Is it possible that computer tech was just weirdly susceptible to startup funding, and it is a really poor fit for biotech?
Computers mostly are
* well understood at every step (well, at least it was all designed by humans and the bits and bobs do what they say on the tin).
* mostly involve producing some kind of output for everyday normal people to use, in the end.
So they are easy to understand and evaluate. Even some investors can manage it.
Biotech stuff seems to mostly involve making tools for other technicians and scientists. And the process by which is works is some ridiculous, quirk-laden byzantine madness that evolution happened to throw together. At least from an outsider point of view it seems like an absolute nightmare.
It’s actually the other way around: it’s surprising software investing works so well compared to biotech.
While biotech companies carry a lot of all-or-nothing R&D risk, their “product market fit” is all but guaranteed. Their addressable market size is well known based on patient numbers and how much they can charge nationalized healthcare agencies and insurance companies based on quality of life improvements is well understood. Once they have premarketing approval, they’re all but guaranteed an exit to one of the pharmaceutical giants. The most promising ones get acquired in phase II before efficacy is even 100% demonstrated.
Look no further than IPOs: on HN we lament all the unprofitable public tech companies but the average biotech IPOs pre-revenue! Before it’s even legal for them to sell a product! That’s increasingly been the case since the 80s due to the exhaustion of small molecules and other low hanging fruit.
In practice, scientific due diligence is harder to fake than aspirational user growth numbers which are far easier to game (case in point: Reddits ongoing bullshit). The FDA isn't going to let anyone put a dozen people at risk of death in phase I trials without a level of due diligence that puts all VCs to shame.
I have a friend who plays the stock market by reading papers published by publicly traded biotech companies and shorting the ones that seem to be fabricating evidence. This works well enough that he doesn't need a job.
That's a really interesting approach. The trick would be knowing the indicators of fabricated data. Or perhaps just knowing when the data isn't good enough to pass the next clinical trial.
Wow that’s truly fascinating. I’d love to hear your friend tell the story of how he got into it and how he makes it work, if he ever finds himself in an autobiographical mood.
It is an absolute nightmare. Biology is fundamentally fuzzy and our knowledge is incomplete. Biological actors, DNA and RNA and proteins, can act in surprising ways in feedback loops that are extremely difficult to track and quantify.
Imagine every time you needed to troubleshoot something in a computer, you had to break out the multimeter. But the multimeter only works for one specific thing, which is an indirect measurement of the phenomena you’re actually interested in and trying to troubleshoot. Also the multimeter has some serious flaws and biases that make it seem like it’s working, but everything you get out of it is wrong and leads you to misinterpreting your results. That’s what its like to do biology.
A lot of innovation and progress is made when new tools to probe what’s going on in biology are invented. For example, cell viability assays used to be conducted by literally counting the number of live cells vs dead cells. Now, you can use a photometric test that’s extremely easy and takes a lot of guesswork out of the assay and makes it routine.
Researchers fundamentally need more of those types of assays to make life easier. And that’s where the dream and the profit people in biotech are chasing after.
Also, due to ethics rules, you aren’t allowed to open a computer to probe it with your broken multimeter unless it has already died. With a lot of paperwork, you may be allowed to probe an abacus and extrapolate the results to a computer.
This reminds me of a school project (building a sound card) where I noticed that when I plugged the oscilloscope at one point it changed the output at another point --> I threw out the board and decided to never do hardware again..
If the probe was single ended (e.g. not a differential probe or handheld unit), you may have shorted something to ground without realizing it. Was a long time before I figured that one out.
> Imagine every time you needed to troubleshoot something in a computer, you had to break out the multimeter.
What disturbs me sometimes is that many people in software engineering approach debugging like empirical science. Run experiments, gather data, fit some curve, essentially. In the end, a program is a product of the mind. It's pure logic, and fundamentally it's understandable, unlike the real world which can at every turn have new surprises for you. We should think more and measure less.
