web02.fireside.fm Thu, 11 Jun 2026 08:38:52 -0500 Fireside (https://fireside.fm) The It's Innate! Podcast - Episodes Tagged with “Computational Modeling” https://itsinnate.fireside.fm/tags/computational%20modeling Wed, 20 May 2026 11:00:00 -0400 Two opinionated developmental cognitive scientists wax theoretical about how infants and children acquire knowledge! en-us episodic A podcast by two developmental cognitive scientists Deon Benton & Jenny Wang Two opinionated developmental cognitive scientists wax theoretical about how infants and children acquire knowledge! no cognitive development, developmental psychology, cognitive science, nature vs. nurture, psychology, social science, science Deon Benton & Jenny Wang theitsinnatepodcast@gmail.com Episode 39: Give-N you Bayes and Backpropagation (Pt. II) https://itsinnate.fireside.fm/39 932fb469-3f12-4fd9-b07b-47445af3d6ac Wed, 20 May 2026 11:00:00 -0400 Deon Benton & Jenny Wang full Deon Benton & Jenny Wang 2:03:56 no <p>We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.</p> <p><strong>Links</strong></p> <p>Lee, M. D., &amp; Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.<a href="https://www.sciencedirect.com/science/article/pii/S0010027710002283?casa_token=CIRzaM6HEdwAAAAA:k8kWVn9Y6td5T-JEwnPTcPt64Pgiw1rqtLV58BCvomCo51GP_36UAc6Wpy3kevkZvN1xiqvY" target="_blank" rel="nofollow noopener">Link</a> </p> number cognition, mechanism, computational modeling, connectionism, bayesian inference We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.

Links

Lee, M. D., & Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.Link

]]> We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.

Links

Lee, M. D., & Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.Link

]]> Episode 24: People and objects are different, and infants innately know this. Or do they? https://itsinnate.fireside.fm/24 6bc53802-e125-4d4e-8b4d-14f53ccdbb85 Sun, 19 Jan 2025 08:00:00 -0500 Deon Benton & Jenny Wang full Deon Benton & Jenny Wang 1:41:01 no <p>Deon and Jenny open this episode, which is a return their classic one-on-one format, by discussing the academic job market, imposter syndrome, and careful science. Following this brief discussion, Jenny and Deon discuss Deon's recent paper titled, "An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies." Deon talks about the motivation for writing this proposal as well as what his account is of how infants might begin to learn about how animates and inanimates differ from one another in terms of their causal abilities. It will come as no surprise that Deon thinks that this knowledge is acquired, and that Jenny is a bit skeptical (although, as you'lll hear, there are signs that she may see the merit in Deon's argument). At a broad level, this episode has it all — we cover philosophy, computational modeling, mechanisms, and developmental science!</p> <p><strong>Links</strong></p> <p>Benton, D. T. (2024). An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies. Journal of Experimental Psychology: General. <a href="https://psycnet.apa.org/record/2025-27513-001" target="_blank" rel="nofollow noopener">Link</a></p> associative learning, empiricism, nativism, mechanism, computational modeling Deon and Jenny open this episode, which is a return their classic one-on-one format, by discussing the academic job market, imposter syndrome, and careful science. Following this brief discussion, Jenny and Deon discuss Deon's recent paper titled, "An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies." Deon talks about the motivation for writing this proposal as well as what his account is of how infants might begin to learn about how animates and inanimates differ from one another in terms of their causal abilities. It will come as no surprise that Deon thinks that this knowledge is acquired, and that Jenny is a bit skeptical (although, as you'lll hear, there are signs that she may see the merit in Deon's argument). At a broad level, this episode has it all — we cover philosophy, computational modeling, mechanisms, and developmental science!

Links

Benton, D. T. (2024). An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies. Journal of Experimental Psychology: General. Link

]]> Deon and Jenny open this episode, which is a return their classic one-on-one format, by discussing the academic job market, imposter syndrome, and careful science. Following this brief discussion, Jenny and Deon discuss Deon's recent paper titled, "An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies." Deon talks about the motivation for writing this proposal as well as what his account is of how infants might begin to learn about how animates and inanimates differ from one another in terms of their causal abilities. It will come as no surprise that Deon thinks that this knowledge is acquired, and that Jenny is a bit skeptical (although, as you'lll hear, there are signs that she may see the merit in Deon's argument). At a broad level, this episode has it all — we cover philosophy, computational modeling, mechanisms, and developmental science!

Links

Benton, D. T. (2024). An associative-learning account of how infants learn about causal action in animates and inanimates: A critical reexamination of four classic studies. Journal of Experimental Psychology: General. Link

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