Moving beyond content‐specific computation in artificial neural networks - Shea - 2023 - Mind & Language - Wiley Online Library
Funding information This research has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No. 681422 (MetCogCon). Give access Share full-text access Use the link below to share a full-text version of this article with your friends and colleagues. Learn more. Share a link A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human-like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content-specific and non-content-specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two takes advantage of the complementary costs and benefit