> The technologies behind computer networking that ultimately resulted in the internet were funded by DARPA starting in the 1950s.
Much of it came from the telegraph network that had been developed in the previous century. See "The Victorian Internet" by Standage.
Also, in the 1970s working on computers, everybody with two computers invented ways to hook them together, i.e. invented networking. Many became commercial, like Compuserve and MCImail, some became free, like the BBS systems. Then there's Ethernet and TokenRing for LAN networks.
(Note that DARPA figured out how to connect two computers as soon as they had two. It's just inevitable, not something coming from nowhere. Given two computers and the telephone lines, inventing a way to network them is going to happen in short order, just as water flows downhill.)
I hadn't even dared to think that Sturgeon's Law might apply to output in the field of science. Yikes.
"Anyway, science right now is in an existential crisis. This is a real, real issue, and there’s now a generation of scientists who specialize in pointing this out and analyzing it. Andrew Gelman and others. I’ll give you an example: I had a conversation with the long-time head of one of the big federal funding agencies for healthcare research who is also a very accomplished entrepreneur, and I said, “do you really think it’s true that 50-70% of biomedical research is fake?” This is a guy who has spent his life in this world. And he said “oh no, that’s not true at all. It’s 90%.” [Richard laughs]. I was like “holy shit,” I was flabbergasted that it could be 90%.
He’s like “well look, 90% of everything is shit”, which is literally this thing called Sturgeon’s law which says that 90% of everything is bad. 90% of every novel written is bad, 90% of music, 90% of art… 90% of everything is bad. So his analysis was, anything you get in the field of medical experimentation, biomedical development, and this is going to be true of any field, there’s like five labs total in the world that are really good at what they’re doing and doing really cutting edge work. And this is true of quantum computing; pick any field for advanced technology you want.
So those five labs have a pretty good shot at doing interesting work, even some of that is going to reproduce and some of it isn’t. But once you get out of those top five labs, it’s pretty much make-work, incremental, marginal improvements at best, and a complete waste of time otherwise. And I said “good God, why does the other 90% continue to get funded if you know this?” And he said, “well, there are all these universities and professors who have tenure, there are all these journals, there are all these systems and people have been promised lifetime employment.” Anyway, a longwinded way of saying that we have pretty serious structural and incentive problems in the research complex. "
I believe, this is how scaling works, and exactly the price we pay to afford the top-notch. In any given field, company, pro sport team, there are top 10% labs/groups/players that matters the most. However, to make the 10% emerge, there has to be a pyramid where the rest 90% is responsible for forming a stable infrastructure. Then it comes down to how well we can design the pyramid. Our result should be evaluated not by how thin we cut down the infrastructure, but how easy we make top-players emerge.
On another note, I have seen small no-name labs published impactful scientific results, and then went back to stealth mode again. It's super cool. Science labs, unlike a business entity, should not be measured by recurrent revenue and growth.
Yes, but this sturgeons law (maybe less extreme extent) often applies to within labs or within scientists as well.
Newton did first rate work, but he also spent a lot of time working on alchemy and theology which didn’t get anywhere.
Research grants are generally competitive, if you haven’t shown you’ve ever done something my significant or haven’t done something significant in a long time, it is difficult to survive. But indeed even the top scientists spend a lot of time on dead ends.
It is true that often only top 5 labs or so doing good work, but those top 5 labs are not constant over time, they wax and wane like fashion trends.
The lesson is just because over last few years the top work came from only a few labs, it’s premature to eliminate all other labs because those top labs could be lower in the next cycle.
Not only this, but it appears to me that diagnoses of the state of science as a problem are making the classic problem a person like Andrew Gelman would usually quickly point out, which is ignoring base rates. Saying 70% of published research can't replicate sounds bad in a vacuum, but how does that compare to 50 years ago? We have no idea if this number that sounds terrible outside of any context represents an improvement, degradation, or no difference at all from what we should expect.
That isn't by any means to suggest we shouldn't try to make science better by being more replicable and reducing fraud, but if it is an improvement, we're already doing something right and there is far less cause for despair and cynicism.