No, I think software companies work well with startup funding simply because of the strange effect that unit costs have on software profits.
The way computer (and especially internet) companies work is that once you have a working product, you can sell it a practically infinite number of times for practically zero marginal cost.
This means that the successful software/internet companies are INCREDIBLY profitable, since they can sell the same product millions of times.
Are startup investors good at predicting which company is going to be successful? Oh god no, they are awful at it. 90% of the companies they invest in fail completely.
It doesn't matter, though, because they only need one success to make all those failures worth it. The cost of investing in a failure is WAY lower than the cost for NOT investing in a success.
This means they don't really care that they can't evaluate which companies will be successful, they just cast a wide enough net to not miss the successes.
Lots of Biotech stuff does fine, and plenty of tech startups are basically frauds (WeWork for example). I don’t think you can extrapolate that startup funding doesn’t work for Biotech.
I'm not sure what makes WeWork a tech startup. Renting short term office space is not a high-tech endeavor. But it's true that there are plenty of tech startup frauds, like Nicola.
FWIW, the WeWorks I've worked in have better tech than most traditional offices I've worked in. The printing and room booking experiences are pretty great.
Revolutionizing global consciousness sounds more like a religion or something, but whether it was a, uh, niche religion or a real estate company, surely neither of those things is tech.
I’m sure there are other great examples, but WeWork doesn’t really seem like one; they were a real estate company, right? Cryptocurrency stuff maybe could be a better example though.
I feel like Crypto generally delivers on what it promises in terms of technology. If I go to investors to found Holebucket to produce the worlds first bucket manufactured with a one inch hole straight through the bottom, it isn't exactly hard to accomplish my goal. Crypto startups have a product, it's just a really dumb product. But Theranos for instance just straight up never had a product in the first place.
The problem appears to be that our present text conversation climate is such that you must either pick Team Science or Other Team, and should you mention that there are faked results hiding in plain sight, people get upset because they think perhaps what you're saying is "Maybe vaccines do cause autism" and "Maybe HCQ does cure COVID-19".
But that's not the truth. There is no monolithic Science entity. It is a property of every organization that reward-alignment is a stronger long term mechanism than fact-alignment. And it is impossible to direct the two in the same direction. This means that among the science establishment, there will be those who have ruthlessly optimized for the reward.
This is part of why the general Internet arguer's approach of "There is some evidence that X is Y look at this study url://url.url/url.pdf" is often the blind leading the blind.
Yes. Most people bring it up because they have an interest in a specific study or result being wrong, which I suspect has trained people to be dubious of anyone questioning The Science.
And some people treat it as a quasi belief system, which makes sense, with precepts like 'the world is deterministic, causes precede effects' and so on. You could do worse. But they aren't scientists and they don't generally grok that science is an activity whose output is sometimes useful models and not 'Truth'.
My mental model here is that you thus get people who trust in science as a paradigm, who then see doubt or skepticism as aimed against the whole edifice that is part of their fundamental understanding of the world, resulting in discomfort and leading to expected results.
In other words pretty normal stuff that resembles when you come across an argument whose implications are opposed to your principles, that you suspect of trickery, but lack the rhetoric to dismantle yourself.
"You can't trust anything" (with an implied "But you can trust me.") is, however, the battle cry of the charlatan.
Part of the exasperation of "Team Science" is that so many from "Team Other" are not acting in good faith. Most of "Team Other" doesn't actually care about getting to truth--they only care about winning (for some value of that--the leaders grifting and the followers "sticking it" to the other team).
> The problem appears to be that our present text conversation climate is such that you must either pick Team Science or Other Team, and should you mention that there are faked results hiding in plain sight, people get upset because they think perhaps what you're saying is "Maybe vaccines do cause autism" and "Maybe HCQ does cure COVID-19".
Assume that you consider yourself unable to evaluate the truthfulness of scientific claims.
