I agree with Roose’s point in “How Schools Can Survive (and Maybe Even Thrive) With A.I. This Fall”, that generative AI should instead be understood and not banned in classrooms. I think that for many people, especially those who are not experienced in working with AI or do not know much about how models like […]

Some aspects of Andrew Abbott’s critique resonate with me. For instance, he points out that some students only read the highlighted portions of the text, bypassing the development of a logical argument that comes with reading the entire passage. Having attended his class for two weeks, I confess to being one of those students who […]

Dr. Chomsky’s argument against LLMs primarily focuses on how despite the perceived intelligence of a model, any given is unable to process information the way humans can, which, in his opinion, poses a limit on LLMs. I agree that the way LLMs are constructed limit their ability to imitate humans, however I think Chomsky is […]

Chomsky’s counterargument, in my view, lacks clarity. He contends that “The essence of machine learning is about description and prediction; it doesn’t delve into causal mechanisms or physical laws.” Yet, when we prompt advanced models like GPT 3.5 or GPT 4 with questions such as why apples fall, they can provide explanations that touch on […]

To read Ouyang (2022)’s paper, I tried ChatGPT’s PDF plugin to assist reading the paper, and it seems to work well. In this response I will bring up two points, one for my own reaction to the paper and another on the attempt to use ChatGPT assistance. I find the notion of “alignment” very interesting […]

These readings inform me of the history of the development of cognitive science, in particular, how certain concepts that I take for granted (mechanism, machine, computation, information, symbol, etc.) came onto the main stage. There are two main thoughts I had as I read through this history: I noticed a distinctive approach to the Mind-Body […]