Tl;dr

Convergent abstraction hypothesis posits abstractions are often convergent in the sense of convergent evolution: different cognitive systems converge on the same abstraction, when facing similar selection pressures and learning in similar environments. It is a less ambitious alternative to 'natural abstractions hypotheses' and, in my view, more likely to be true.

Convergence may be real, useful, and empirically robust, while still being contingent and fragile under changes in architecture, training pressure, or optimization regime.

Convergent evolution 

To recapitulate some basics: notice that sharks, ichthyosaurs and dolphins look remarkably similar, despite their ancestors being wildly different.

This is a case of convergent evolution: the process by which organisms with different origins develop similar features. Both sharks and dolphins needed speed and energy efficiency when moving in an environment governed by the laws of hydrodynamics, and so they converged on a pretty similar body shape.

A complementary concept from biology is contingency - convergent features are themselves often contingent on some other feature. For example, the shark morphology depends on there being a central vertebral column (or spine), which only evolved once and is the defining feature of vertebrates. There are many other aquatic predators [...]

---

Outline:

(00:44) Convergent evolution

(01:53) Convergent evolution applied to abstractions

(02:22) Selection pressures

(02:53) Compression buys you a lot

(04:41) Shared environments

(05:30) What this predicts

(06:21) What this does not predict, or contingency in abstraction space

(06:45) Case study of architectural contingency: convergent vision abstractions

(09:14) Whats the difference between convergent abstractions and natural abstractions

(11:22) Why do I care

The original text contained 1 footnote which was omitted from this narration.

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

---

Images from the article:

Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.