Former Google Researcher Says Architectural Choices Like Transformers No Longer Matter for Go

Zhang found that with modern hardware and proper initialization against existing strong models, many architectural innovations and training tricks developed for Go AI systems are now obsolete. His experiments showed ResNets and Transformers perform comparably, and complex distributed training infrastructure can be replaced with simpler synchronous approaches. This validates aspects of the 'bitter lesson' that raw compute and scale matter more than algorithmic sophistication, though Zhang notes initialization strategy remains critical.