It also, of course, doesn't do any base rate comparison to non-scientific ways of generating facts. If 90% of published psychology research turns out to be wrong, but 99% of folk psychology turns out to be wrong, then science is still winning there.
Interesting. Marc is a nuanced guy of course but I sense he may have shifted in the last while. I recall in his 1:1 w/ Peter Thiel he took the opposing side of this argument. Peter does not mince words re: the progress of "science". Perhaps Marc was just doing it for the sake of discussion.
Playing with some numbers... here's an interesting way setting a bar for publication can backfire: if you don't publish negative results, and you define positive results as 0.05-level, you're going to greatly inflate the amount of false-positives you publish, in fields that rely on statistical significance.
(Fudging here around the 0.05 threshold threshold, since stuff on that boundary is the most likely to produce false positives, not sure what how to use a more realistic range... I think this would just be upper-bound on false positives? Please correct/clarify if your probability/statistics knowledge here is deeper than mine!)
Let's say twenty different researchers have a similar idea, they all pursue it, and one of them gets (un)lucky and gets apparently statistically significant results. They're the only ones that try to publish, and nobody ever has the knowledge that it only worked 1 time out of 20 (or more?) - even the people who's experiments failed who see it are only aware of their own attempt, and maybe they just messed something up.
Let's say 90% of all published results are non-reproducible. What sort of pipeline would be required to create that? For every reproducible, significant finding, there are 9 false-positives. For each of those false-positives there were 19 true-negatives. So about 1 out of 180 research attempts are reproducible truly-meaningful novel results. Does that sound reasonable? It's hard, right, especially to keep finding new things on top of everyone else's continued progress too? But it isn't necessarily malicious or fraudulent every step of the way - we just have our system structured in a way that biases in favor of creating false positives.
(Put in other numbers, say 10% of all research has significant results, then 90% of it doesn't, and at the 0.05 level, that's still (up to?) 4.5 false positives for every 10 truly statistically significant things, meaning close to 1 out of every 3 papers would still be expected to be a false positive.)
Publishing negative results would require a bigger publication industry, and more people spending more time filtering through it all, but you'd at least be able to compare to the literature to say "this looks like it worked, but ... it hasn't ever worked for anyone else."
People look to get 3 things in a job: Compensation, Interest and Reputation.
The professor is a researcher who teaches. However, they do not want to merely be a teacher. Especially when it comes with a substantial pay cut in comparison to the industry. So, you offer them repute and interest by giving tenure and something to research. The university gets a better teacher for cheap and the professor gets an inflated sense of ego and self-actualization.
From the student's point of view, it opens up alternate avenues for promotion. If only the top 5 labs get funded enough to do good work, then entering those top 5 labs early is absolutely essential. Anyone who doesn't get on the bandwagon early, will be left to the wolves like medical residencies. It will greatly exacerbate the competition in standardized exams and sideline students who don't abide by a rigid template early in life. (eg: a lot of friends went to tier 2 universities for their masters, did excellent work and got into the top 5 labs purely because the top 50 lab was funded enough for them to make up for lost time early in life)
I have also seen lab impact scores jump around substantially enough, that while the 90% hypothesis may be true, we have no way to picking out who will create the 10% that's gold. While half of the 10% might get reliably produced by the top 5 labs. The other half can be notoriously hard to pin down. You will see this in top industry groups (MSR, Brain) that hire exclusively out of the top 5 labs. Even there, the 90% number holds, despite there being a hiring system specifically built for capitalistic impact.
On the flip side, any academic field whose employability exists only within academia is a dictionary-definition pyramid scheme. It is a common accusation that's correctly levied on the liberal arts, but STEM should not be immune to it.
It should be point out that Marc Andreessen of all people should deeply believe Sturgeon's law - after all, return on investment for venture firms are dominated by few 'hits' and lots of 'duds'.
Of course - I think if anyone act on the belief that 90% of their bets are duds, they would not be in the venture business. It's really interesting that a process could lead to a distribution - but knowing the outcome distribution is actually...useless?
