Show HN: Sam Altman:"Scaling LLMs won't get us to AGI" – maybe we found a path
by nvrstl | 2025-08-19 18:33:37+00:00
Hi HN,

At the 2023 Hawking Fellowship at Cambridge Union, a student asked Sam Altman: “To get to AGI, can we just keep min-maxing language models, or is there another breakthrough that we haven’t really found yet?”

Altman’s response was telling: “We need another breakthrough… I don’t think that doing that will get us to AGI. If, for example, superintelligence can’t discover novel physics, I don’t think it’s a superintelligence. Teaching it to clone the behavior of humans and human text – I don’t think that’s going to get there.”

If Altman is right that scaling alone is a dead end, then this might be the beginning of the real race - not just to build bigger LLMs, but to invent the architectures that can discover the unknown.

This echoes a long-standing question in AI research: what lies beyond scaling language models in the pursuit of true general intelligence?

Did we finally stumbled onto the next breakthrough Altman was hinting at?

We think so.

Collective AGI: The Civilizational Path to AGI

Rooted in History: Human intelligence didn’t become powerful in isolation. A single brain is limited. What made human intelligence general and world-changing was the civilizational process - networking, collaboration, culture, institutions, governance, commerce, law, ethics - compounding across generations.

A Pattern, a Fractal: Ecosystems evolve through interdependent species; human intelligence evolved through interdependent minds. Civilization was humanity’s first great outcome of collective intelligence, recursively amplifying the reach of individual cognition.

Applied to AGI: In the same way, AGI won’t emerge from a single artifact or mono-worldview. It must arise through plurality of AI forms, multi-agent networks, evolving institutions, and shared participation - the same mechanisms that scaled human intelligence, now applied to artificial intelligence.

If that’s true, the next breakthrough isn’t bigger LLMs. It’s building civilizational ecosystems for AI societies scale - that don’t just predict text, but evolve new knowledge, new institutions, and new ways of thinking.

I'm Kanishka Nithin, I’ve been working on AI for over a decade, and today I’m excited (and a little nervous) to share something deeply personal and long in the making: AGI Grid - our open effort to together build what we call Collective AGI - The open, fastest, safest, and most efficient path to Artificial General Intelligence.

AGI Grid: It is a open civilizational infrastructure ecosystem for collective AGI

Website: https://www.agigr.id Vision paper: https://resources.agigr.id

The collective AGI ecosystem consists of 12 Open source projects - listed at

Docs: https://docs.agigr.id

What we’d love from HN: Feedback: Does this framing of Collective AGI resonate? Critique: Where do you see the holes? Collaboration: If you’re working on agents, collective intelligence, or diverse cognitive architectures, let’s talk.

This project grew out of both crisis and conviction, and we believe the next leap in AI won’t come from a single giant model, but from grids of diverse forms of intelligence, aligned and cooperating.

-Team AGI Grid: A Collective AGI