▽はてなｱﾝﾃﾅ - umedamochioのｱﾝﾃﾅ
●12/23 07:47
2024/12/23 07:34:06 Technology News - Tech News2024/12/23 07:29:07 Forbes.com - Forbes Magazine Table Of Contents2024/12/23 07:08:44 Wired News2024/12/23 06:48:31 Silicon Valley2024/12/23 06:39:16 Read/Write Web2024/12/23 06:39:01 John Battelle’s Searchblog2024/12/23 05:57:11 Policy: public policy, networks, intellectual property. Connected - Corante2024/12/23 05:56:21 Forbes.com - Columnis

▽Burr Settles
●12/23 07:15
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▽Statistical modeling, causal inference, and social science: Blog of Andrew Gelman’s research group, featuring Bayesian statistics, multilevel modeling, causal inference, political science, decision theory, public health, sociology, economics, and litera
●12/23 04:26
Stanford medical school professor misrepresents what I wrote (but I kind of understand where he’s coming from)Posted on December 22, 2024 12:59 PM by Andrew2This story is kinda complicated. It’s simple, but it’s complicated.The simple part is the basic story, which goes something like this:– In 2020, a study was done at Stanford–a survey of covid exposure–that I publicly criticized: I wrote

▽榮倉奈々ｵﾌｨｼｬﾙｻｲﾄ
●12/22 16:32
2024.12.20【ﾚﾎﾟｰﾄ】榮倉奈々『ｲﾝｽﾀﾝﾄん♪CAF〓 by AGF』ｵｰﾌﾟﾆﾝｸﾞｲﾍﾞﾝﾄ

▽Google Research Scientists and Engineers: Jeffrey Dean
●12/22 15:07
Emergent abilities of large language modelsBarret ZophColin RaffelDale SchuurmansDani YogatamaDenny ZhouDon MetzlerEd H. ChiJason WeiLiam B. FedusMaarten Paul BosmaOriol VinyalsPercy LiangSebastian BorgeaudTatsunori B. HashimotoYi TayTMLR (2022)Preview Preview abstract Scaling up language models has been shown to predictably confer a range of benefits such as improved performance