It may be harder to combine two skills such as sales and engineering, than knowledge in bio and AI, e.g., which are both technical.
The dual PhD problem of today’s startups
21–30 of 126 posts
Re: The dual PhD problem of today’s startups
#22Every week in my inbox, there is [...] Another fintech play for payments and credit cards and personal finance, [...] another cryptocurrency Of course, there are a bunch of new horizons out there [...] Cryptocurrencies and finance. It seems a lot can change two paragraphs on. Life moves pretty fast these days. Edited to add: I reject the central thesis of this article, and pretty every one of the supporting arguments…
Last time I checked, Bitcoin was still trading safely for around $12k.
Re: The dual PhD problem of today’s startups
#23Earlier quoted context omitted.
> and no one understood the applications it would have to future technology until much later on Huh? FHSS was a specific wartime effort with a wartime goal that, aside from that its modern application is mostly civilian, is not terribly distant from its intended use case.
There is actually a whole backstory to people ignoring the idea because she was a woman etc. The navy initially turned down the technology when she presented it. More the the main point I made above- people did not know what they were looking at because they could not think of how important it would be or how it could evolve.
I thought they turned it down because the permittivity of radio through the seawater dielectric made it impractical.
Re: The dual PhD problem of today’s startups
#24Earlier quoted context omitted.
There is actually a whole backstory to people ignoring the idea because she was a woman etc. The navy initially turned down the technology when she presented it. More the the main point I made above- people did not know what they were looking at because they could not think of how important it would be or how it could evolve.
I thought they turned it down because the permittivity of radio through the seawater dielectric made it impractical.
You're correct, and at the frequencies at which permittivity is reasonable, FHSS is much less effective. And Hedy Lamarr was far from the first person to come up with FHSS for communications.
Re: The dual PhD problem of today’s startups
#25The 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 even get to the point where you can get real feedback on the business model.
3 - There are often other considerations e.g. regulations or interactions with existing products, that are entirely outside of the control of the company that can significantly alter the likelihood of success.
Re: The dual PhD problem of today’s startups
#26> 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…
The last two pairs are non-issues, both have plenty of funding. For the former however, one misstep and you have the FDA/DHS or one of state medical unions breathing down your neck.
Re: The dual PhD problem of today’s startups
#27Every week in my inbox, there is [...] Another fintech play for payments and credit cards and personal finance, [...] another cryptocurrency Of course, there are a bunch of new horizons out there [...] Cryptocurrencies and finance. It seems a lot can change two paragraphs on. Life moves pretty fast these days. Edited to add: I reject the central thesis of this article, and pretty every one of the supporting arguments…
This is funny, but to give Danny the benefit of the doubt: he presumably means there are horizons out there in cryptocurrencies and finance that aren't approached by also-ran "fintech plays" or "another cryptocurrency"...
Re: The dual PhD problem of today’s startups
#28Somehow that link redirects me to
https://guce.advertising.com/collectIdentifiers?sessionId=3_...
Re: The dual PhD problem of today’s startups
#29The 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 raise capital now, and that is the exact problem we're running into.
There's a reason for the "janitor as a service" unoriginal ideas--because they're easy to understand, so more likely to be funded. Those kinds of investors are looking for the buzzwords, too, "as a service," "cloud," "social," "AI" that cut off ideas that aren't strictly consumer-facing and infinitely scalable. If you have a modest idea that requires a modest amount of money and targets a modest group of people, you're just not going to hear back from investors. This causes people to have to wrap their idea in buzzwords or lobotomize it into something that allows them to achieve their true goal in a sideways manner.
Re: The dual PhD problem of today’s startups
#30> AI and bio > two very [...] disparate fields They are not, really. The field of bioinformatics exists for almost 20 years, as in, you can degree in it - I almost did myself. And the "informatics" part that you get educated about is pretty much data science, that, by now, uses a lot of ML methods and just like ML requires a very serious math foundation.
That's not a lot of bioinformatics programs that I'm seeing. A lot of bachelors programs seem to focus on teaching almost exclusively the basics of BLAST and all it's boring related algorithms (basically everything in this Coursera course[0]) and their mathematical foundations. Master's programs sometimes are a bit better with a hint of ML, but ultimately most people I've encountered there are still awfully unequipped to tackle ML problems and transfer the advances from mainstream ML to biology/biochemistry problems.
[0]: https://www.coursera.org/specializations/bioinformatics