Jordan Bardella revient sur la promesse du RN d’abroger la réforme des retraites s’il parvient au pouvoir
https://www.lemonde.fr/politique/article/2…
Republican Voters Against Trump on X: "Cavuto: “You said that [Trump] is a populist, and an authoritarian narcissist. That character is too important to me and it's a job that requires the kind of character he just doesn't have. That's pretty strong.” Paul Ryan: “Yeah. That's the way I feel. I agree with that.” https://t.co/l3M…
#Språkrådet har fått nye nettsider https://sprakradet.no/aktuelt/nytt-kjoremonster-pa-sprakradet-no/
Disse er ser ut til å være laget i WordP…
Rheinmetall, Kyiv agree to start producing Lynx armored vehicles in Ukraine in 2024: https://benborges.xyz/2024/06/12/rheinmetall-kyiv-agree.html
QUOTE OF THE DAY
“Learn the rules like a pro, so you can break them like an artist.”
— Pablo Picasso
Agree, disagree — be inspired or not.
QOTD is fuel for conversation, and food for thought.
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#QuoteOfTheDay
This cloud architecture is fascinating.
1. Secure the hardware supply chain.
2. Rely on secure boot and the trust cache to assure loaded software.
3. Remove code that provide access in and out of the runtime.
4. Rely on per-boot on-disk encryption keys to secure data on Flash.
5. Generate per-node public/private key pairs for data exchange with client.
6. Rely on Secure Enclave to hide private keys from runtime.
7. Rely on 3rd party load balancers to batch…
Subtoot 'cause the post I saw had enough replies already, but this is a bad article (though it has a wonderful description of how Von Neumann machines work):
https://aeon.co/essays/your-brain-does-not-process-information-and-it-is-not-a-computer
For context, I'm against most uses of modern LLMs for several good ethical reasons, and I think the current state of AI research funding is both unsustainable and harmful to knowledge development. However, I've done a tiny bit of deep learning research myself, and I think the tech has a lot of cool potential, even if on balance it might have even more terrifying-potential.
The central problem with this article is that while it accurately describes ways that most human brains differ fundamentally from one way computers can be set up, it completely ignores how (computer) neutral networks work, including the fact that they'd perform very similar to the humans on the dollar bill task, because they encode a representation of their training inputs as distributed tweaks to the connection weights of many simulated neurons. (Also, people with photographic memory do exist...)
I think that being challenged in one's metaphors is a great idea (read Paul Agre on AI) and this is a useful article to have read for that reason, but I think the more useful stance is a principled agnosticism towards whether the human brain works like a computer, along with a broader imagination for "what a computer works like." More specifically, I'm quite convinced the brain doesn't work like a modern operating system (effectively the central straw man in this article), but I reserve judgement on whether it works like a neutral network.