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The dual PhD problem of today’s startups

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Re: The dual PhD problem of today’s startups

#41

Post by Igelau »

Andyfilms wrote: post #29
woeirua wrote: post #25

The reason you don't see more startups in the hard sciences is not due to the lack of hybrid talent as this article surmises. It's because: 1 - VCs are reluctant to fund capital intensive startups that have time horizons for exits that are significantly longer than software based startups. 2 - The product lifecycle is so much longer, which makes it inherently much riskier. In many cases it can be years before you eve…

This, 100%. The author says how difficult it is for multidisciplinary teams to come together when they don't understand each others skillsets--but the same applies to the investors themselves. When you start talking about these complicated ideas, there comes a point where unless the investor is involved in the industry they're investing in, they simply won't understand the true impact of it. My company is trying to r…

> janitor as a service

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Re: The dual PhD problem of today’s startups

#42

Post by ryan_j_naughton »

Igelau wrote: post #41
Andyfilms wrote: post #29

Earlier quoted context omitted.

This, 100%. The author says how difficult it is for multidisciplinary teams to come together when they don't understand each others skillsets--but the same applies to the investors themselves. When you start talking about these complicated ideas, there comes a point where unless the investor is involved in the industry they're investing in, they simply won't understand the true impact of it. My company is trying to r…

> janitor as a service Tired of trusting the flimsy log sheet on the door to know when your custodial staff last cleaned the bathroom? We present: Toiletherium. A cryptocurrency-backed suite of apps and IoT devices that turns real cleaning into real consensus. Our state of the art MopMine equation incorporates real sweat and toil recorded by SmartMops into mining the next block. Pit teams against teams with MopSync,…

Brilliant. The dystopia we find ourselves in is palpable. Your language drives home the insanity of our times because not only is this product absurd but also believable.

Re: The dual PhD problem of today’s startups

#43

Post by Metacelsus »

dnautics wrote: post #36
woeirua wrote: post #25

The reason you don't see more startups in the hard sciences is not due to the lack of hybrid talent as this article surmises. It's because: 1 - VCs are reluctant to fund capital intensive startups that have time horizons for exits that are significantly longer than software based startups. 2 - The product lifecycle is so much longer, which makes it inherently much riskier. In many cases it can be years before you eve…

It's 1. But also, who can blame them. I've seen really stupid companies come out of biotech incubators, including one that was peddling a genetically modified probiotic whose concoction as designed is known to be ineffective pharmacologically (and an equivalent reformulation strategy is not known in their host species), and a company that demoed reconstituted mock vegan meringues that had residual trifluoroacetic aci…

>a company that demoed reconstituted mock vegan meringues that had residual trifluoroacetic acid in their demo day samples

Yikes! I've had some protein preps go wrong, but never this wrong!

Re: The dual PhD problem of today’s startups

#44

Post by asdff »

digitallogic wrote: post #15

> Today’s startups have a biologist talking about wet labs on one side and an AI specialist waxing on about GPT-3 on the other, or a cryptography expert negotiating their point of view with a securities attorney. There is constant and serious translation required between these domains, translation that (I would argue mostly) prevents the fusion these fields need in order for new startups to be built. Is that all that…

As someone from an academic background, it's a bit different than how academic labs are set up. My academic lab had a number of different projects in different research areas, ranging from human health to agriculture, but the unifying theme was big data analysis. The fact we all had this focal point meant we often had shared overlap with common tooling, which meant a lot of collaboration. Whether it was for alzheimers susceptibility or corn yields, you were working with tabular data.

Sure, we had people worked more on the bench and people who never set foot in the lab, but everyone made sure to know exactly how their data came into their hands and it's purpose, so if you were a statistician, you would learn everything about the corn sample you were given to analyze so you could make the correct considerations in your analysis. And if you were that wet lab person and wanted to present a figure that the statistician generated, you would learn everything about the test used, and all the assumptions made when choosing that method of analysis over others. Even in academia, this high level of collaborative interdisciplinary learning can be rare, but makes you a much better scientist who as a much better grasp on the wider project and your role to play.

I think a lot of startups operate with a mercenary mindset. Everyone is hired to play a discrete non-overlapping role, which tends to silo ideas. Central planning from upon high is also the norm, rather than collaborative discussion and solving problems from the bench up.

Depressingly, there are more and more big name academic labs that are adopting this startup oriented top down approach, with a head professor calling the shots and giving marching orders to a few sub research professors with their own postdocs, and grad students, and undergrads. I've known grad students and post docs in these labs who are outright denied to direct the research in their own projects, even if they have good ideas, simply because they didn't come from the top down. Pursuing your own ideas is the whole point of grad school and post doctoral training. On top of that, these labs siphon funding from more innovative and smaller groups by outputting higher numbers of ho hum papers, or affording expensive research with large, multi-institutional grants, both of which are heavily favored metrics in the grant proposal and tenure process.

Re: The dual PhD problem of today’s startups

#45

Post by sushshshsh »

ryan_j_naughton wrote: post #42
Igelau wrote: post #41

Earlier quoted context omitted.