Being told that claims you'd thought were properly vetted are actually wrong, then means that you have no way to know if other claims are accurate or not.
If your process doesn't work, then any knowledge based on that process is called into question.
It is just a way for large biotechs to offload some of the risk / cost of R&D to VCs in exchange for some of the upside. People are always willing to make those types of bets.
I don't think it's about the type of tech. Calling both groups "tech companies" is misleading to start with. The California start-up ecosystem is based on applying tech to create consumer products and once market fit and growth potential are evidenced it's straightforward to scale it globally.
Biotech companies are developing new technology, in a highly regulated environment where, like other comments point out, there's a predictable economic niche. They only share a denomination, the dynamics are wholly different.
I just started reading your article, and am down to "What If You Really Are a Fraud?". I think the more interesting thing is not people who have delusions of competency, but people who feel they have "imposter syndrome", but are actually imposters (not just newbies who are still learning), and convince themselves that they aren't after finding out about imposter syndrome.
I don't know how much this happens, but in areas such as education I think it could happen, as the criteria for most tertiary, and some secondary, educators isn't competency in teaching, but competency in a subject. And teaching effectively, especially to a large class, is quite hard.
> people who feel they have "imposter syndrome", but are actually imposters (not just newbies who are still learning), and convince themselves that they aren't after finding out about imposter syndrome.
I could be one of those. But the thing is: a) one can rarely tell. And b) one way to look at imposter syndrome isn't that everyone is actually great while feeling terrible; it's that most people are quietly struggling in a lot of ways, which they see in themselves, but which are hidden from others. We could mostly be (and likely are) mediocre.
So I can be struggling for real, and be a real "impostor", and be doing fine relative to the average population of my peers, all at once. I see many ways I'm struggling with things my peers seem to breeze through, but I might not see the ways I'm succeeding where they're quietly struggling themselves, and vice versa.
Completely agree. You have a very healthy way of looking at this personally, and this is the larger lesson people need to take in. "Imposter syndrome" is more a rule of thumb to not be too hard on yourself. The bigger, and more difficult lesson, is to recognize what needs improvement, what you can improve, and what you can't, in yourself and other.
The more you learn about a subject the more you areas you discover that you do not know about. Learning has three basic stages 1) You are new 2) You think you know everything 3) You think you know nothing. I think at stage 3 impostor symptom can kick in. The dangerous stage is stage 2 where you feel very confident.
It was a huge climbdown for me when I went to college. In high school, I was in the top 25 of my class of almost 1000 and I never broke a sweat. I never developed study habits because I didn't need them. One semester my junior year, my friend and I just spent one week in early November doing the entire semester's work, some late, some early. The rest of the time I could spend doing dumb shit and also hacking away on my computers.
I did so well I got into a college where I was annoyingly average. By the time I developed some semblance of study habits and realistic sense of my abilities, it was too late to get my GPA much above 3 (this was before grade inflation was much of a thing). In graduate school I finally got my shit together and learned to just work, but I wasn't in as elite of an environment anymore thanks to my performance in undergrad.
I had wanted my whole life to be away from the normies in high school and once I got there, I didn't love it. It was humiliating. But that was good for me. Realizing you're 1 in 1,000 or 1 in 10,000 instead of 1 in a million is probably much more realistic. And also annoyingly, this is exactly what testing when I was like 7 years old told me, but the illusion of being in an exurban high school made me think otherwise.
Now I read we are shaped more and more and more by our experiences at around age 18. That's the music you hang on to and even, I read this week, the politicians we hang on to. I love to think I'm different, but I really am part of Generation Clinton. I really am not 1 in a million or 1 in 100,000 even.
I think a lot of the kinds of people drawn to tech had similar experiences in their formative years. You see a lot of posts here with ideas about reforming education, but schools need to get everyone through, not just the 1 in 10,000 or even 1 in 100 types. In the US, you don't get sorted like that until about age 18 when you're already having a lot of defining experiences.
