Are Modern ML PhDs Becoming Too Incremental? r/MachineLearning Debates Research Quality at 101 Upvotes

r/MachineLearning·medium signal

A r/MachineLearning discussion (101↑, 32 comments) asks whether modern ML PhD research is becoming too incremental — minor benchmark improvements over existing methods rather than novel contributions. Respondents cite pressure to publish, benchmark gaming, and the difficulty of competing with well-funded industry labs as driving factors. The thread surfaces a structural concern: as frontier models become corporate products, academic ML research risks becoming a benchmark-chasing exercise rather than a source of genuine innovation.