![変更容易性と理解容易性を支える自動テスト(2024/02版) / Automated Test Knowledge from Savanna 202402 YAPC::Hiroshima edition](https://cdn-ak-scissors.b.st-hatena.com/image/square/b14c3c9aeb2716d80432a3b55084b172303aceca/height=288;version=1;width=512/https%3A%2F%2Ffiles.speakerdeck.com%2Fpresentations%2Fa87e76a8d71f450f93fa5c326409e4b5%2Fslide_0.jpg%3F28899481)
Recent developments in foundation models, like Large Language Models (LLMs) and Vision-Language Models (VLMs), trained on extensive data, facilitate flexible application across different tasks and modalities. Their impact spans various fields, including healthcare, education, and robotics. This paper provides an overview of the practical application of foundation models in real-world robotics, wit
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