has already been fully explained by adaptation and natural selection.
cannot be reproduced by any simple computational rules or models.
stems from intrinsic computational processes (simple underlying rules).
represents a fundamentally higher order of complexity than anything non-biological.

2. Why is biology “more obviously program-like” than physics, according to Wolfram?

Biological systems are inherently more complex, forcing programmatic thinking.
Physical laws cannot be represented as computational rules, whereas biology can.
Early computers were modeled directly on biological brains.
Biological organisms contain DNA that explicitly encodes development instructions.

3. What microscopic observation supports the idea that simple rules underlie biological complexity?

Microscopic organisms show greater complexity than larger ones.
Many microscopic structures are regular and repetitive, hinting at simple programs.
There is no visual similarity between biological and computational patterns.
Microscopic forms violate known physical laws.

4. In Wolfram’s minimal evolution model, an organism’s genotype is:

the final pattern or phenotype it exhibits.
the initial seed configuration.
the cellular-automaton rule (the program) that generates it.
the fitness metric used for selection.

5. A mutation is accepted when it:

immediately produces a more complex-looking pattern.
is always accepted (no filtering).
increases the total number of cells, regardless of lifetime.
keeps or lengthens the pattern’s finite lifetime (and avoids infinite growth).

6. Typical mutation sequences in the model:

quickly get stuck and can’t find longer-lived patterns.
routinely reach rules with much longer-lived, complex patterns.
require one unique mutation path to improve.
leave patterns simple with no lifetime increase.

7. Neutral mutations mainly:

are a nuisance and are filtered out immediately.
actively hinder progress by wasting time.
accumulate and open paths to later fitness gains.
do not exist in this model.

8. The dominant factor shaping evolved complexity is:

detailed environmental selection.
intrinsic computational irreducibility of development.
pure random chance.
an external intelligent designer.

9. Switching the fitness goal (e.g., width vs. height) showed that:

patterns became trivial and predictable.
evolution failed entirely under new fitness measures.
width-optimized patterns looked random and unrelated to height-optimized ones.
complex “life-like” patterns still emerged; only the trait changed.

10. Fitness over time exhibits:

a smooth, gradual rise with every mutation.
a single early jump, then no change.
long plateaus and occasional sharp jumps (punctuated equilibrium).
random zig-zags with no pattern.

11. Wolfram’s abstract “fundamental problem of medicine” is:

sequencing the entire genome in advance.
finding a counter-perturbation to restore a derailed developmental trajectory.
deriving one master equation for all outcomes.
classifying diseases into a fixed taxonomy.

12. When a single-cell perturbation was introduced, not observed was:

rapid self-healing to normal.
a shorter remaining lifetime (earlier “death”).
unbounded, tumor-like growth.
splitting into two independent living patterns.