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Sebastian Ruder GitHub
semi-supervised — Pseudo-code in LaTeX for common proxy-label approaches for semi-supervised learning
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19 September
18 September
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korrents.com
Japan is not usefully described as a Confucian society; the label is applied as a lazy racial category.Their words
In other words, “Confucian” is lazily applied to Japan as a racial category, rather than any kind of a useful description of the culture and society.
12 September
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Their words
This is the first time a debate over whether a model ‘was AGI’ felt non-silly. I do not think it is AGI, and I would warn against the dangers of using that label prematurely, but I would not laugh at you for disagreeing.
4 September
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1 January
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Their words
there's also a flip side to this or a dark side, a shadow side to identity, which is the tighter you cling to an identity, the harder it becomes to grow beyond it. And so once you have started to identify as a certain type of person, once you adopt that label, oh, I am a member of this group or I am the type of person who believes this thing, it becomes hard to stretch and grow outside of that.
23 November 2025
26 September 2025
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Their words
squirrels don't go to school. Squirrels can learn all about the world. It's absolutely obvious I would say that um supervised learning doesn't happen in animals.
17 September 2024
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korrents.com
Corporations dishonestly claiming the open source label for marketing is evidence that open source has won.Their words
When corporations disingenuously claim to be “open source” for marketing purposes, it’s a clear sign that Open Source is winning.
7 July 2024
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korrents.com
Using supervised fine-tuning to teach a language model new knowledge risks increasing its hallucination rate.Their words
These empirical results from Gekhman et al. (2024) point out the risk of using supervised fine-tuning for updating LLMs' knowledge.
25 May 2024
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Their words
For the most part, it’s like these names are just utterly arbitrary, so you have no thing to latch on to. It’s not really a thing that our brain does very well to learn meaningless, arbitrary stuff. So what you need to do is build connections somehow, visualize a connection, and sometimes it’s obvious or sometimes it’s not.
16 January 2024
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Recommendsrcmnd.app
SupervisedTheir words
Longtime tech reporter Matt Lynley offers an uncommonly technical assessment of new AI developments in his newsletter Supervised. Original reporting and a fast cadence help this one stand out from other AI newsletters.
21 April 2022
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Mixed onrcmnd.app
BreathTheir words
Anyway, the book has compelling parts, but hurts its own arguments with sloppy pseudo-science.
20 February 2022
5 December 2021
26 July 2019
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Their words
Human error is blamed for over 90 percent of industrial and automobile accidents. It is the leading cause of aviation accidents, and medical error is reported to be the third-largest cause of death in the entire United States. Horrifying? Yes, but why do we label it “human error”? It is design error.
1 January 2017
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Readrcmnd.app
Bad ScienceTheir words
Examples of good science, pseudo-scientific bullshit, and how to discern between the two.
30 August 2016
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