One of the worst predictors of founder success we've tracked is how well someone pitches; the correlation between pitch quality and outcome was actually negative.
Zuckerberg was so awkward in early investor meetings that VCs wondered if he could ever manage anyone, Larry Page refused interviews and earnings calls for years, and Jan Koum sold WhatsApp to Facebook for $19B as a Ukrainian immigrant with limited English.
Highly articulate people are great with the 45min process of telling a story to strangers, but this is a pretty different skill to building a company. Founders who spend years optimising to be persuasive have often optimised away from the building skills that compound over the 10yrs of execution that come afterwards; it’s incredibly hard to do both well. The articulate founder will impress your partners but the awkward one will return your fund.
Math folks look at AI output, it's clearly legit math, and they're like, yeah this thing knows how to do math
Humanities folks look at AI output, and are immediately like: this thing can't possibly be as good at interpreting texts as we are
It seems to me that before "urgently figuring out how to control AI systems much smarter than us" we need to have the beginning of a hint of a design for a system smarter than a house cat.
Such a sense of urgency reveals an extremely distorted view of reality.
No wonder the more based members of the organization seeked to marginalize the superalignment group.
It's as if someone had said in 1925 "we urgently need to figure out how to control aircrafts that can transport hundreds of passengers at near the speed of the sound over the oceans."
It would have been difficult to make long-haul passenger jets safe before the turbojet was invented and before any aircraft had crossed the atlantic non-stop.
Yet, we can now fly halfway around the world on twin-engine jets in complete safety.
It didn't require some sort of magical recipe for safety.
It took decades of careful engineering and iterative refinements.
The process will be similar for intelligent systems.
It will take years for them to get as smart as cats, and more years to get as smart as humans, let alone smarter (don't confuse the superhuman knowledge accumulation and retrieval abilities of current LLMs with actual intelligence).
It will take years for them to be deployed and fine-tuned for efficiency and safety as they are made smarter and smarter.
Imagine being ignorant of technologies that's propelled 100,000,000x gains in the last few decades
* FinFET
* 3D NAND
* High K Metal Gate
* Argon Fluoride Immersion Lithography
* Low K Dielectrics
* Copper interconnects
* Strained Silicon
* Gate All Around
* 3D Stacking
* EUV