> So those five labs have a pretty good shot at doing interesting work, even some of that is going to reproduce and some of it isn’t. But once you get out of those top five labs, it’s pretty much make-work, incremental, marginal improvements at best, and a complete waste of time otherwise. And I said “good God, why does the other 90% continue to get funded if you know this?” And he said, “well, there are all these universities and professors who have tenure, there are all these journals, there are all these systems and people have been promised lifetime employment.” Anyway, a longwinded way of saying that we have pretty serious structural and incentive problems in the research complex. "
This seems like an non-thorough and fairly uninteresting answer to the question.
I would want to know how much useful-but-not-groundbreaking stuff still comes out of the "make work" crowd, how wide you need the funnel to be at the top to make sure you catch the people who can end up in the top labs and who make breakthroughs, how much of a "safety net" that you need to make sure people are motivated to jump into the funnel in the first place rather than going into something safer, etc.
A world where we have fewer "wasteful" make-work research jobs but also have fewer breakthroughs isn't great. Hell, you could call the majority of today's service- and information-oriented non-academic jobs "make-work" too (let's up those clickthrough rates! let's stream this video in 8k instead of 4k! let's move this money around slightly faster!). So is there necessarily much utility in moving "make-work" researchers into other fields?
it's all about incentives, the modern academic system has the incentives all wrong for creating innovation and quality work. Replication crisis is just a symptom of the real problem
> So those five labs have a pretty good shot at doing interesting work, even some of that is going to reproduce and some of it isn’t. But once you get out of those top five labs, it’s pretty much make-work, incremental, marginal improvements at best, and a complete waste of time otherwise. And I said “good God, why does the other 90% continue to get funded if you know this?” And he said, “well, there are all these universities and professors who have tenure, there are all these journals, there are all these systems and people have been promised lifetime employment.” Anyway, a longwinded way of saying that we have pretty serious structural and incentive problems in the research complex. "
You need to fund avenues that don't look promising now. Some new developments may make them good. E.g. deep learning before 2011.
It is also difficult to identify who is doing good work a priori and there’s also the out of left field work which proves successful despite being a no name. You also train new scientists etc…. I think most noble prizes are from people whose research was initially discounted.
> So his analysis was, anything you get in the field of medical experimentation, biomedical development, and this is going to be true of any field, there’s like five labs total in the world that are really good at what they’re doing and doing really cutting edge work. And this is true of quantum computing; pick any field for advanced technology you want.
That's also true for software engineers. A handful of 10x can carry a company a long way.
As if we are capable of determining who is doing the top 10% best science and are not glued to the 10% most shining project according to the fad of the day.
I don't see a better system. Maybe I'm misunderstanding his or your point. To me this is essentially capitalism. 90% or more of businesses fail, and of those that don't, 90% or more suck. But if you tried to call that 99% "waste" that could be avoided by only running the good business, you would fail miserably. Research is exactly the same. We can't just identify and fund the good research.
(But this should be obvious to a VC so I may be reading it wrong)
> He’s like “well look, 90% of everything is shit”
I think there is a difference between "being shit" and "being fake" though. 'do you really think it’s true that 50-70% of biomedical research is fake?'
Fake seems more insidious and problematic.
Also this brings up a very troubling issue. If 90% of the "research is fake/shit" and lets say that means that 90% of the researchers are "fake/shit", then it means that 'scientific' consensus is also likely "fake/shit".
This is why I'm always skeptical of 'scientific' consensus. Science is about evidence, testing, etc. Not consensus - which is the realm of politics, law, etc.
And I'd suspect 99.99% of social 'sciences' is probably 'fake/shit' and that is used to push/change society/government/etc.
> So it’s very hard to make time scales match for 20-year intellectual journeys.
Xerox did it with the copy machine. Which then remade the business world. They did it again with the user interface, though it was Apple that capitalized on it.
Frank Whittle soldiered on for many years trying to invent the jet engine, funded by venture capitalism at the time. The government wasn't interested until he demonstrated flying jet aircraft. In the meantime the US government shut down Lockheed's nascent jet engine project.
