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#emergence

3 posts2 participants0 posts today
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h o ʍ l e t t

→ How the human brain is like a murmuration of starlings
aeon.co/essays/how-the-human-b

“The core idea of emergence inspired me to develop the concept I call the entangled brain: the need to understand the brain as an interactionally complex system where functions emerge from distributed, overlapping networks of regions rather than being localised to specific areas.”

AeonHow the human brain is like a murmuration of starlings | Aeon EssaysThe brain is much less like a machine than it is like the murmurations of a flock of starlings or an orchestral symphony
#human#emergence#entangled
Public
FÉLIN

💡 𝐋𝐞𝐬 𝐞́𝐜𝐨𝐮𝐭𝐞𝐬 𝐬𝐮𝐫 𝐥𝐞𝐬 𝐩𝐥𝐚𝐭𝐞𝐟𝐨𝐫𝐦𝐞𝐬 𝐩𝐫𝐨𝐯𝐢𝐞𝐧𝐧𝐞𝐧𝐭 𝐚̀ 𝟔𝟐% 𝐝𝐞𝐬 𝐩𝐥𝐚𝐲𝐥𝐢𝐬𝐭𝐬 𝐜𝐫𝐞́𝐞́𝐞𝐬 𝐩𝐚𝐫 𝐥𝐞𝐬 𝐚𝐮𝐝𝐢𝐭𝐞𝐮𝐫𝐢𝐜𝐞𝐬 𝐞𝐮𝐱.𝐞𝐥𝐥𝐞𝐬-𝐦𝐞̂𝐦𝐞𝐬...

Ce chiffre significatif est issu de l’enquête multi-plateformes, menée par Alix Bénistant (enseignant/chercheur à l’Université Sorbonne Paris Nord LabSIC / LabEx ICCA) sur les habitudes et usages de découverte, dans le cadre de notre grand dossier "Émerger sur les plateformes".

👉 L'enquête : fede-felin.org/2025/03/12/le-s

Streaming musical : Comment les français découvrent leur musique ?
#emergence#decouvrabilité#streaming
Public
petersuber

From #JohnHopfield on his #Nobel prize: "I think that the prize is recognizing, in part, the fact that understanding the deep problems of things like #mind is not going to come forth in some simple way like Newtonian physics. It really requires much more understanding of the relationship between structure and properties, and structure dynamics and properties."
nobelprize.org/prizes/physics/

NobelPrize.orgThe Nobel Prize in Physics 2024The Nobel Prize in Physics 2024 was awarded jointly to John J. Hopfield and Geoffrey E. Hinton "for foundational discoveries and inventions that enable machine learning with artificial neural networks"
#AI#CogSci#Emergence
Public
Winfried 🏳️‍🌈

Really revealing thread on LLMs. People are defending LLMs with arguments that boil down to 'intelligence is an emergent property and LLMs have so many parameters that intelligence will emerge'. But what we see, is plausible language and #hallucinations, not the #emergence of #intelligence

#LLM #GenerativeAI #AI via @gleick mas.to/@gleick/113058537194470

mas.toJames Gleick (@gleick@mas.to)When he’s not busy being one of our best fiction writers, Ted Chiang has become our best critic of generative AI: “The programmer Simon Willison has described the training for large language models as ‘money laundering for copyrighted data,’ which I find a useful way to think about the appeal of generative-A.I. programs: they let you engage in something like plagiarism, but there’s no guilt associated with it because it’s not clear even to you that you’re copying.” https://www.newyorker.com/culture/the-weekend-essay/why-ai-isnt-going-to-make-art
Public
Sara Nyberg

Creating a Node of #Emergence

- #Living, #Learning, and #Growing Together for a #Flourishing World -

"We are looking for co-creators of our new #international deliberately developmental #community in #Stockholm "

Does this sound interesting to you?
Read more here - and express your interest!
ekskaret.confetti.events/proje

ekskaret.confetti.eventsEmerge Project Lakefront- Living, Learning, and Growing Together for a Flourishing World -
Public
Yohan John 🤖🧠

"... even a full description of the microscopic components and their interactions may not facilitate the identification of when and where emergent phenomena may take place".

💯

From the paper on emergence by Fernando Rosas and colleagues. arxiv.org/abs/2402.09090

Here's a Quanta article about it:
quantamagazine.org/the-new-mat

arXiv.orgSoftware in the natural world: A computational approach to hierarchical emergenceUnderstanding the functional architecture of complex systems is crucial to illuminate their inner workings and enable effective methods for their prediction and control. Recent advances have introduced tools to characterise emergent macroscopic levels; however, while these approaches are successful in identifying when emergence takes place, they are limited in the extent they can determine how it does. Here we address this limitation by developing a computational approach to emergence, which characterises macroscopic processes in terms of their computational capabilities. Concretely, we articulate a view on emergence based on how software works, which is rooted on a mathematical formalism that articulates how macroscopic processes can express self-contained informational, interventional, and computational properties. This framework establishes a hierarchy of nested self-contained processes that determines what computations take place at what level, which in turn delineates the functional architecture of a complex system. This approach is illustrated on paradigmatic models from the statistical physics and computational neuroscience literature, which are shown to exhibit macroscopic processes that are akin to software in human-engineered systems. Overall, this framework enables a deeper understanding of the multi-level structure of complex systems, revealing specific ways in which they can be efficiently simulated, predicted, and controlled.
#Emergence
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