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AI is more than GenAI
Practical AI: Machine Learning, Data Science, LLM
Boosting Model Generalizability
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Enhancing model generalizability involves understanding effective feature representation and leveraging vast amounts of data for training. By utilizing unsupervised methods, massive datasets, including images, videos, and textual content scraped from the internet, can be employed to create training tasks without manual curation. This new approach automates the development of tasks such as autocomplete or word masking, allowing models to learn from examples generated programmatically. Such techniques aim to improve the adaptability of large foundation models for various downstream tasks through fine-tuning, ultimately expanding their applicability across diverse scenarios.
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