Discussion thread for "Foundational must read GPT/LLM papers"

I thought this article was very interesting:

Research abstract explained by GPT-4:

Researchers have created a new kind of recurrent neural network (a type of artificial intelligence model) that operates continuously over time. Instead of using typical methods to define how these networks change and learn, they built them using a combination of simple linear systems and nonlinear gates. The special thing about these networks is that their behavior changes fluidly over time. When they run these networks, they use mathematical methods to calculate the results. These new neural networks show stable behavior, can represent complex patterns better than other similar networks, and are better at predicting sequences of data. The researchers have used both theory and practical tests to show that these “Liquid Time-Constant Networks” (or LTCs) perform better than other common types of neural networks, especially when predicting sequences.

In my opinion, this research offers immense potential for physical systems like walking robots and self-driving cars, but I doubt it will outcompete large language models when it comes to predicting text sequences.

Thoughts?

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