Ayyoub Oukaci

Logician, Author and Translator

Master's in Mathematical Logic and Foundations of Mathematics

Licentiate's in Philosophy

German Language at Goethe-Institut

[Jon Mackenzie @Jon_Mackenzie]

If you want to know why the Premier League feels like such a strange place tactically already this season, I wrote a book about it and you can buy it here:

https://t.co/xoOBxVp3NR

[Palgrave Macmillan @Palgrave]

What are the limits of markets? What moral responsibilities do businesses have? To what extent is individual economic success shaped by personal effort versus social factors? In 'Social Economies,' Lester Hadsell examines these questions across twenty clear chapters, analyzing the connections between economies and society. https://t.co/H7rt5uXyFo

[Santa Fe Institute @sfiscience]

A chair can still look like a chair, even when reduced to a sparse cloud of points. Humans are remarkably good at recognizing objects from this kind of minimal 3D information. 

A new study by SFI Program Postdoctoral Fellow Shuhao Fu and co-authors asks whether deep learning models represent 3D shapes in similar ways, and finds that hierarchical abstraction is key to more human-like performance.

https://t.co/BZQG1Wcp37

[Santa Fe Institute @sfiscience]

In the 1970s, Thomas Nagel famously asked "what is it like to be a bat?" Today, large language models clamor to give an answer. Researchers optimistically argue that AI will allow humans to speak to whales, monkeys, even bats within a handful of years. However, interspecies communications experts have raised important questions about such bold claims.

 To explore what interspecies communication actually requires, historically, philosophically, and empirically, SFI co-organized the working group "Interspecies: Decoding, Translation, and Interpretation" this May in collaboration with the Interspecies Internet.

https://t.co/KJckQGdZ1Z

[Nature Human Behaviour @NatureHumBehav]

The interaction of meaning similarity and confusability explains regularity in form–meaning mappings at and below the word level https://t.co/X9qm4rAJ1V

[Nature Human Behaviour @NatureHumBehav]

Brain activity, disruption and connectivity comparisons identify origins of human metacognition in other primates https://t.co/vdrW6gtsTX

[Nature Human Behaviour @NatureHumBehav]

The growing concentration of national influence in global science https://t.co/aJ1dbsIUlg

[Nature Human Behaviour @NatureHumBehav]

The role of context in continuity and segmentation https://t.co/bvUWfGF7YW

[Nature Human Behaviour @NatureHumBehav]

Hybrid neural–cognitive models reveal how memory shapes human reward learning https://t.co/B9wiwpftD6

[Palgrave Macmillan @Palgrave]

'The Case Against Political Parties', an #OpenAccess book by @ChrisBaylor5, argues that parties often undermine rational deliberation, fair representation, and government accountability. https://t.co/CzViPcyGXz

[arXiv math.LO Logic @mathLOb]

Victoria Gitman, Joel David Hamkins, Thomas A. Johnstone: Class choice and the surprising weakness of Kelley-Morse set theory https://t.co/6Fobdzmnme https://t.co/r57FNmn2hr https://t.co/YFyIHSA0Hf

[arXiv math.LO Logic @mathLOb]

Toby Meadows: Foundations with Imagination https://t.co/5YEIm7gk3H https://t.co/GmB87wQ6VI https://t.co/DsFB5TraFC

[Bloomsbury Philosophy @BloomsburyPhilo]

In this book, Blake investigates early Chinese philosophy of language through the concept of 'fa', providing fresh insights into ancient Chinese thought and language.

Learn more: https://t.co/VYAjpI63TY
Preview: https://t.co/TzT2rtmH4k

[Physics MDPI @Physics_MDPI]

#Article
A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts by Marcel Ausloos, Giulia Rotundo and Roy Cerqueti
https://t.co/OySP5Y0X1t

@MdpiPhysci @uniofleicester @ASE_Bucuresti @UnivBabesBolyai @SapienzaRoma @UnivAngers

[Michael Timothy Bennett @MiTiBennett]

New preprint.

[arXiv math.LO Logic @mathLOb]

Christopher Sorg: Koopman Spectral Computation Beyond The Reflexive Regime: Endp... https://t.co/W7AB9xKbok https://t.co/4A9dt5GiPm https://t.co/EWuWUaTUCn

[arXiv math.FA Functional Analysis @mathFAbot]

Lamby, Nicolay: A Functorial Approach to Multi-Space Interpolation with Functi... https://t.co/JJNkO0VkR9 https://t.co/lGLEXuiWeA https://t.co/oI41Tb3XRt

[arXiv math.FA Functional Analysis @mathFAbot]

Deyu Chen, Guixiang Hong: The nonlinear estimates on quantum Besov space https://t.co/ESWUnL3lOu https://t.co/J3EbCRQ6Ui https://t.co/MqT48F0LAh

[Santa Fe Institute @sfiscience]

We trust our memories because they feel natural, and because time seems to flow in only one direction, from the past to the present. Physics, however, allows for stranger possibilities that challenge our intuition.

In a new paper, SFI researchers examine the Boltzmann brain hypothesis, a longstanding thought experiment that raises fundamental questions about memory, entropy, and the direction of time. The work clarifies how arguments for or against these ideas depend on assumptions about the past that are not fixed by physical laws alone.

https://t.co/hbixt3ip0Y

[Michael Levin @drmichaellevin]

New preprint: https://t.co/8tCMPK7AlH
Chris Fields, @BeneHartl, @LPiolopez
"Remapping and navigation of an embedding space via error minimization: a fundamental organizational principle of cognition in natural and artificial systems"

Abstract:

The emerging field of diverse intelligence seeks an integrated view of problem-solving in agents of very different provenance, composition, and substrates. From subcellular chemical networks to swarms of organisms, and across evolved, engineered, and chimeric systems, it is hypothesized that scale-invariant principles of decision-making can be discovered. We propose that cognition in both natural and synthetic systems can be characterized and understood by the interplay between two equally important invariants: (1) the remapping of embedding spaces, and (2) the navigation within these spaces. Biological collectives, from single cells to entire organisms (and beyond), remap transcriptional, morphological, physiological, or 3D spaces to maintain homeostasis and regenerate structure, while navigating these spaces through distributed error correction. Modern Artificial Intelligence (AI) systems, including transformers, diffusion models, and neural cellular automata enact analogous processes by remapping data into latent embeddings and refining them iteratively through contextualization. We argue that this dual principle - remapping and navigation of embedding spaces via iterative error minimization - constitutes a substrate-independent invariant of cognition. Recognizing this shared mechanism not only illuminates deep parallels between living systems and artificial models, but also provides a unifying framework for engineering adaptive intelligence across scales.