Can you elaborate more on characteristics that predict successful founders. How easy is it to identify these before the applicants go through the program?
I work at a startup designing synthetic proteins using deep learning: https://www.evozyne.com/. Even though the products my company works on are impactful, due to counterfactuality, I think my impact is through ETG.
You don't need a bio background to work in bio-related ML. Getting a CS degree with some bio-related courses/self-study the side seems enough. Also bioinformatics != bio-ML.
My impression is EAs (especially 80k) think you will make an impact through research only if you are in the top few percent of researchers in the world. I think that is especially hard to achieve in biology (especially wet-lab biology) because:
Success in biology is incredibly resource constrained. So getting into a rich lab is key
Success in biology is much more luck-dependent than other fields. Intelligence is secondary.
Other reasons to not do biology:
Biology postdocs/PhDs work longer and are paid lesser than CS
Feedback cycles in biology have long time windows. This means it can take years to know your project failed. Personally, I found this incredibly demotivating but people’s tolerance for this can differ
Option value for other jobs is worse. If you have a CS degree and decide to leave academia it’s easier to get an industry job than it’s for bio
I second that this is a problem exacerbated by 80,000 hours. For example, I used to work in biomedical research, and 80,000 hours recommends a career path that involves getting a PhD at a top school. I did my PhD in India, which severely limits my career capital. Eventually, I decided to leave research and move to data science to ETG. To be clear, there were other factors involved and I think it's likely that 80,000 hours is correct that it's only worth being in academic research if you are in the top 0.1%. But it is strangely discouraging nonetheless
I looked into LINK earlier this year and had the vague impression that they are not funding constrained since newer security rules during COVID have added too many barriers to attempting rescue.
Can you elaborate more on characteristics that predict successful founders. How easy is it to identify these before the applicants go through the program?
Can I ask why you picked MSI as an example? If I take your argument seriously, is MSI the family planning charity you recommend I donate to?
I work at a startup designing synthetic proteins using deep learning: https://www.evozyne.com/. Even though the products my company works on are impactful, due to counterfactuality, I think my impact is through ETG.
You don't need a bio background to work in bio-related ML. Getting a CS degree with some bio-related courses/self-study the side seems enough. Also bioinformatics != bio-ML.
As a person who was a biologist and now does ML:
My impression is EAs (especially 80k) think you will make an impact through research only if you are in the top few percent of researchers in the world. I think that is especially hard to achieve in biology (especially wet-lab biology) because:
Other reasons to not do biology:
Biology postdocs/PhDs work longer and are paid lesser than CS
Feedback cycles in biology have long time windows. This means it can take years to know your project failed. Personally, I found this incredibly demotivating but people’s tolerance for this can differ
Option value for other jobs is worse. If you have a CS degree and decide to leave academia it’s easier to get an industry job than it’s for bio
I think a stronger case may be made for substituting fish with bivalves, though this is again anecdotal.
I second that this is a problem exacerbated by 80,000 hours. For example, I used to work in biomedical research, and 80,000 hours recommends a career path that involves getting a PhD at a top school. I did my PhD in India, which severely limits my career capital. Eventually, I decided to leave research and move to data science to ETG. To be clear, there were other factors involved and I think it's likely that 80,000 hours is correct that it's only worth being in academic research if you are in the top 0.1%. But it is strangely discouraging nonetheless
There is a list here where I see "Front-end web development" and "back-end web development
Interesting example of pro-GMO farmers here
How do I make cause area restricted donations?
I looked into LINK earlier this year and had the vague impression that they are not funding constrained since newer security rules during COVID have added too many barriers to attempting rescue.