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Simplifying ML Tooling and Embracing Change
Simplifying ML tooling to cater to a wider audience and promote user-friendly solutions, such as avoiding complex systems like Git for versioning data. Additionally, the company is focused on making clear and simple tools that genuinely benefit users. The company also recognized a shift in ML tasks, realizing that some tasks could be simplified by directly querying the language models instead of training separate models. Despite the bittersweet feeling, they adapt to this change and aim to stay flexible in the rapidly evolving field of machine learning.