以往只支持NLP、圖像分類等等單一領域模型搜索的AutoML算法，現在被整合到了一個平臺上，可以構建任何AI模型，無需再重新設計參數、或反覆微調，「AI設計師」就能幫你寫出想要的模型。
目的是讓AI來設計神經網絡，自動對網絡深度、層類型、結構、優化算法等因素進行合理搭配，效果通常比人工直接設計更好。
Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).
The library enables you to:
Run many AutoML algorithms out of the box on your data - including automatically searching for the right model architecture, the right ensemble of models and the best distilled models.
Compare many different models that are found during the search.
Create you own search space to customize the types of layers in your neural networks.
參考連結：https://cloud.google.com/automl-tables
github連結：https://github.com/google/model_search
資訊詳見：https://bangqu.com/HC4P93.html