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Prikvačeni tweet
"This very cogitation carries with it I don't know what secret, hidden horror; indeed one finds oneself wandering in this immensity, to which are denied limits and center and therefore also all determinate places." Image: First page of Kepler's Mysterium Cosmographicumpic.twitter.com/Gu2xmwaXDZ
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'When Newton demonstrated the supreme importance of accelerations in dynamics, the perspective of science changed, for the world at the present instant became the mere consequence of its initial conditions'pic.twitter.com/yvngFGpZdn
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only the probable is experienced
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Emergent architecture: the Horseshoe bat, who uses its specialized facial complexion for an enhanced echolocation Photograph: Ivan Kuzminpic.twitter.com/xmZu6WuEL0
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To me, the question should be inverted: what could Darwinian processes be an expression 𝘰𝘧? That would lead one to a transversal question about the general economy of nature. But maybe that is beyond biology, physics, or any methodologically manageable procedure.
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Can natural selection be physicalized? Even if we can give an empirically consistent form of quantum Darwinism, I doubt we'll be able to render it completely continuous with its biological version.
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Darwinian logic has been often recognized as a ubiquitous process happening in many natural strata. Dennett refers to natural selection as an 'algorithm', and Everett already talked in his long thesis about a branching process.https://twitter.com/_infinitography/status/1179144711984095233?s=20 …
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The arborescent structure of worlds is a simple emergent structure from the interactions between the quantum system and its environment. The environment 'selects' the relative weights that the components will have in the following generation.https://twitter.com/_infinitography/status/1176225304156737536?s=20 …
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In the (contemporary) MWI, the gap between the quantum and the classical is merely a quantitative one: certain components have higher weight (they're more "robust"), which allows them to be more frequently measured by the environment.
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This analogy, by itself, can be applied irrespective of any interpretation of QM, given decoherence. But I think that where it's most useful is in the Many-Worlds Interpretation.
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The key analogy resides in a functional identification of the mean fitness of a certain genotype (w) and the relative Born weights of the components of ψ. This implies that a higher probability of classically persisting in the environment is equivalent to being better adapted.
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1. Representation of the density matrix of a wave-function. 2. Representation of an adaptive topography. While showing these two images is just a bit of demagoguery (they're just two graphs), I think that, put together, they help to grasp the idea in an intuitive waypic.twitter.com/Lr6FWd1OTH
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where ψ represents a wave function, α and β its different components and 2αβ the coherence effects between them; 𝑤 represents their respective fitness values
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tecnocartesius proslijedio/la je Tweet
As far as current machine learning is concerned, generalization originates from the ability to learn the latent manifold on which the training data lies, i.e. the ability to interpolate between training samples (local generalization, by definition)
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irreducible randomness is the only true geotrauma
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Douglas House, Harbor Springs (1973) Architect: Richard Meier | Photograph: AIApic.twitter.com/SI6IfJTeLh
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