> I think it’s possible we as a society spent 50 years assembling these systems and these games in the first half the 20th century, and then we spent the last half of the 20th century gaming the games.
Interesting perception, seems to have explanatory power. I’ll note that building games and gaming them has accelerated with tech. (Facebook, Tiktok, Amazon, REvil, Robinhood.) These aren’t institutional games, these are societal games. Different and fluid yet roughly defined groups.
The super elite hypothesis is interesting, in that it lacks a plausible mechanism. By and large you would expect that educating and equipping more people would produce more progress in any field, up until there is more coordination tax than benefit from adding more people.
Is it possible that the sciences and other fields have exceptionally high coordination taxes? Or is it likely that we’ve structured them such that only a small number of slots exist for people to move the needle.
The latter seems eminently true given the finite number of conference slots and the former seems true given the the need to convince more people of a given direction.
If such a dynamic exists than the advent of communication technologies may actually hamper forward progress due to elimination of smaller research networks.
> Marc: I think there’s a real argument, and this is the most uncomfortable form of argument, there is a real argument that there are just a certain number of super-elite people.
I really enjoy it when people say exactly what they think.
It's not a brave or iconoclastic thought; it's actually incredibly common: Throughout history the wealthy have thought of themselves as superior.
If they got lucky, it was because they were "super-elite." No one's going to win a nurture-or-nature argument but there's a clear self-interest in these situations to call nature what was, at least in part, nurture.
The only way the statement could be false would be for everyone to be at the same level of skill/knowledge/aptitude/etc. but there's clearly some non-uniform distribution and regardless of where you draw the line to define super-elite, some people will fall in that group.
I can't tell whether these types of guys are totally ignorant of concepts like the Nietzschean Übermensch or whether they're just careful to avoid referring to it too directly.
I like what strongtowns has to say on the topic. Also, it does seem like circumstances bringing people together for some amount of time seems necessary for bonding.
It's difficult to speak off-the-cuff on any topic that might come up in an interview, but I expected better than 'at least it's not boring' about QAnon when attempting to reply on the social impacts of technology.
Social media definitely has negative impacts (e.g. directly tied to mobs in India and Burma) and positive impacts (so much easier to stay connected across the world) - it would've been 'interesting' to hear a more nuanced take from one of the inventors of the modern internet
> Traditionally if I wanted to work at a company in another country I would have to go to that country. I’d have to be an immigrant from my country, at least for a while. In a world of remote work and Zoom and Slack, I can now work for people anywhere in the world. I can work for companies doing any kind of knowledge work. Immigration policies apply to the atoms of human beings, they don’t apply to the bits. I can go to work for some company anywhere in the world if it’s a remote-friendly company. I may never travel there, I may never have to travel there.
Marc Andreessen is getting very close to saying the quiet part out loud. This is the clearest statement I've seen to date from a venture capitalist that white collar offshoring is almost certainly going to accelerate due to the shift towards remote work brought on by the pandemic.
Well, it's a free market (for capital, but even then not really, but close enough for rhetorical purposes). Outcompete those offshore workers, there was never any other option.
> Marc Andreessen is getting very close to saying the quiet part out loud. This is the clearest statement I've seen to date from a venture capitalist that white collar offshoring is almost certainly going to accelerate due to the shift towards remote work brought on by the pandemic.
If anyone isn't hiring international remote right now they are losing a huge opportunity. Lots of people are looking at jumping ships, and western companies can outbid almost anyone for top talent.
Genuinely curious question: how does something come to be defined as cutting edge? Is it more of a feeling when someone is working on something that just seems so far away from the norm? Is everyone who is researching ways to cure cancer on the cutting edge, or is it a very small subset of that group? Is it defined by how close someone is to actually achieving a discovery?
> you can see in the data the scandals cause people to use them more.
I often wonder if all that negative press about leaks, facebook's privacy violations etc. are just publicity stunts. So many tech articles seeking outrage and smell of fake.
