Microsoft vs Google: Former Partners Now Have Radically Different Plans for AGI

Two recent podcast interviews revealed a fascinating split in how the biggest AI companies are approaching AGI.

Demis Hassabis, CEO of Google DeepMind, and Mustafa Suleyman, CEO of Microsoft AI, co-founded DeepMind. Now they’re leading rival labs — and their roadmaps to AGI couldn’t be more different.

Google’s approach

Hassabis appeared on The Google DeepMind Podcast with Professor Hannah Fry to discuss Google’s scientific approach. Hassabis is building AGI as the ultimate scientific tool to unlock the secrets of the universe.

He wants to solve “root node“ problems: fundamental challenges like room-temperature superconductors and nuclear fusion. He says Google DeepMind splits resources 50/50 between scaling infrastructure and pure research innovation, betting that AGI requires both. 

More specifically, he’s working on:

Fix AI’s “jagged intelligence“ problem, where models that ace PhD-level math still fail simple counting.

Build physics benchmarks to ensure AI actually understands Newton’s laws, not just visual plausibility (looking realistic or believable to us humans).

Chase an AlphaZero-like leap where AI discovers knowledge independently, as opposed to simply compressing human data (basically what it does now).

Microsoft’s approach

Suleyman joined Moonshots with Peter Diamandis to outline Microsoft’s AGI strategy. Suleyman is building the ultimate economic engine to rewrite capitalism. But more importantly, one that keeps humans firmly in control.

He rejects the entire “race“ metaphor for AGI. There’s no finish line, no winner, but a proliferation of knowledge where technology scales simultaneously across the board. Microsoft’s mandate isn’t to “win“ AGI but to ensure self-sufficiency: training frontier models end-to-end without relying on partners like OpenAI.

More specifically, he sees a path towards AI success going like this:

Kill the current interface paradigm; no more apps or browsers, and move instead towards conversational agents acting as 24/7 assistants.

Sell “certified agents“ with guarantees of reliability and safety.

Focus on containment before alignment; limit what AI systems can do before worrying about their values.

Build strict liability frameworks so humans remain accountable for AI actions.

Where do both land on AGI? Hassabis thinks we’re years away from AGI because current models lack consistency across tasks. Suleyman argues we’ve already passed the classic Turing Test; we barely noticed because improvements happen so fast now. His new benchmark for AGI is economic: give an agent $100K and see if it can autonomously turn it into $1 million.

Why this matters

Google’s splitting its bets between scientific perfection and products it can ship now.

Microsoft’s betting on shipping controllable agents that create economic value today, with humans maintaining ultimate authority (augmentative intelligence), while still developing more frontier models for later down the line. That’s the benefit of having access to OpenAI’s models for years to come, you see…

Our take: Reframing the debate away from a race to be won makes sense. Both former partners seem to agree that the current dynamic has pros and cons.

The pros = progress is moving ultra-fast (I think Demis said DeepMind made something like 5 years of progress in one year in 2025), but the con is this competitive acceleration that only slows down when the legal guardrails get finalized. As for that, A16Z has some ideas…

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