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Program Aided Language Models

Data Skeptic

CHAPTER

Choosing Python and the Trend of End-to-End in Machine Learning

Why Python was chosen as the language for the project and its advantages in pre-training copies of codecs and overall performance in codecs. Discussion on the trend of end-to-end machine learning and the benefits of offloading calculations to the Python interpreter, depending on task complexity. Limitations of language models and the importance of real-world signals.

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