> janitor as a service Tired of trusting the flimsy log sheet on the door to know when your custodial staff last cleaned the bathroom? We present: Toiletherium. A cryptocurrency-backed suite of apps and IoT devices that turns real cleaning into real consensus. Our state of the art MopMine equation incorporates real sweat and toil recorded by SmartMops into mining the next block. Pit teams against teams with MopSync,…

Brilliant. The dystopia we find ourselves in is palpable. Your language drives home the insanity of our times because not only is this product absurd but also believable.

When janitors are automated away by coronavirus, will we also need to teach the robots how to write on paper and read handwriting on paper?

Re: The dual PhD problem of today’s startups

#46

Post by haihaibye »

pontus wrote: post #32

The article misses the point, I think. The reason why (most, not all!) VCs are successful is not because they have some secret visionary insights into the future of technology but rather because they have the means of diversifying their investments in things that are more or less guaranteed to happen. Will work be more decentralized in 10 years than it is today? Yes. Will financial institutions move away from the arc…

>> Will work be more decentralized in 10 years than it is today? Yes.

That's a big call during an unprecedented work from home pandemic.

Re: The dual PhD problem of today’s startups

#47

Post by Igelau »

dnautics wrote: post #36
woeirua wrote: post #25

The reason you don't see more startups in the hard sciences is not due to the lack of hybrid talent as this article surmises. It's because: 1 - VCs are reluctant to fund capital intensive startups that have time horizons for exits that are significantly longer than software based startups. 2 - The product lifecycle is so much longer, which makes it inherently much riskier. In many cases it can be years before you eve…

It's 1. But also, who can blame them. I've seen really stupid companies come out of biotech incubators, including one that was peddling a genetically modified probiotic whose concoction as designed is known to be ineffective pharmacologically (and an equivalent reformulation strategy is not known in their host species), and a company that demoed reconstituted mock vegan meringues that had residual trifluoroacetic aci…

We're kind of like Uber but instead of calling a car for yourself, you call a deadly pie for your enemies. Our drivers are incentivized by the rating system to operate with discretion that beats similar state-sanctioned programs. Launch flavors include Rhubarb, Almost Almond, and Death by Chocolate.

Re: The dual PhD problem of today’s startups

#48

Post by austinl »

woeirua wrote: post #25

The reason you don't see more startups in the hard sciences is not due to the lack of hybrid talent as this article surmises. It's because: 1 - VCs are reluctant to fund capital intensive startups that have time horizons for exits that are significantly longer than software based startups. 2 - The product lifecycle is so much longer, which makes it inherently much riskier. In many cases it can be years before you eve…

Another reason we see duplicate startups within a few domains is that there are many VCs, and each wants to have a horse in the race.

Perhaps they missed on one fintech company, and now it's grown enough to make the market. So they lead an investment in a competitor, or a company in a similar space. This significantly de-risks the investment vs. allocating money towards something entirely new.

Re: The dual PhD problem of today’s startups

#49

Post by dnautics »

Metacelsus wrote: post #43
dnautics wrote: post #36

Earlier quoted context omitted.

It's 1. But also, who can blame them. I've seen really stupid companies come out of biotech incubators, including one that was peddling a genetically modified probiotic whose concoction as designed is known to be ineffective pharmacologically (and an equivalent reformulation strategy is not known in their host species), and a company that demoed reconstituted mock vegan meringues that had residual trifluoroacetic aci…

>a company that demoed reconstituted mock vegan meringues that had residual trifluoroacetic acid in their demo day samples Yikes! I've had some protein preps go wrong, but never this wrong!

if you've ever done an hplc with triflouracetic acid, I promise you there's residual tfa in there, even after a round of lyophilization. Though typically I'm not putting HPLC preps in my mouth. The burney/tingley sensation on my tongue was unmistakable and very reminiscent of the residual feel you get after pipetting 100% TFA in the hood.

I strongly believe that this startup did not know that about TFA, but it's basic common knowledge if you're in a reputable protein biochemistry lab (and you're paying attention). When you're moving fast to show something for demo day, you're going to use whatever you have around to do your protein preps, because TFA is standard practice.

Anyways, if any VCs want a Burton Guster to super sniff questionable biotechs, I'd be happy to do a bit of consulting on the side.

Re: The dual PhD problem of today’s startups

#50

Post by sorethescore »

woeirua wrote: post #25

The reason you don't see more startups in the hard sciences is not due to the lack of hybrid talent as this article surmises. It's because: 1 - VCs are reluctant to fund capital intensive startups that have time horizons for exits that are significantly longer than software based startups. 2 - The product lifecycle is so much longer, which makes it inherently much riskier. In many cases it can be years before you eve…

This is so true. A mentor of mine has been developing a new cancer therapy with a physicist for over a decade. He's spent millions of dollars and all he has to show for it at this point is a machine for rats that can kill cancer better than the standard of care, for rats. He's building a machine for humans now but by the time he's done he'll have probably invested close to $10M all by himself just to have a single proof of concept that he can take to market. That's an insane amount of investment until as you said, you even get to the point where you can get real feedback on the business model. Ultimately though he understood the fundamental physics and knew that it would work just as well as anyone could.
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