We are living a grand illusion. As we watch Large Language Models (LLMs) draft essays, write functional code, and converse with poetic nuance, we operate under a quiet, dangerous assumption: that if we just stack enough parameters, compute cycles, and training text high enough, true understanding and intent will eventually spark at the top.

It wonโ€™t.

https://ocrampal.com/the-quest-for-an-impossible-theory-why-computation-cant-solve-meaning-and-what-it-means-for-llms/

#programming #AI #intelligence #cogsci #philpsy #neurosky #philosophy

Why Computation Can't Solve Meaning (And What It Means for LLMs): the Quest for an (Im)possible Theory

We are living a grand illusion. As we watch Large Language Models (LLMs) draft essays, write functional code, and converse with poetic nuance, we operate under a quiet, dangerous assumption: that if we just stack enough parameters, compute cycles, and training text high enough, true understanding and intent will eventually

ocrampal`s place
I'm at #Duke to share methods and results from Socratic Reflection experiments to the Advances in Decision Analysis #conference:

#2026ADA website: https://conferences.fuqua.duke.edu/2026-informs-advances-in-decision-analysis-conference

Follow the URL below for our results and my posts about other talks or posters I see.

#cogSci #xPhi #AI

I'm at #Duke to share methods and results from Socratic Reflection experiments to the Advances in Decision Analysis #conference:

#2026ADA website: https://conferences.fuqua.duke.edu/2026-informs-advances-in-decision-analysis-conference

Follow the URL below for our results and my posts about other talks or posters I see.

#cogSci #xPhi #AI

Do students actually learn better from mistakes? A new study suggests: not always. Searching for errors didn't improve learning, but it did increase time and cognitive load. Here's what that means for teaching.
#education #learning #cogsci #teaching
https://theeconomyofmeaning.com/2026/06/18/do-we-actually-learn-better-from-mistakes/
Do We Actually Learn Better From Mistakes?

Do students learn better from mistakes? New research shows when errors helpโ€”and when correct worked examples are the better choice.

From experience to meaning...

Can 3-6 year-olds distinguish between reliable vs. unreliable informants?

A study of 93 #kids found the children were sensitive to source reliability, with limited abilities to generalize across contexts.

https://doi.org/10.1016/j.jecp.2026.106547

#devPsych #cogSci #epistemology #xPhi #parenting

This notebook explores "epistemic curvature" and homotopy-theoretic #activeinference using a REAL WORLD example.

The example is very simple, but there are plans to extend it to large-scale social networks in the future.

#Science #cogsci #math

https://colab.research.google.com/drive/16tUQiybglvn2RfzKuu_0uoI_drPQIRYS?usp=sharing

Google Colab

Why canโ€™t the tech world agree on whether AI actually "reasons"?

It turns out, the answer is hidden in how we talk about feeling cold.

https://www.ocrampal.com/i-am-vs-i-have-how-everyday-grammar-secretly-influences-the-ai-debate/

#programming #AI #intelligence #cogsci #philpsy #neurosky #philosophy

"I Am" vs. "I Have": How Everyday Grammar Secretly Influences the AI Debate

When you say "I am cold," you aren't just describing your temperature. You are picking a side in a centuries-old philosophical war, one that perfectly explains why the tech world is currently tearing itself apart over whether AI can truly "reason." There is a curious linguistic asymmetry hiding in plain

ocrampal`s place
Very excited for this week of events! ๐Ÿงช๐Ÿง  #cogsci #neuro

RE: https://bsky.app/profile/did:plc:vcxh6n4wf255576clqdp6bf6/post/3mnflzqp5ek2m

Do logical visual aids (such as Venn diagrams) improve argument evaluation?

Not in this study of 164 English speakers (with "normal or corrected-to-normal vision and no issues seeing color").

https://doi.org/10.1111/cgf.70476

#logic #teaching #edu #visualization #CogSci #learningScience

CSCI 1377: Tools for Thought (Spring 2026)

https://fed.brid.gy/r/https://cel.cs.brown.edu/csci-1377-s26/