IMO that kind of thinking flips correlation/causation, and feels like some sort salience bias towards voluminous but crappy work. Yes, you can do it, just goo

IMO that kind of thinking flips correlation/causation, and feels like some sort salience bias towards voluminous but crappy work. Yes, you can do it, just good bye impact. Worse, it's a self-fulfilling prophecy: by moving your work to be more incremental, you're even more at risk by the incremental advances of others. The field exploded, so yes, there are way more good and even more bad papers, so some researchers interpret that as the need to publish a lot. Top labs attract a lot of students and funding, so the PI spends little time per student, and instead farms out to post docs who are there for only a few years, and in turn they do most of the phd student mentoring. And many folks want to bean count neurips papers. The result is yes, if you're unintentional about impact, and get distracted by the volume, you too can optimize for that, do lets of incremental work, ultimately you've learned some skills and wrote papers that won't matter. Google/FB/OpenAI/Spotify/LinkedIn/etc will still hire you at the end, that's fine, they hire a ton of phds. Objectively, there are some real jumps happening, but zoomed out, very few of the papers coming out in a given year change all that much. E.g., we're using LLMs for some hard societal problems (misinfo, cyber, ...), but nothing fundamental changed in our startup's work since gpt-4 came out, and all versions before gpt-4 weren't significant enough to motivate using generative LLM methods. There are a few methods we're tracking (e.g., graph RAG, certain kinds of agents), but most work is embarrassingly shallow or bad, so the incremental papers have done almost nothing to influence us, and we learn more from other industry folks doing more ambitious or real work here. The previous disruption on our AI side was around GNNs, but that was over many years and quite rocky. So if we were doing all this as a serious PhD project (invention) instead of as a startup (innovation), I'd expect similarly low levels of disruption from the perceived fast pace of others.