2) And Cantor's first underwriting of a non BTC/ETH/SOL treasury company
3) $360M reserve, $220M via PIPE ($100M cash, $120M IP tokens), $82M will be used to purchase $IP in the open market within 90 days
4) Framing as public play on AI is smart – "Equity markets clearly have an insatiable demand for foundational architecture for AI. We believe building scalable tech for data through programmable IP is the next big unlock for AI."
We have officially entered Stage 3 of DATs.
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1/ I finally read Leopold Aschenbrenner's essay series on AI: Situational Awareness
Everyone, regardless of your interest in AI, should read this.
I took notes, they're sloppy but figured I'd share.
Welcome to the future:
2/ from gpt4 to AGI: counting the OOMs
- ai progress is rapid. gpt-2 to gpt-4 went from preschooler to smart high schooler in 4 years
- we can expect another jump like that by 2027. this could take us to agi
- progress comes from 3 things: more compute, better algorithms, and "unhobbling" (making models less constrained)
- compute is growing ~0.5 orders of magnitude (OOMs) per year. that's about 3x faster than moore's law
- algorithmic efficiency is also growing ~0.5 OOMs/year. this is often overlooked but just as important as compute
- "unhobbling" gains are harder to quantify but also huge. things like RLHF and chain-of-thought reasoning
- we're looking at 5+ OOMs of effective compute gains in 4 years. that's another gpt-2 to gpt-4 sized jump
- by 2027, we might have models that can do the work of ai researchers and engineers. that's agi (!!)
- we're running out of training data though. this could slow things down unless we find new ways to be more sample efficient
- even if progress slows, it's likely we'll see agi this decade. the question is more "2027 or 2029?" not "2027 or 2050?"
3/ from AGI to superintelligence: the intelligence explosion
- once we have agi, progress won't stop there. we'll quickly get superintelligence
- we'll be able to run millions of copies of agi systems. they'll automate ai research
- instead of a few hundred researchers at a lab, we'll have 100 million+ working 24/7. this could compress a decade of progress into less than a year
- we might see 5+ OOMs of algorithmic gains in a year. that's another gpt-2 to gpt-4 jump on top of agi
- there are some potential bottlenecks, like limited compute for experiments. but none seem enough to definitively slow things
- superintelligent ai will be unimaginably powerful. it'll be qualitatively smarter than humans, not just faster
- it could solve long-standing scientific problems, invent new technologies, and provide massive economic and military advantages
- we could see economic growth rates of 30%+ per year. multiple economic doublings in a year is possible
- the intelligence explosion and immediate aftermath will likely be one of the most volatile periods in human history