One of my big career disappointments was having a meeting with Marc Andreessen with regard to a project he needed us for, not as an "investee". I didn't idolize him or anything before that but I had it in mind that he would at least have something to offer. In our conversation I realized almost immediately he was a total buffoon and had just been in the right place at the right time.
Ok, but please let's not go into unsubstantive personal attack in HN threads. Maybe you don't owe that person better but you owe this community better if you're participating here.
> In our conversation I realized almost immediately he was a total buffoon and had just been in the right place at the right time.
Sometimes it takes a while, and some deep context, and then some more context, ideally in a different set of circumstances, before you can assess someone's capabilities fairly.
Some people shine in their specialty domain, and flail outside of it.
Others are good in fair weather, but fragile in a crisis. Others are kind of the opposite, losing steam day to day, but rising to the occasion when shit happens.
Seasoned salespeople know all this. They do well consistently in spite of it all by presenting themselves credibly irrespective of their competency in any domain. They dress right for their audience, and they speak persuasively, always mindful of what their audience wants and needs to hear.
But listen to Andreesen talk! He sounds like he's never had to learn how to persuade anybody of anything. Well, not any regular people.
> Moderna, which innovated the concept of mRNA vaccines, it was a classic venture capital company. That company would not have existed without venture capital, these vaccines would not exist without venture capital.
Interesting. I commonly hear asserted that breakthrough fundamental inventions don't come from capitalism.
The fundamental inventions on mRNA vaccines were grant-funded academic work. But I don't know that anyone asserts that breakthrough inventions don't come from capitalism, certainly in the 19th and early 20th century many inventions were created by individual entrepreneurs, for example the Wright Brothers.
[+] [-] WalterBright|4 years ago|reply
Much of it came from the telegraph network that had been developed in the previous century. See "The Victorian Internet" by Standage.
Also, in the 1970s working on computers, everybody with two computers invented ways to hook them together, i.e. invented networking. Many became commercial, like Compuserve and MCImail, some became free, like the BBS systems. Then there's Ethernet and TokenRing for LAN networks.
(Note that DARPA figured out how to connect two computers as soon as they had two. It's just inevitable, not something coming from nowhere. Given two computers and the telephone lines, inventing a way to network them is going to happen in short order, just as water flows downhill.)
We'd have had an internet one way or another.
[+] [-] zepto|4 years ago|reply
Then DARPA contribution was literally to work out how to connect separate networks together into a practical wide area network.
The internet is a network of networks.
We would of course have had one in some form. The one we have is based on DARPA’s.
[+] [-] dboreham|4 years ago|reply
[+] [-] bastawhiz|4 years ago|reply
https://www.cybertelecom.org/notes/telegraph.htm
[+] [-] hncurious|4 years ago|reply
"Anyway, science right now is in an existential crisis. This is a real, real issue, and there’s now a generation of scientists who specialize in pointing this out and analyzing it. Andrew Gelman and others. I’ll give you an example: I had a conversation with the long-time head of one of the big federal funding agencies for healthcare research who is also a very accomplished entrepreneur, and I said, “do you really think it’s true that 50-70% of biomedical research is fake?” This is a guy who has spent his life in this world. And he said “oh no, that’s not true at all. It’s 90%.” [Richard laughs]. I was like “holy shit,” I was flabbergasted that it could be 90%.
He’s like “well look, 90% of everything is shit”, which is literally this thing called Sturgeon’s law which says that 90% of everything is bad. 90% of every novel written is bad, 90% of music, 90% of art… 90% of everything is bad. So his analysis was, anything you get in the field of medical experimentation, biomedical development, and this is going to be true of any field, there’s like five labs total in the world that are really good at what they’re doing and doing really cutting edge work. And this is true of quantum computing; pick any field for advanced technology you want.
