Learning is very difficult
Libretech Systems - DARKLEAF
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npub16d8g...4rzv
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☆.𓋼𓍊 𓆏 𓍊𓋼𓍊.☆
⠀⠀⠀⠀⣿⡇⠀⢸⣿⡇⠀⠀⠀⠀
⠸⠿⣿⣿⣿⡿⠿⠿⣿⣿⣿⣶⣄⠀
⠀⠀⢸⣿⣿⡇⠀⠀⠀⠈⣿⣿⣿⠀
⠀⠀⢸⣿⣿⡇⠀⠀⢀⣠⣿⣿⠟⠀
⠀⠀⢸⣿⣿⡿⠿⠿⠿⣿⣿⣥⣄⠀
⠀⠀⢸⣿⣿⡇⠀⠀⠀⠀⢻⣿⣿⣧
⠀⠀⢸⣿⣿⡇⠀⠀⠀⠀⣼⣿⣿⣿
⢰⣶⣿⣿⣿⣷⣶⣶⣾⣿⣿⠿⠛⠁
⠀⠀⠀⠀⣿⡇⠀⢸⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
There is no great content. Only words that become thoughts
Coding with a rubber duck might yield better results than with advanced AI
Holding a strong opinion is of no use if you don’t constantly question it with your own writing
We are one misunderstanding away from total annihilation
Death of agricultures, and frozen land
Man went underground
Winter
That we would launch weapons on our forms of life
In the mechanism of the universe , damnation is tied to celestial machines
Deep shadow self of fear
The Last Scan
The Last Scan
Been working on this story for a month now
Satisfied with this version of it
The Chrononaut's Loop
Bold love
Echoes
Human-AI Collaboration with Misaligned Preferences
Jiaxin Song, Parnian Shahkar, Kate Donahue, Bhaskar Ray Chaudhury
Citation - arXiv:2511.02746 [cs.GT]
In many real-life settings, algorithms play the role of assistants, while humans ultimately make the final decision. Often, algorithms specifically act as curators, narrowing down a wide range of options into a smaller subset that the human picks between: consider content recommendation or chatbot responses to questions with multiple valid answers.
Crucially, humans may not know their own preferences perfectly either, but instead may only have access to a noisy sampling over preferences. Algorithms can assist humans by curating a smaller subset of items, but must also face the challenge of misalignment: humans may have different preferences from each other (and from the algorithm), and the algorithm may not know the exact preferences of the human they are facing at any point in time.
In this paper, we model and theoretically study such a setting. Specifically, we show instances where humans benefit by collaborating with a misaligned algorithm. Surprisingly, we show that humans gain more utility from a misaligned algorithm (which makes different mistakes) than from an aligned algorithm. Next, we build on this result by studying what properties of algorithms maximize human welfare, when the goals could be either utilitarian welfare or ensuring all humans benefit. We conclude by discussing implications for designers of algorithmic tools and policymakers.
https://cdn.satellite.earth/859216c98a89a025c9b7c3269c5b5e056243fa4a9d12e18b50e5bccb71379d4c.pdf
Forgotten Tasks


Actively supporting the security and integrity of the Bitcoin protocol through community involvement is essential to the long-term success of Bitcoin.
State held Christ at ransom
ARTIST
Wallace Smith
DATE
1922

