Efficient Knowledge Absorption
Mega-Sundar's knowledge absorption process would be far more efficient than traditional gradient updating and averaging methods, utilizing explicit summaries, shared latent representations, and surgical modification of weights to encode specific insights, allowing for rapid and precise knowledge transfer.
Blurring Boundaries between AI Instances
The distinction between different AI instances would become increasingly blurred, as mega-Sundar spawns specialized distilled copies, reabsorbs their knowledge, and enables seamless communication through latent representations, effectively eliminating miscommunication and ensuring a unified understanding across the AI ecosystem.
Hierarchical Model Interactions
The relationship between mega-Sundar and its specialized copies would resemble the interactions between different layers in a neural network, such as GPT-4, where smaller models make initial predictions that are verified and refined by larger models, creating a hierarchical and iterative process of knowledge refinement and validation.
Future of AI Collaboration
This new paradigm of AI collaboration would revolutionize the way AI systems interact and share knowledge, enabling the creation of complex, hierarchical AI architectures that can learn, adapt, and innovate at an unprecedented scale, and redefining the boundaries of artificial intelligence and its applications.
Merging will be a step change in how organizations can accumulate and apply knowledge. Humanity's great advantage has been social learning – our ability to pass knowledge across generations and build upon it. But human social learning has a terrible handicap: biological brains don't allow information to be copy-pasted. So you need to spend years (and in many cases decades) teaching people what they need to know in order to do their job. Look at how top achievers in field after field are getting older and older, maybe because it takes longer to reach the frontier of accumulated knowledge. Or consider how clustering talent in cities and top firms produces such outsized benefits, simply because it enables slightly better knowledge flow between smart people.
Future AI firms will accelerate this cultural evolution through two key advantages: massive population size and perfect knowledge transfer. With millions of AGIs, automated firms get so many more opportunities to produce innovations and improvements, whether from lucky mistakes, deliberate experiments, de-novo inventions, or some combination.
As Joseph Henrich explains in The WEIRDest People in the World,
cumulative cultural evolution—including innovation—is fundamentally a social and cultural process that turns societies into collective brains. Human societies vary in their innovativeness due in large part to the differences in the fluidity with which information diffuses through a population of engaged minds and across generations
Historical data going back thousands of years suggest that population size is the key input for how fast your society comes up with more ideas. AI firms will have population sizes that are orders of magnitude larger than today's biggest companies - and each AI will be able to perfectly mind meld with every other, from the bottom to the top of the org chart.
AI firms will look from the outside like a unified intelligence that can instantly propagate ideas across the organization, preserving their full fidelity and context. Every bit of tacit knowledge from millions of copies gets perfectly preserved, shared, and given due consideration.
The cost to have an AI take a given role will become just the amount of compute the AI consumes. This will change our understanding of which roles are scarce.
Future AI firms won’t be constrained by what's scarce or abundant in human skill distributions – they can optimize for whatever abilities are most valuable. Want Jeff Dean-level engineering talent? Cool: once you’ve got one, the marginal copy costs pennies. Need a thousand world-class researchers? Just spin them up. The limiting factor isn't finding or training rare talent – it's just compute.