research-culture

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#research-culture

@gdb: OpenAI has built the muscle of making long-term research bets:

X AI KOLs Timeline · yesterday Cached

OpenAI has fostered a culture of supporting long-term research bets, such as full-duplex models like the GPT-live series, as highlighted by Kundan Kumar.

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#research-culture

The Fall of the Theorem Economy

Hacker News Top · 2026-07-02 Cached

David Bessis reflects on the nature of mathematical research, arguing that conceptual understanding is more valuable than the mere production of theorems, drawing from his own experiences in academia and a machine-learning startup.

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#research-culture

@46ge5: The most valuable indicator to judge the level of an AI Lab/group/department is not whether it has SOTA models or where the models rank, but the "fluff paper rate". SOTA models reflect momentary performance, while the fluff paper rate reveals the lab's culture, research taste, long-term goals, and values, and even a company's development (Meta AI is the most typical example, feeding too many water monsters like Tian Yuandong; when it came to cutting-edge LLM work, no one stepped up). That's why many underestimate Alexandr Wang; his replacing Yann and drastically cutting out those parasites is already a huge contribution.

X AI KOLs Timeline · 2026-06-03 Cached

The tweet points out that evaluating an AI lab should focus not just on SOTA models but on the "fluff paper rate", and comments on the culture issues within Meta AI and the contribution of Alexandr Wang replacing Yann.

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#research-culture

@yifan_zhang_: Jane Street is the GOAT As Rohan @_arohan_ mentioned, good researchers respect other people’s work. Quantitative resear…

X AI KOLs Timeline · 2026-05-08 Cached

The article highlights Jane Street's contribution to pushing the frontiers of Deep Learning through quantitative research, emphasizing the respect good researchers have for such work.

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#research-culture

Are we optimizing AI research for acceptance rather than lasting value? [D]

Reddit r/MachineLearning · 2026-04-20

A researcher critiques how AI conference acceptance culture prioritizes satisfying reviewers over producing work with lasting value, noting the expectation of extensive evaluations that are rarely verified by others.

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