A recent paper has caught my attention with its approach to solving a wide array of problems using something called a "regressor," powered by the advanced capabilities of Large Language Models (LLMs).
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This is significant because it shows that language models can outperform traditional regression models on multiple tasks if given the opportunity to train over diverse datasets.
At its core, the concept of a regressor might sound technical, but it's essentially a way to predict outcomes based on a set of inputs. Imagine trying to guess the final score of a basketball game based on past performances, or determining
