not to say priming is without its limitations, however. Interpreting a failure to observe priming may not be as simple as Branigan & Pickering (B&P) imply.

The model of phoneme monitoring proposed by Norris et al. is implausible when implemented in a localist connectionist network. Lexical representations mysteriously inform phoneme decision nodes as to the presence or absence of a target phoneme.

Bruineberg and colleagues helpfully distinguish between instrumental and ontological interpretations of Markov blankets, exposing the dangers of using the former to make claims about the latter. However, proposing a sharp distinction neglects the value of recognising a continuum spanning from instrumental to ontological. This value extends to the related distinction between “being” and “having” a model.

Despite its strengths, Leech et al.'s model fails to address the important benefits that derive from self-explanation and task feedback in analogical reasoning development. These components encourage explicit, self-reflective processes that do not necessarily link to knowledge accretion. We wonder, therefore, what mechanisms can be included within a connectionist framework to model self-reflective involvement and its beneficial consequences.