Finally, an editorial in Science that isn't just hedging its bets and trying to play nice. This is a long overdue piece.
https://www.science.org/content/blog-post/assault-science-funding-continues
The US government is out to destroy US (and possibly global) science and they do not know nor care about how to fix it. You do not play nice with these kinds of people. You root them out before they destroy the thing you love
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James Hawley, PhD
@jrhawley@scholar.social
I use math and computers to study cancer biology.
Senior Data Scientist at Roche. PhD in computational biology and cancer epigenetics from the Department of Medical Biophysics at the University of Toronto.
This is my scientific account. Views are my own.
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Open post
Replying to
@gedankenstuecke@scholar.social I feel like for a lot of the people complaining about Codeberg, it's one of the first times that someone they respect has told them "no, go away". And they *do not* like it or know how to respond
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If anyone has any doubts that the #AI industry is all about dismantling labour rights, let's consider this:
https://www.engadget.com/2225849/google-shuts-down-alphafold/
Google shuts down the #AlphaFold project. One of the most impactful machine learning projects in the sciences is being dismantled despite its immense value.
Why?
The article doesn't mention it, but it's almost certainly because DeepMind was trying to form a union to protect their rights and oppose Google's military contracts.
https://www.wired.com/story/google-deepmind-unionization-talks-are-off-to-a-rocky-start/
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I recently discovered @betanalpha@fediscience.org 's writing on the foundations of probability theory, and they're very very good:
https://betanalpha.github.io/writing/
I understand all this algebra and analysis is too heavy for most undergrads. But it does give the topic the serious treatment it deserves (topology, Hausdorff spaces, measure theory, conditional distributions over partitions) while still providing enough background to understand it.
I highly recommend it!
#bayesian #statistics
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I recently attended a presentation by people from Anthropic at work about their large language models. One undercurrent in the presentation was that thinking is hard - wouldn't it be nice if it was easier? I'm sorry to say, but that's your job.
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