The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 13 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Chan: 12-week accelerators struggle to turn academic researchers into business operators
“You're looking at university accelerators, I think in general you know, they tend to be something like, you know, 12 week courses to teach or mentor a university of research to found the company. Sometimes, you know, it's not to say that it doesn't work but th…”
Chan: China added the equivalent of the US energy grid in ten years
“China has put on the whole of the US energy grid in the last 10 years.”
Chan: Much new nuclear tech rebadges decades-old incremental improvements
“So a lot of the nuclear technologies are 30, 4050 years old that have been that incrementally improved, and they've kind of rebadged as new technology, but the researchers know it's not that novel, right?”
Chan: Academic researchers spot technology breakthroughs long before mainstream investors
“What happens is that in research, there's an awareness of things coming down the pipe in the research community that mainstream and investors don't really know about, but that part there is really, really valuable, and that's the part that we want, we get onto”
Chan: Neuromorphic Computing Is Accelerating in Commercial Readiness
“There's this growing field of neuromorphic computing, which has been there for a long time, but it's starting to improve in its commercial readiness, and it's really accelerating at the moment.”
Chan: Commercial validation and runway dramatically improve executive hiring for spin-outs
“Our thesis, and it's proved to be true, is that the caliber of people that you can attract to a startup like these are early, but if you can get them out of the lab, you can answer some questions around, okay, these are the parties that we, that have expressed…”
Chan: Traditional VCs struggle to invest pre-team formation in deep tech
“When you deal with something as early as what we are, and we're taking multiple bets, you know, across all these emerging fields of research generally difficult for VCs to invest at that point in time, you know, because they're pre, pre-formation of teams, you…”
Chan: Fierce academic debate is the best signal for deep tech bets
“If the noise is loud, and there's for and against, normally it's a good time to start thinking about putting some bets down in, in these areas, because it's noisy in research land, but outside of research, it's basically non-existent, you know.”
Chan: Academic researchers, not Nvidia, initiated using GPUs for AI compute
“Researchers brought the, ah, use case of GPUs for AI. Researchers did that, not Nvidia. They were focusing on gaming, but these guys, these researchers were using it for compute. He wasn't aware of that.”
Chan: Early-stage investors do not need deep technical knowledge if they know people
“Like you don't need to know technically what's going on to the nth degree, but you do need to know the people.”
Chan: Many universities operate internal funds to co-invest in spinouts
“A lot of universities have their own funds now. So you might be aware that they have their own funds. So that's an investment, Christian. That's not a brat. That's a, do we think that this thing's got a chance? So they, when they reach out to us, they have alr…”
Chan: Family offices usually invest earlier in startups than traditional VCs
“They generally are very entrepreneurial and have a great sense for investing in things, and they probably, I would say most times, you know, come in earlier than traditional VCs.”
Chan: Most outsized venture returns in AI and deep tech trace back to universities
“So if you think about AI, we think about nuclear fusion or, you know, a lot of different areas of research that have translated into really outsized returns for investors. They probably have originated from university or at some point touched the university in…”