Interesting piece! The types of companies you talk about fostering make me think of the the German Mittelstand companies, which are often highly technical, innovative and focused on dominating niche markets. They also create mutual interdependence between the company and its employees. I think the American way of creating would be employee options, which it seems to me are underused outside of the startup/tech world.
Interesting writing and ideas! Nonetheless, as a deep tech VC allow me to tell you that, per your last lines on recommending us how to allocate "a massive amount of time", we tend to be good at telling a founder if their idea is good or bad, and investing in it in consequence. However, we are not usually good at producing innovative ideas of our own; much less to feeding them into academia to steer research topics. That may be a work better performed by incumbents or customers, who are more directly in contact with the several pains to solve in an industry. Another story is to be asked about concrete research subjects and what their expected impacts in industry could be.
Great piece! One big reason that I think any sort of deep tech VC won't be successful is that most of the economic profit derived from deep tech innovations is not actually captured by the inventors. Bell labs invented the transistor, and they captured an epsilon of the profit from the subsequent creation of the computer industry. As you note, any VC will have to acknowledge that investing in deep tech will be a worse proposition than normal other investments, and they will have to be OK with some other companies will take advantage of the inventions in which they invested to make many multiples more than they will.
This is a really great analysis of market differences between software and hard tech! Agree that there isn't really any institution out there that's doing this yet, but I think VC's are definitely experimenting with new models for deep tech. Several that might be of interest and are similar to some of the tamer takeaways (and would be curious for reactions):
- Activate (supports scientists for two years to develop ideas, with funding and national lab support) https://www.activate.org/
- Nucleate (community-run, non-equity, startup accelerator for bio PhD students) https://nucleate.xyz/
Agree that none of these models have that exact combination of pre-problem discovery entry for graduate students and institutional funding/support for actually solving engineering problems first through consulting that you describe though.
Interesting piece! The types of companies you talk about fostering make me think of the the German Mittelstand companies, which are often highly technical, innovative and focused on dominating niche markets. They also create mutual interdependence between the company and its employees. I think the American way of creating would be employee options, which it seems to me are underused outside of the startup/tech world.
Interesting writing and ideas! Nonetheless, as a deep tech VC allow me to tell you that, per your last lines on recommending us how to allocate "a massive amount of time", we tend to be good at telling a founder if their idea is good or bad, and investing in it in consequence. However, we are not usually good at producing innovative ideas of our own; much less to feeding them into academia to steer research topics. That may be a work better performed by incumbents or customers, who are more directly in contact with the several pains to solve in an industry. Another story is to be asked about concrete research subjects and what their expected impacts in industry could be.
Great piece! One big reason that I think any sort of deep tech VC won't be successful is that most of the economic profit derived from deep tech innovations is not actually captured by the inventors. Bell labs invented the transistor, and they captured an epsilon of the profit from the subsequent creation of the computer industry. As you note, any VC will have to acknowledge that investing in deep tech will be a worse proposition than normal other investments, and they will have to be OK with some other companies will take advantage of the inventions in which they invested to make many multiples more than they will.
This is a really great analysis of market differences between software and hard tech! Agree that there isn't really any institution out there that's doing this yet, but I think VC's are definitely experimenting with new models for deep tech. Several that might be of interest and are similar to some of the tamer takeaways (and would be curious for reactions):
- Deep Science Ventures fully funded PhD program (get your phd through doing problem discovery with a VC) https://deepscienceventures.com/venture-science-doctorate
- Fifty Years PhD to VC night-class basically https://deepscienceventures.com/venture-science-doctorate
- Activate (supports scientists for two years to develop ideas, with funding and national lab support) https://www.activate.org/
- Nucleate (community-run, non-equity, startup accelerator for bio PhD students) https://nucleate.xyz/
Agree that none of these models have that exact combination of pre-problem discovery entry for graduate students and institutional funding/support for actually solving engineering problems first through consulting that you describe though.