So those five labs have a pretty good shot at doing interesting work, even some of that is going to reproduce and some of it isn’t. But once you get out of those top five labs, it’s pretty much make-work, incremental, marginal improvements at best, and a complete waste of time otherwise. And I said “good God, why does the other 90% continue to get funded if you know this?” And he said, “well, there are all these universities and professors who have tenure, there are all these journals, there are all these systems and people have been promised lifetime employment.” Anyway, a longwinded way of saying that we have pretty serious structural and incentive problems in the research complex. "
[+] [-] helixc|4 years ago|reply
On another note, I have seen small no-name labs published impactful scientific results, and then went back to stealth mode again. It's super cool. Science labs, unlike a business entity, should not be measured by recurrent revenue and growth.
[+] [-] j7ake|4 years ago|reply
Newton did first rate work, but he also spent a lot of time working on alchemy and theology which didn’t get anywhere.
Research grants are generally competitive, if you haven’t shown you’ve ever done something my significant or haven’t done something significant in a long time, it is difficult to survive. But indeed even the top scientists spend a lot of time on dead ends.
It is true that often only top 5 labs or so doing good work, but those top 5 labs are not constant over time, they wax and wane like fashion trends.
The lesson is just because over last few years the top work came from only a few labs, it’s premature to eliminate all other labs because those top labs could be lower in the next cycle.
[+] [-] petermcneeley|4 years ago|reply
This law seems to lack any kind of rigor or theoretical basis and seems like a purely rhetorical device.
[+] [-] nonameiguess|4 years ago|reply
That isn't by any means to suggest we shouldn't try to make science better by being more replicable and reducing fraud, but if it is an improvement, we're already doing something right and there is far less cause for despair and cynicism.
It also, of course, doesn't do any base rate comparison to non-scientific ways of generating facts. If 90% of published psychology research turns out to be wrong, but 99% of folk psychology turns out to be wrong, then science is still winning there.
[+] [-] u385639|4 years ago|reply
[+] [-] majormajor|4 years ago|reply
(Fudging here around the 0.05 threshold threshold, since stuff on that boundary is the most likely to produce false positives, not sure what how to use a more realistic range... I think this would just be upper-bound on false positives? Please correct/clarify if your probability/statistics knowledge here is deeper than mine!)
Let's say twenty different researchers have a similar idea, they all pursue it, and one of them gets (un)lucky and gets apparently statistically significant results. They're the only ones that try to publish, and nobody ever has the knowledge that it only worked 1 time out of 20 (or more?) - even the people who's experiments failed who see it are only aware of their own attempt, and maybe they just messed something up.
Let's say 90% of all published results are non-reproducible. What sort of pipeline would be required to create that? For every reproducible, significant finding, there are 9 false-positives. For each of those false-positives there were 19 true-negatives. So about 1 out of 180 research attempts are reproducible truly-meaningful novel results. Does that sound reasonable? It's hard, right, especially to keep finding new things on top of everyone else's continued progress too? But it isn't necessarily malicious or fraudulent every step of the way - we just have our system structured in a way that biases in favor of creating false positives.
(Put in other numbers, say 10% of all research has significant results, then 90% of it doesn't, and at the 0.05 level, that's still (up to?) 4.5 false positives for every 10 truly statistically significant things, meaning close to 1 out of every 3 papers would still be expected to be a false positive.)
Publishing negative results would require a bigger publication industry, and more people spending more time filtering through it all, but you'd at least be able to compare to the literature to say "this looks like it worked, but ... it hasn't ever worked for anyone else."
[+] [-] screye|4 years ago|reply
People look to get 3 things in a job: Compensation, Interest and Reputation.
The professor is a researcher who teaches. However, they do not want to merely be a teacher. Especially when it comes with a substantial pay cut in comparison to the industry. So, you offer them repute and interest by giving tenure and something to research. The university gets a better teacher for cheap and the professor gets an inflated sense of ego and self-actualization.
