Affordance

In psychology, affordance is what the environment offers the individual. In design, affordance has a narrower meaning; it refers to possible actions that an actor can readily perceive.

10 Examples of Affordances - The Boffins Portal

Affordance is a concept in design that refers to the possible actions or uses that an object or environment offers a user. It is the relationship between an object and the person using it and what the person perceives they can do with the object based on its physical characteristics. In other words, affordance is ... Read more

Funding and Framing Impact in the Neuro Frontier

Representations 04: Philanthropy, FRO, Connectomes, ARIA

Towards Post-Interaction Computing: Addressing Immediacy, (un)Intentionality, Instability and Interaction Effects

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we ...

What are Affordances? — updated 2026

Affordances are the characteristics or properties of an object that suggest how it can be used. It shows a user that an object can be interacted with.

560 – Ecological Cognition II: Resonance

560 What the heck does the brain do in Ecological Dynamics, if it isn’t computing, processing, or representing? An introduction to the concept of Resonance.Download link

51 Ways to Spell the Image Giraffe: The Hidden Politics of Token Languages in Generative AI

Generative AI models don't operate on human languages – they speak in **tokens**. Tokens are computational fragments that deconstruct lan...

562 – Ecological Cognition III: Radical Embodied Cognitive Science (part 1)

562 Continuing the journey in understanding the Ecological approach to cognition by looking at Tony Chemero’s book: Radical Embodied Cognitive Science. Conceptualizing cognition in terms of agent-environment dynamics instead of computation and representation. What is RECS, and where did these ideas come from?Download link

A foundation model of vision, audition, and language for in-silico neuroscience | Research - AI at Meta

Cognitive neuroscience is fragmented into specialized models, each tailored to specific experimental paradigms, hence preventing a unified model of...

Horismos: Self-representation and the Derived Constitutional Boundary in Enriched Cognitive Systems

We present a theory of self-representing cognitive systems grounded in $$([0,\infty ],+)$$([0,∞],+)-enriched category theory and the Yoneda lemma. The central object is a self-representing $$([0,\infty ],+)$$([0,∞],+)-enriched category $$\mathcal{C}$$C—a Lawvere metric space whose objects are complete epistemic architectures, whose hom-values record directed informational upgrade costs, and which is separated, closed under internal homs, and bilaterally Cauchy complete—together with a contractive cognitive endofunctor $$F:\mathcal{C}\rightarrow \mathcal{C}$$F:C→Cmodelling iterative self-improvement. We establish eight results in a single logical arc. The Horizon Theorem shows that the Yoneda embedding $$\varphi (A)=\mathcal{C}(-,A)$$φ(A)=C(-,A)is never essentially surjective: $$\mathcal{C}$$C sits strictly inside its own free Cauchy completion $$\mathcal{P}(\mathcal{C})$$P(C), with the non-representable presheaves forming a topologically dense family, proved via a reflexivity argument. The Lawvere–Banach Attractor Theorem shows that every contractive endofunctor on a bilaterally complete, separated $$([0,\infty ],+)$$([0,∞],+)-enriched category converges to a unique fixed point $$\mathbf {\Omega }$$Ωat a geometric rate. The Boundary Derivation Theorem shows that $$\mathbf {\Omega }$$Ωis the minimal F-invariant substructure of $$\mathcal{C}$$C, with all of $$\mathcal{C}$$Cas its basin of attraction—the constitutional boundary, derived rather than postulated. The Horizon Expansion Theorem shows that each strictly ascending self-modification produces a new, quantitatively distinct non-representable witness. Beyond these four central results, we prove that Kleene and Bourbaki–Witt conditions yield only non-expansiveness when metrised, that contractive endofunctors form a monoid, and that the Yoneda horizon admits an observable diagnostic stabilising in finite time. The architectural section derives structural corrigibility and the alignment-incompleteness duality among five implications. The organising duality is exact: the non-surjectivity of $$\varphi $$φ and the existence of $$\mathbf {\Omega }$$Ωare two faces of the same $$([0,\infty ],+)$$([0,∞],+)-enriched structure. $$\mathbf {\Omega }$$Ωinhabits the space between them—not as a postulate, but as a proof. We argue that the eight theorems constitute universal laws of contractive cognitive systems: a stable constitutional boundary is not an engineering design choice but a topological inevitability for any reliably self-improving agent operating within a self-representing enriched metric space. The postulate becomes a theorem. The boundary is not imposed. It emerges.

Alexander Lerchner, The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness - PhilArchive

Computational functionalism dominates current debates on AI consciousness. This is the hypothesis that subjective experience emerges entirely from abstract causal topology, regardless of the underlying physical substrate. We argue this view ...

The Brainmade Mark

When you see this logo on any artwork, whether painting, poetry, or prose, you know that it was made by a human just like you.

The Philosophy of Language Models

ABSTRACT The success of large language models (LLMs) across many domains of AI research has generated intense debate. Some attribute their impressive performance on complex tasks to human‐like linguistic and cognitive capacities, whereas others ascribe it to shallow pattern matching. These disputes stem from deep‐seated philosophical disagreements about the nature of language and cognition. We provide an opinionated survey of these disagreements across core topics in the philosophy of mind and language, including syntactic competence, compositionality, linguistic meaning, representation, attitudes, reasoning, agency, and consciousness. We contend that progress on these issues requires not only clarity about background philosophical commitments but also, in many cases, close engagement with emerging empirical evidence.

Alexander Lerchner, The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness - PhilPapers

Computational functionalism dominates current debates on AI consciousness. This is the hypothesis that subjective experience emerges entirely from abstract causal topology, regardless of the underlying physical substrate. We argue this view ...