Integrated People & Systems
What machines can teach us about our humanity
One observation I’ve noticed in the High Performance Computing (HPC) build out for AI is just how integrated everything is. The chip design, chip packaging, data center build, infrastructure integration etc. Every part of the stack is so well thought out and tied together. Having everything in one place, together and co-located is why the system works better.
Just like how machines learn from us, I believe something about the design of machines can teach us about ourselves.
However, our current society doesn’t reward humans for the same logic? Society says “a human who does more than X is too distracted or not focused enough”. The more I live through my own life, the more I viciously reject that idea. The wrong question is: “how much do you do at once?” but rather “how much can you harmoniously integrate together”?
When you search through the history of humanity and look at those who have changed the course of our species, you seem the same patterns.
Satoshi integrated economics, computer science and game theory to create Bitcoin.
Da Vinci integrated art, science, biology and more to create his most famous pieces.
I could list many more examples, but break throughs in innovation happen because of the integration of two or more unlikely intersections.
So why does society punish people for those who do more?
Forces of Specialization
The industrial engine said that efficiency is the dominant metrics of of value. The more cars we can produce the more money we make. If we have one person who is responsible for one thing, we have clear boundaries in institutions and bureaucracies.
Complexity explosion of knowledge. Post WWIII the amount of human knowledge exploded. Specialization became critical to ensure knowledge was guarded. This was the rise of education institutions around one domain of knowledge.
Management consultants, private equity and resumes want things that are “easy to recognize”. Things that break patterns are not helpful to the machine and aren’t promoted.
Financial incentives. Founders who do “too much” are punished by venture capitalists as they want their employees (I mean portfolio founders), to allocate all their risk to one thing while they get to diversify the risk of their capital across 10-100 other startups. It’s not evil, it’s just incentives.
However, we’re transitioning out of the era of the specialization into the area of the generalists with existing specialties.
Once you achieve mastery in a single domain, you can use those principles and system to start to learn other domains. Going deep in one thing can teach you so much about how certain truths of reality work. There are laws that govern reality in every domain and once you see them in one field, you won’t be able to not see them in other domains.
LLMs/AI reduce the time to get up to speed on the frontier of any body of human knowledge. Integration costs come down massively so the opportunity to integrate goes up. You see this with all the following examples:
Engineers becoming product people
Designers learning how to code
Startups that are run by fewer people due to high talent densities
Portfolio managers doing what would be done by 5-10 analysts on their team
This trend is only going to accelerate. If you can up-skill & educate yourself, you can integrate more domains and create value that needs to be created in the world. The old forces that worked against integration and favored specialization are now reverting. In this perspective, lies opportunity.