A Very Brief and Critical Discussion on AutoML
This is an incremental discussion critiquing AutoML's current state and challenges for researchers and practitioners.
The paper categorizes AutoML into narrow and generalized types, concluding that most research is narrow, driven by commercial needs with increased computing costs, and generalized AutoML faces significant obstacles tied to AGI.
This contribution presents a very brief and critical discussion on automated machine learning (AutoML), which is categorized here into two classes, referred to as narrow AutoML and generalized AutoML, respectively. The conclusions yielded from this discussion can be summarized as follows: (1) most existent research on AutoML belongs to the class of narrow AutoML; (2) advances in narrow AutoML are mainly motivated by commercial needs, while any possible benefit obtained is definitely at a cost of increase in computing burdens; (3)the concept of generalized AutoML has a strong tie in spirit with artificial general intelligence (AGI), also called "strong AI", for which obstacles abound for obtaining pivotal progresses.