So my interpretation of what you're writing is that people just get used to being the smartest guy in the room. Some may like being around others like that, but if they're honest I bet most people don't. They should!
The lamest possible source turned me around on this. I was listening to Howard Stern (not my parents, not my friends, not my teachers) rant about how when he did his movie he found the movie people interested in building stars up, but his background in radio was all about burning people down and recycling them. I decided I liked building people up more. The karma didn't take long to pay me back.
When you're anonymous on the Internet, nobody knows if you're full of shit or really pack the gear, so we see a lot of bullshit words to add the kind of credibility you might see from a resume.
The 1 in a million are either screwed over worse than you were, or are recognized early and perennially challenged to further their development.
> In the US, you don't get sorted like that until about age 18 when you're already having a lot of defining experiences.
Programs for regular and exceptionally gifted students do exist in the US, but this varies state-to-state and district-to-district.
The best "reform" I've thought of to address almost everything you've mentioned is to teach kids, early on, about failure. That it isn't the end of the world, what they can do to try to identify it happening, and how they can recover from it. Though like anything else this has to be done in moderation, as people who keep failing eventually give up entirely.
GATE programs are underfunded and to the extent they exist they only make it worse most of the time because they basically are telling you: you are elite! and in your school you probably are, but you're usually still in the same school. Most of the time it's just pull outs.
Also, I wasn't screwed over. I live a charmed existence that I am thankful for every day. (=
eta: 100% agree we need to teach kids about failure. I understand the concerns about too much, but right now I don't think they are exposed to enough.
But yeah, the situation for regularly gifted students is often as you say. And any school program that truly held them to higher standards would also end up penalizing them with lower grades that would make them look non-competitive to highly selective universities.
> but right now I don't think they are exposed to enough.
Except those in the bottom 25%. They are human too, and deserve a good, well-tailored education.
Actually, in my college dorm we had a guy who was only 16 who'd been accelerated. I wouldn't exactly say he was "bullied," but he didn't have a very easy time of it.
For me it was a bad choice to only take one year of community college in lieu of high school, instead of two. And being mainstreamed in math at the beginning of middle school instead of accelerated a year was particularly painful.
True story: one of my neighbors went to University of Chicago High School ("Uni High" as it's called). It was (and probably still is) a school for the extremely gifted. (I suppose they have some Reverse Imposters there, too, but I wouldn't know /s )
My dad was against my going there; I wouldn't be able to talk to ordinary people if I was only ever around those "gifted" kids.
I suppose there's something to that; I cited this article:
by a guy who didn't know what to say to the plumber standing in his kitchen, whereas I'd much rather be around people like that than the Reverse Imposters.
Acceleration (universal or subject-specific grade skipping) can help with this. It challenges the gifted student appropriately while still allowing them to socialize with regular people.
Naively it might seem that this could lead to bullying, but from what I read it tends to work really well. The older students aren't threatened by the prodigy.
I took geometry as a freshman in a class full of juniors and seniors. The bullying was frequent, and the teacher strategically refused to show up on time so I had to either wait around outside the classroom like a coward or go in and be hazed.
I skipped mid 3rd to mid 4th. I wasn't really that much younger, but it was not good. It wasn't just that they were bigger or whatever, but at that age what you're going through is still pretty tightly coupled to your age. I didn't feel normalish until well into high school.
I don't recommend it. I recommend letting kids accelerate, but right now the consensus seems to be accelerate most people who need it at 9th grade, not 7th, and definitely not before. As with most of these things the consensus goes back and forth, but that squares with my lived experience.
I wonder if skipping in the middle of the year was particularly bad.
The recommendation you cite conflicts with Miraca Gross's recommendation for exceptionally gifted students, but they will be a minority of those who can grade skip.
i took algebra 2/trig as a freshman in a class full of juniors and became friends with pretty much all of them. i was a pakistani dude at a title 1 school. it just depends on the class
As adults we're constantly interacting with people younger and older than us by multiple decades. Even as college students we're in classes with those younger or older by multiple years.
