Quanta Magazine discusses why the human genome may be difficult to model with artificial intelligence if it is treated as a simple “blueprint” or algorithm. The article argues that genetic information is embedded in a complex, physical biological system rather than operating like a straightforward set of instructions. It emphasizes that genome behavior emerges through interactions among many components, including how genetic material is organized and regulated inside cells. Because of this “tangled physicality,” patterns found in genetic data may not translate into clear, generalizable rules for prediction or explanation. The piece suggests that AI approaches could face limits when they assume that genotype-to-trait relationships are direct and static. Instead, models may need to account for biological context and the many processes that shape gene activity over time and across environments. Overall, Quanta presents the view that the genome’s complexity and physical implementation can confound attempts to build overly simplified computational representations of heredity.