From the student's point of view, it opens up alternate avenues for promotion. If only the top 5 labs get funded enough to do good work, then entering those top 5 labs early is absolutely essential. Anyone who doesn't get on the bandwagon early, will be left to the wolves like medical residencies. It will greatly exacerbate the competition in standardized exams and sideline students who don't abide by a rigid template early in life. (eg: a lot of friends went to tier 2 universities for their masters, did excellent work and got into the top 5 labs purely because the top 50 lab was funded enough for them to make up for lost time early in life)
I have also seen lab impact scores jump around substantially enough, that while the 90% hypothesis may be true, we have no way to picking out who will create the 10% that's gold. While half of the 10% might get reliably produced by the top 5 labs. The other half can be notoriously hard to pin down. You will see this in top industry groups (MSR, Brain) that hire exclusively out of the top 5 labs. Even there, the 90% number holds, despite there being a hiring system specifically built for capitalistic impact.
On the flip side, any academic field whose employability exists only within academia is a dictionary-definition pyramid scheme. It is a common accusation that's correctly levied on the liberal arts, but STEM should not be immune to it.
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] yuy910616|4 years ago|reply
Of course - I think if anyone act on the belief that 90% of their bets are duds, they would not be in the venture business. It's really interesting that a process could lead to a distribution - but knowing the outcome distribution is actually...useless?
[+] [-] majormajor|4 years ago|reply
This seems like an non-thorough and fairly uninteresting answer to the question.
I would want to know how much useful-but-not-groundbreaking stuff still comes out of the "make work" crowd, how wide you need the funnel to be at the top to make sure you catch the people who can end up in the top labs and who make breakthroughs, how much of a "safety net" that you need to make sure people are motivated to jump into the funnel in the first place rather than going into something safer, etc.
A world where we have fewer "wasteful" make-work research jobs but also have fewer breakthroughs isn't great. Hell, you could call the majority of today's service- and information-oriented non-academic jobs "make-work" too (let's up those clickthrough rates! let's stream this video in 8k instead of 4k! let's move this money around slightly faster!). So is there necessarily much utility in moving "make-work" researchers into other fields?
[+] [-] ren_engineer|4 years ago|reply
[+] [-] cscurmudgeon|4 years ago|reply
You need to fund avenues that don't look promising now. Some new developments may make them good. E.g. deep learning before 2011.
[+] [-] sjg007|4 years ago|reply
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] 908B64B197|4 years ago|reply
That's also true for software engineers. A handful of 10x can carry a company a long way.
[+] [-] satellite2|4 years ago|reply
[+] [-] version_five|4 years ago|reply
(But this should be obvious to a VC so I may be reading it wrong)
[+] [-] dotcommand|4 years ago|reply
I think there is a difference between "being shit" and "being fake" though. 'do you really think it’s true that 50-70% of biomedical research is fake?'
Fake seems more insidious and problematic.
Also this brings up a very troubling issue. If 90% of the "research is fake/shit" and lets say that means that 90% of the researchers are "fake/shit", then it means that 'scientific' consensus is also likely "fake/shit".
This is why I'm always skeptical of 'scientific' consensus. Science is about evidence, testing, etc. Not consensus - which is the realm of politics, law, etc.
And I'd suspect 99.99% of social 'sciences' is probably 'fake/shit' and that is used to push/change society/government/etc.
[+] [-] WalterBright|4 years ago|reply
Xerox did it with the copy machine. Which then remade the business world. They did it again with the user interface, though it was Apple that capitalized on it.
Frank Whittle soldiered on for many years trying to invent the jet engine, funded by venture capitalism at the time. The government wasn't interested until he demonstrated flying jet aircraft. In the meantime the US government shut down Lockheed's nascent jet engine project.
[+] [-] quantified|4 years ago|reply
Interesting perception, seems to have explanatory power. I’ll note that building games and gaming them has accelerated with tech. (Facebook, Tiktok, Amazon, REvil, Robinhood.) These aren’t institutional games, these are societal games. Different and fluid yet roughly defined groups.
[+] [-] lumost|4 years ago|reply
Is it possible that the sciences and other fields have exceptionally high coordination taxes? Or is it likely that we’ve structured them such that only a small number of slots exist for people to move the needle.
The latter seems eminently true given the finite number of conference slots and the former seems true given the the need to convince more people of a given direction.
If such a dynamic exists than the advent of communication technologies may actually hamper forward progress due to elimination of smaller research networks.
