Human brains are preconfigured with instructions for understanding the world

Innate structure, “bootloaders,” and evolution

• Many commenters like the “bootloader/firmware” analogy: brains start with prewired structure and priors, not a blank slate.
• Evolution is framed as “pretraining” that encodes inductive biases about the world; instincts are seen as implementations of these priors.
• Others object to terms like “instructions” and “chosen,” arguing this anthropomorphizes evolution and overcomputationalizes brains.

Animals, instincts, and human developmental tradeoffs

• Numerous examples of precocial species (foals, deer, iguanas, turtles, chickens) suggest complex behaviors (walking, escaping predators, web-building) appear almost immediately, implying strong innate circuitry.
• Human infants also show early reflexes (stepping, diving, gripping) that later disappear and are replaced by learned skills.
• Several comments stress the tradeoff: more built‑in behavior vs greater plasticity. Humans are highlighted as extreme outliers—born “premature” due to head size, with long dependency but much higher later cognitive flexibility.

DNA, information content, and emergent complexity

• There is awe that ~1.5 GB of DNA (plus epigenetics, maternal environment, cell chemistry) can yield a functioning brain+body.
• Commenters compare this to procedural generation, compression, Kolmogorov complexity, and 64k demos: small programs generating enormous complexity.
• Emphasis that DNA mostly encodes proteins and local rules, not explicit “blueprints”; global structure and behavior emerge from many interacting cells and simple rules.

Neurodiversity and environment mismatch

• People with ADHD/autism speculate their brains may reallocate circuits (e.g., from social modeling to pattern/system modeling) or tune “reality-check vs flow” differently.
• Several argue traits like hyperfocus, vigilance, and deep systems interest could be advantageous in pre-industrial or hunter‑gatherer settings, and only become “disorders” in modern environments.

Critiques of the study and its framing

• Skeptics say the headline overreaches: organoids showing self-organized firing sequences may just reflect generic network dynamics, not “instructions for understanding the world.”
• They note organoids lack real sensory input and bodily context; their main near-term value is seen as modeling development and pathology, not high-level cognition.
• Some call the article “promo-fluff,” arguing that inferring philosophical notions (innate ideas, Kantian categories) from these data is a category mistake.

Philosophical and AI parallels

• Multiple references to Kant, Plato, Chomsky and universal grammar: the finding is read as another blow to “tabula rasa” views.
• Others point to no‑free‑lunch theorems: any effective learner must encode priors.
• Analogies to LLMs and “system prompts” are common, with debate over whether current AI architectures capture anything like the brain’s compact, evolution-shaped priors.