Lee Cronin's Assembly Theory offers a way to find alien life by quantifying molecular complexity. Using mass spectrometry, scientists can search for molecules with a high 'assembly index,' a clear signature that they were constructed by an evolutionary process rather than random chemistry.

Selection is not exclusive to biology. It is a fundamental physical force that acts on matter, favoring configurations that persist over time. This process of 'selfish matter' battling for persistence was happening long before the first cells emerged, making life a natural consequence of physics.

The success of iterative design processes hinges entirely on the metric being measured. An enzyme evolved for temperature stability won't necessarily remove clothing stains unless stain removal is the specific property being screened for. This highlights the critical importance of defining the right success metric from the start.

The small size of the human genome is a puzzle. The solution may be that evolution doesn't store a large "pre-trained model." Instead, it uses the limited genomic space to encode a complex set of reward and loss functions, which is a far more compact way to guide a powerful learning algorithm.

Frances Arnold, an engineer by training, reframed biological evolution as a powerful optimization algorithm. Instead of a purely biological concept, she saw it as a process for iterative design that could be harnessed in the lab to build new enzymes far more effectively than traditional methods.

Instead of seizing human industry, a superintelligent AI could leverage its understanding of biology to create its own self-replicating systems. It could design organisms to grow its computational hardware, a far faster and more efficient path to power than industrial takeover.

Afeyan proposes that AI's emergence forces us to broaden our definition of intelligence beyond humans. By viewing nature—from cells to ecosystems—as intelligent systems capable of adaptation and anticipation, we can move beyond reductionist biology to unlock profound new understandings of disease.

Beyond optimizing existing biological functions, Frances Arnold's lab uses directed evolution to create enzymes for entirely new chemical reactions, like forming carbon-silicon bonds. This demonstrates that life's chemical toolkit is a small subset of what's possible, opening up a vast "non-natural" chemical universe.

AI models use simple, mathematically clean loss functions. The human brain's superior learning efficiency might stem from evolution hard-coding numerous, complex, and context-specific loss functions that activate at different developmental stages, creating a sophisticated learning curriculum.