[+] [-] petermcneeley|4 years ago|reply
I really enjoy it when people say exactly what they think.
[+] [-] david927|4 years ago|reply
If they got lucky, it was because they were "super-elite." No one's going to win a nurture-or-nature argument but there's a clear self-interest in these situations to call nature what was, at least in part, nurture.
[+] [-] jstx1|4 years ago|reply
The only way the statement could be false would be for everyone to be at the same level of skill/knowledge/aptitude/etc. but there's clearly some non-uniform distribution and regardless of where you draw the line to define super-elite, some people will fall in that group.
[+] [-] abvdasker|4 years ago|reply
[+] [-] FooBarBizBazz|4 years ago|reply
> But I think of sociability or socializing as a collective action problem.
is excellent. He nails it in a way I hadn't articulated before. Marc disagrees, but I'm really with Richard on this one.
[+] [-] lambdatronics|4 years ago|reply
https://www.strongtowns.org/journal/2021/1/6/college-campuse...
https://news.ku.edu/2018/03/06/study-reveals-number-hours-it...
[+] [-] highenergystar|4 years ago|reply
Social media definitely has negative impacts (e.g. directly tied to mobs in India and Burma) and positive impacts (so much easier to stay connected across the world) - it would've been 'interesting' to hear a more nuanced take from one of the inventors of the modern internet
[+] [-] abvdasker|4 years ago|reply
> Traditionally if I wanted to work at a company in another country I would have to go to that country. I’d have to be an immigrant from my country, at least for a while. In a world of remote work and Zoom and Slack, I can now work for people anywhere in the world. I can work for companies doing any kind of knowledge work. Immigration policies apply to the atoms of human beings, they don’t apply to the bits. I can go to work for some company anywhere in the world if it’s a remote-friendly company. I may never travel there, I may never have to travel there.
Marc Andreessen is getting very close to saying the quiet part out loud. This is the clearest statement I've seen to date from a venture capitalist that white collar offshoring is almost certainly going to accelerate due to the shift towards remote work brought on by the pandemic.
[+] [-] exolymph|4 years ago|reply
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] 908B64B197|4 years ago|reply
If anyone isn't hiring international remote right now they are losing a huge opportunity. Lots of people are looking at jumping ships, and western companies can outbid almost anyone for top talent.
[+] [-] mym1990|4 years ago|reply
[+] [-] birdyrooster|4 years ago|reply
[+] [-] cblconfederate|4 years ago|reply
I often wonder if all that negative press about leaks, facebook's privacy violations etc. are just publicity stunts. So many tech articles seeking outrage and smell of fake.
[+] [-] hamburgerwah|4 years ago|reply
[+] [-] dang|4 years ago|reply
https://news.ycombinator.com/newsguidelines.html
Your story is interesting, of course; but you're not actually telling us the story.
Also, "total buffoon and had just been in the right place at the right time" is a pretty sweeping conclusion to say you realized "almost immediately".
[+] [-] wombatmobile|4 years ago|reply
Sometimes it takes a while, and some deep context, and then some more context, ideally in a different set of circumstances, before you can assess someone's capabilities fairly.
Some people shine in their specialty domain, and flail outside of it.
Others are good in fair weather, but fragile in a crisis. Others are kind of the opposite, losing steam day to day, but rising to the occasion when shit happens.
Seasoned salespeople know all this. They do well consistently in spite of it all by presenting themselves credibly irrespective of their competency in any domain. They dress right for their audience, and they speak persuasively, always mindful of what their audience wants and needs to hear.
But listen to Andreesen talk! He sounds like he's never had to learn how to persuade anybody of anything. Well, not any regular people.
https://audioboom.com/posts/7923122-flying-x-wings-into-the-...
[+] [-] daxuak|4 years ago|reply
[+] [-] boringg|4 years ago|reply
[+] [-] WalterBright|4 years ago|reply
Interesting. I commonly hear asserted that breakthrough fundamental inventions don't come from capitalism.
[+] [-] yborg|4 years ago|reply