There are a lot of different funding approaches from grants for basic research to growth capital. My favorite is venture capital. Venture capital can be very flexible. It can even straddle the line of philanthropy and investment.
The key advantage of venture capital is that there is a return-on-investment. A venture capital firm might not even ever return “capital” back to investors but rather reinvest it. In that sense, it is like a philanthropy. Therefore it’s actually possible for a fund to continue on with very large time horizons, even indefinitely, and still have a large impact on the strategy it executes on. Such funds are often called strategic venture capital funds, as they have a purpose besides merely ROI.
A $50M fund arranged like this can have an outsized impact. There are problems with venture capital though. The technology should be commercializable within a “reasonable” timeframe, so that the investors can at least liquidate some of the equity if even just to reinvest. With a very large fund, for example one that is in the billions of dollars USD (as some quasi-philanthropic climate funds are), we can shoot for multi-decade time horizons. But for a $50 million dollar fund, we’d probably want a more conventional time horizon (about 10 years). Which means VC is not appropriate if the technology is too speculative. If equity made liquid within 10 years of investment would bankrupt the startup, it is not an appropriate investment.
That’s why I would focus on one area of nanotechnology that appears to have commercial promise right now. The so-called “wet nanotechnology” or how it’s more often called these days “synthetic biology”. This is where you modify or create organisms to create products of interest. As such, if my goal is advancing nanotech, I would fund a VC fund around solving commercial problems in this area that seems to have a shorter commercial time horizon.
Biology is one molecular machine implementation in a possible universe of molecular machines. The universe can be more precise and flexible compared to biology, which is limited to working with a small amount of structures. A lot of work in nanotechnology has been focused on atomically precise manufacturing (APM), which is an important goal. Even if we have perfect control of biology there are limitations in the biological regime.
But I believe that focusing on the biological approach will bear fruit faster. There has been a lot of advancement in the field of genetic engineering or synthetic biology. n the last five years, thanks to advancements in machine learning. Machine learning can untangle the complex biological processes and their relation to final products. With rather new platforms like CRISPR, we can make very precise changes to the genomes of organisms. Combined with understanding and mapping sequences to phenotypes using machine learning, we are getting both getting better at understanding and modifying the behavior of life to get it to make what we want. If we can figure this out, the other kinds of molecular machines, dry nanotech, I think will come as well. But focusing on “wet nanotech” or biological inspired processes will just bear fruit faster. Within 10 years I expect we will have a very clear understanding of metabolism and how to manipulate it though mRNA/viral platforms or changes to DNA.
A molecular machine is a machine that is able to take atoms or molecules and arrange them into structures that are able to serve some kind of purpose (economic, medical, etc.)
My favorite example is the ribosome. We, humans, and all life on earth was created by the actions of this molecular machine. And it’s very powerful. Sure, it works with more limited building blocks compared to “all of matter”. That is the building blocks are 20 amino acids instead of atoms. Amino acids only touch a very small amount of the periodic table. But the sequences printed by these ribosomes create proteins. Proteins can have very complex purposes. In fact, we can create sequences and proteins that do not even exist in nature. The advantage of biology machinery is it already exists. In fact, we already use the structures in biology for purposes in all societies. It touches other areas of the Foresight Institute. The more we can understand biology, the more we will understand how our own bodies work. This is key to life extension as well.
My perspective is from venture capital: it is necessary to break down problems into commercially viable chunks that have a ten year time horizon at most. Venture capital is perhaps the most intrepid kind of commercial financing, and it still works on this kind of time horizon.
This is not to say it is not valuable to have a long view. I think about things about transhumanism and the technological singularity, interstellar travel, post-scarcity, and so forth. All these things are important and worth discussing. But when it comes to financing projects, there must be clear and measurable goals. It’s very hard to get funding otherwise, even far seeing philanthropic funding wants clear and measurable goals on small time horizons, so they can brag about their successes in a timescale of a career.
We break up the question. What is the ultimate goal? A lot is written about this already. But we need to ask the question: What do we invest in right now? If we are successful with this “right now” question, what new questions will be addressable? Can we link this to our “ultimate goal”? We call this a “value chain”: what now leads to what later. It’s a great prop for taking futuristic thinking into practice. This is exactly how we can still work on 30 year or 50 year or even 100 year projects, while still having a measurable result in smaller time scales.
Member of Technical Staff, In-Q-Tel
JJ Ben-Joseph has spent much of his professional career in the confluence of security and artificial intelligence. He provides trusted advice to upper leadership in government and industry in problems of biosecurity, pandemic response, and artificial intelligence (and a long tail of other topics related to futurology).
At In-Q-Tel B.Next, he guides and invests in artificial intelligence startups to advance biosecurity. He is a Biosecurity Fellow (ELBI) at Johns Hopkins Center for Health Security as well as the Foresight Institute. He makes technical contributions to artificial intelligence projects, mostly in pandemic response.