LLMs and Problem Complexity
The complexity of tasks like multiplication poses significant challenges for LLMs, which must remember vast amounts of data to perform seemingly simple operations. As Jan explains, while LLMs can be fine-tuned for specific problems, they are not the ideal solution for the ARC challenge, which was designed for human problem-solving. Interestingly, the constraints of ARC align with the capabilities of LLMs, highlighting the delicate balance between task design and model performance.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Daniel Franzen & Jan Disselhoff - ARC Prize 2024 winners
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