The modern age-cohort school system is the historic exception. Prior to it single-room schools were common. And prior to those apprenticeships in which some of the apprentices or journeymen were older and younger were common.
Heck, in my neighborhood kids were older and younger. I remember getting advice from an older neighborhood kid when beginning elementary school (the part I remember is that lunch boxes weren't cool, and to use a paper bag instead).
You're right in that being the single odd-ball is unusual. But I think it would be better to just make partial and full grade skips more common than to make them rarer.
That's just called Dunning-Kruger and is a well-studied phenomenon.
You see it all over HN too, for instance, people coming up with a "new" idea, writing a blog post about it, and self-promoting as if they've contributed something novel.
The Dunning-Kruger effect is not well established. It often doesn't reproduce.
Also the effect isn't that people misjudge their knowledge, it's that they misjudge their place within a distribution. Suppose I give an exam to 30 people, and the results are normally distributed around a score of 70 with a low of 40 and a high of 97. The bottom of the distribution may accurately predict that they scored about 40 on the exam, but if you ask them how they performed relative to their peers, they will believe that they are about average and guess that a sizable portion of the class performed worse than them. Alternatively, if you ask the top performer who scored a 97, they will say that they think they scored about 97, but they will think maybe a few other people scored higher and maybe that the average was in the high 80s. The Dunning-Kruger effect posits that people are actually pretty good at accessing their own knowledge without being a good judge of how knowledgeable others are.
>Also the effect isn't that people misjudge their knowledge, it's that they misjudge their place within a distribution.
Put differently, isn’t this saying it’s a misattribution of confidence? In the context of the original claim about investing, that seems very relevant.
I suppose that the Dunning Kruger effect is "well studied" in that there have been many attempts to study it, which so far cannot find reproducible results, and suggest that it isn't a real psychological phenomenon.
Look, I understand there's a lot of trouble in psychology in general and there has been some reproduction issues with that one. But the truth is, we all know instances of the guy who thinks he knows everything just because he's good at something else and just thinks everything people went through to get where they are was a mistake. Whether or not this is a psychological thing in reality, it's something most of us have experienced and that's the name people know it by.
That's not even what the original study claimed to find though! It caught on because it seems so intuitive, yes, but the specific curve of confidence vs. skill doesn't seem to look like that at all.
This is how memes or memetics or just language works though. Things often get called something they aren't and if it sticks it sticks. I'm not saying it's correct or whatever, just that it stuck because it vaguely gave a name for something people experience and didn't have a name for before.
Look through any etymological dictionary and you'll see this phenomenon. What does a computer have to do with "to strike" in PIE? Something! But it's not the literal meaning.
No, but the behavior expressed by adopting such an attitude is. Yours is a nitpick that is probably worth mentioning but doesn't really change the analysis.
Again, I'm not saying that's what it SHOULD be called, I'm saying it's a useful term for something we experience. At some point the wrong definition becomes the correct one, that's most etymologies.
It's why people say "and I" as an object and don't know what question begging is or whatever. It just doesn't matter in the long run.
Those studies, which do consistently show significant effects despite your citation-unladen claim, explore averages across a general population and seek to explain society-wide phenomena through the lens of "average" humans. This implies an assumption of homogeneity within the general population. Such tests will of course be underpowered compared to case studies in specific circumstances, particularly those involving self-selection and a cohort-level cultural bias toward "I'm smart and need to pick things up quickly for my day job which means that skill is equally accurate and transferrable to everything I read about".
It started as a syndrome. I don't think it would survive Wikipedia's modern standards if it hadn't generated its own support by existing in a different era.
Look, Bob, I don't have a personal vendetta against you. I do find value in clarifying things that are obscured by pomp and rhetoric. What's more, I don't appreciate muddied conversations, particularly when the motivation for the introduction of such mud is purely self-serving, especially in monetary terms.
