The challenges of funding deep tech, moving from science to products

If you want to move from science to products, you have to live for some time in a super-position of those states before you can collapse the wave function and understand what is it that you have. For me, what was so lucky, was to have investors put speculative money in, that first 15 months we weren’t a research project but we still weren’t a company.

That was Ilan Gur on the Idea Machines podcast with Ben Reinhardt. Obviously, the DoD does not accept life in that superposition of states. Indeed, that incubation, discovery, and pivoting into an actual product is presumed to be hammered out from high readiness technologies and sufficient paper planning. Here’s some more interesting discussion on the difficulties of funding deep tech problems.

Ilan: You can’t blame VC or Wall Street. Frankly, the earliest investors in [deep tech] companies — those companies are not going to make their money no matter how successful if the success starts 20 years later. The only way to encourage that kind of work at that stage is to start thinking about it as a really interesting applied research lab. What I’m interested in, is how we get the government to realize that a network or constellation of startups, however you want to think about it, that should be the best way to do applied research. There are a lot of problems with governments funding startups as research labs. I think that’s a really compelling direction.

 

Ben: What are the biggest challenges?

 

Ilan: … R&D funding can be used irresponsibly, either because you’re going to fund an evil technology, or because you’re going to squander the money because you’re buying a Ferrari on the side.

 

Ben: Or just buying really expensive equipment when it’s not necessary. I think that’s insidious, when it’s not clearly fraud but do you really need it?

 

Ilan: … If government sends a check to Virginia Tech to do research, there are a lot of guardrails and bounds that would make it really hard for that money to be spent in an irresponsible way or be ethically misled. It happens. But one of the best parts of startups is they’re much less tightly bound and a lot more dynamic in how they’re led. The incentives are different. But it also means you have less control mechanisms. And that stuck with me as a challenge.

 

Any of the actors, including government, are willing to take insane amounts of technical risk and scientific risk, but there’s very little appetite to take institutional risk, or modality risk…. No one ever lost their job funding a Stanford professor to do research, whereas, god forbid I accidentally fund Theranos to do research. That’s death.

 

Ben: I call that asymmetric career risk. Where nobody gets fired for funding the safe thing. But we’re counting on the outlier results. The problem is they can be outliers on the good or bad side. If you fund an outlier on the bad side you get fired. Unlike a VC, who gets to participate in the outsized upside of positive outliers, someone in the government — sure, they’ll get some, ‘yay, you funded it’ — but they won’t get much participation in the upside if it pays off.

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