I want to take issue with "it would take little effort to find 100s of projects at universities across the world that are better versions of these projects", both as a trained biologist (neurobiology), current postdoc, and former entrepreneur.
I share your intuition, I really do. I even said similar things in grad school (and still do, sometimes). But the reality is that:
1. These are not supposed to be projects, they are supposed to be companies creating products. The gulf between "Nature paper" and "something someone will buy" is incredibly long and arduous. Plus, these are VC-backed, meaning there's an expectation of timeline (short) and return (high). These aren't "take $20m from darpa and engage in another four years of R&D" type endeavors. So while they might look trivial scientifically (although I do not think that they do), they have to be working sooner rather than later.
2. "Better versions" is also a tough thing to assess. The people involved matter a lot -- thus even technically superior solutions from very smart people might still not be "better versions". I know many grad students who are much more knowledgable than some of the top data scientists, who nonetheless would fall on their faces if they tried to do a data science startup. Similar for life sciences and biotech.
I think the people who poo-poo academia are largely setting up strawmen -- even Peter Thiel (whose first VC firm, Founders Fund, backed both of my startups) admits that there's a substantial role for government and academic activity in enabling long-term technical innovation.
As biologists, we know just how hard it is to make _anything_ work in this space. Most new drugs fail, most clinical trials fail, most pathways end up being hard to target, etc. etc. Often building a company in the biotech space is like trying to build a microprocessor company where we're still not entirely sure "how the silicon works".
The challenge for YC and other VCs is to identify technologies that are "almost there", and help turn them into companies and products. That's very hard, and I'm not really even sure that we (as academics) are any good at it either.
Will some of them fail? Sure. Will some of them leave the startup scene and maybe go back and do a postdoc or work for an industrial research lab or do another startup, much wiser? Of course. But that hardly seems like a horrible outcome, especially if the scientists learn a lot along the way.
If these biotech and hard-science startups fail, backed by the best startup accelerator on earth, then the effect will be a hard-science investment winter. So there is more at stake than you let on.
I share your intuition, I really do. I even said similar things in grad school (and still do, sometimes). But the reality is that:
1. These are not supposed to be projects, they are supposed to be companies creating products. The gulf between "Nature paper" and "something someone will buy" is incredibly long and arduous. Plus, these are VC-backed, meaning there's an expectation of timeline (short) and return (high). These aren't "take $20m from darpa and engage in another four years of R&D" type endeavors. So while they might look trivial scientifically (although I do not think that they do), they have to be working sooner rather than later.
2. "Better versions" is also a tough thing to assess. The people involved matter a lot -- thus even technically superior solutions from very smart people might still not be "better versions". I know many grad students who are much more knowledgable than some of the top data scientists, who nonetheless would fall on their faces if they tried to do a data science startup. Similar for life sciences and biotech.
I think the people who poo-poo academia are largely setting up strawmen -- even Peter Thiel (whose first VC firm, Founders Fund, backed both of my startups) admits that there's a substantial role for government and academic activity in enabling long-term technical innovation.
As biologists, we know just how hard it is to make _anything_ work in this space. Most new drugs fail, most clinical trials fail, most pathways end up being hard to target, etc. etc. Often building a company in the biotech space is like trying to build a microprocessor company where we're still not entirely sure "how the silicon works".
The challenge for YC and other VCs is to identify technologies that are "almost there", and help turn them into companies and products. That's very hard, and I'm not really even sure that we (as academics) are any good at it either.
Will some of them fail? Sure. Will some of them leave the startup scene and maybe go back and do a postdoc or work for an industrial research lab or do another startup, much wiser? Of course. But that hardly seems like a horrible outcome, especially if the scientists learn a lot along the way.