Recent advancements in large-scale neural networks suggest that machines may surpass human capabilities in most domains sooner than anticipated. A fierce competition is underway among companies, with billions of dollars invested in hardware. This race could result in one system significantly outperforming the rest, primarily due to resource limitations and the availability of top-tier engineers. The inherent ease of replicating digital intelligence might produce a dominant system that outpaces all others. Even if such a system aligns perfectly with the objectives of human civilization, I contend that it might be evolutionarily unstable. From simple artificial constructs to intricate organisms and societies, there are myriad instances where a singular, homogeneous system becomes unstable, losing both its long-term viability and its meaningful goals. I believe that this relationship between variability and long-term outcomes is universal in nature and, when combined with the rapid replication potential of digital intelligence, could provide some context for the Fermi paradox. I delve deeper into this concept in my LinkedIn article, which can be found here: I firmly believe this topic warrants broader discussion and attention.

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