Here’s a couple of interesting facts:
- Venture investment sentiment on systemic innovation is flighty.
- The long-term competitive value of systemic innovation is profound and stable.
The first fact is very salient these days, but the second one is no less obvious: the difference between the leading organizations, and even societies, and the rest has more to do with long-term fundamental advantages in the sophistication of their physical and intellectual infrastructures than with short-term tactical optimization (which is why they are often resilient to bad decisions, and why defeating an incumbent often requires focused long-term investment in whatever breakthrough innovation they are ignoring: cutting-edge incumbents aren’t defeated, they first stop being cutting-edge without noticing or doing anything about it).
To put it in another way, your valuation is what the market thinks about you, your capabilities are how you stand with respect to Nature. The second is much harder to figure out, more stable, and over time it’s what matters.
There are reasons for this discrepancy, both cultural and infrastructural — although at some level culture is infrastructure and vice versa — but more interestingly, it presents an exploitable competitive opportunity: investments in innovation are universal in optimistic times, giving an advantage to those with large-scale capital deployment capabilities, but they are much rarer in more nervous times, which gives an advantage to those making a committed bet to strategic innovation. Transformative advances require the sort of internal processes of change that can’t be purchased but have to be gone through. They have their own form of compound interest which the Fed has no influence on.
One of the main technological developments going on, below and much beyond the quarterly back and forth of products, scandals, and headlines, is the rise of AI capability near key critical thresholds in areas like biology, basic engineering, the brain, and hyperobject modeling and management – all areas where our current abilities are profoundly constrained by cognitive limitations. Much of what we can’t do, for example, in biology is simply due to the fact that we don’t yet quite have the right artificial minds to fully comprehend and research something as complex and delicate as even a single cell – which necessarily implies that improvements in AI (of the sort we’re currently beginning to see) will have a larger impact on medicine and biotechnology, and therefore our economies and societies, than most people imagine.
The nature and impact of this curve is mostly shaped by the intersection between research paths and the nature of the systems themselves; investment patterns might shift around a bit the timing, and have a large impact on the names of the winners, but not whether it’ll happen or the size of the prize.
This doesn’t mean there’s no value to adaptability: tactical nimbleness is how you survive. But strategic consistency is how you win, and the basic strategy of winning the future by building it first is as valid today as it was last week or three years ago. Whoever writes the story of who won and who lost the decade, and even beyond, won’t be writing about interest rates or financial crisis but about committed bets in cognitive and technological innovation paying off in retroactively inevitable ways.