It seems obvious to me that Substack assesses your quality as a writer by checking on click-throughs from various sources and I would wager good money that they pay out differently depending on the behavior of the users who follow those links, either algorithmically in realtime or whenever it comes time to renegotiate terms. It's not even 2+2 here, Bob.
PS: morality is more than just "would someone else do it". Don't make me start quoting cliches typically reserved for 5 year olds.
Is free, perhaps. But that could be for many reasons, including that you haven't yet convinced Substack to monetize your offerings. Isn't that how it always is when publishing on platforms you don't own? That you must prove your worth to get the paying gig?
Arrgh, why didn't I.think of that? I just left for vacation with an open code review that should have been easy because some new junior found some issues that I couldn't resolve before packing my suitcase.
Thanks junior, the issues you found were real, even if small, and things will be better when I return and fix them.
Man how insane is it that these guys and gals raised 400 millions on tech without any raw data, nothing to show for it? It was never reproduced? They just said they got it?
The more I live in this world, the more I realize that its winners are pretty much exclusively charismatic bullshitters. I used to think that professional investors actually were a little smarter than the rest. I mean, here they are making huge bets on particular numbers on the roulette wheel--they must know something we don't! But they keep getting fooled!
They have gobs and gobs of money to invest. Rich people chasing ever riskier rewards just handing money to them! They have to find something promising to throw it at. But who is it going to? Evidently, a lot of it goes to founders whose primary skill is storytelling. I used to think, no matter how handsome and smooth and persuasive you are, you at least have to have a little substance behind your enchanting narrative and ivy-league mannerisms. But here we are with failure after failure (and a once-a-decade colossal failure like Theranos) where all the warning signs were visible to someone not under the spell, and these bullshitters are still getting funding shoveled at them.
It's pretty sad that "look like you know what you are doing and convince gullible people" is probably the best future career advice I can give to my school-age daughter.
> I used to think that professional investors actually were a little smarter than the rest.
It's been my experience that you can't tell who's smarter than who by what they do for a living. On the whole, no group is actually smarter than any other group.
> It's pretty sad that "look like you know what you are doing and convince gullible people" is probably the best future career advice I can give to my school-age daughter.
I don't agree with that takeaway. I think the takeaway is that confidence is the primary thing that people take as a proxy for competence. It's not really about gullibility as much as people engaging in a heuristic. So learn to fake confidence, but have the chops to back it up.
I'd venture that professional concert piano players or chess professionals (just to pick two random ones that popped into my head) are on average more intelligent than other fields which I won't name.
I suppose it depends on the definition of smart which I understand as intelligent/good rational decision making but maybe you mean somthing else.
I think the point GP was trying to make was about individuals in the groups, not averages. There are some brilliant janitors, and some professional piano or chess players have had savant syndrome. You're unlikely to find unintelligent or savant biochemists, but I'm sure more than a few are hyperfocused on their discipline to the exclusion of competency in other areas.
I doubt a biochemist would have savant syndrome. It's possible, maybe. It would probably look like someone who could recall all of the enzymes (and their variants) and intermediates in various biosynthetic pathways and could tell you without research which enzymes would need to be expressed together to get from one starting chemical to another.
> It's been my experience that you can't tell who's smarter than who by what they do for a living. On the whole, no group is actually smarter than any other group.
I assumed they meant professional investors are smarter about evaluating potential investments. Not generally smarter, just smarter about what they put their money into.
OP here. I guess rather than "smarter" I meant to convey: less gullible, less vulnerable to being influenced by silly signals like someone's mannerisms and confidence, less reliant on unexplainable gut feels.
I guess when I think of professional investors picking some of these dogs, my mind imagines that scene in Moneyball[1] where the old timers are trying to pick baseball players by who "looks good," "has a good jaw," "how the ball sounds when it pops off his bat, and "what the player's girlfriend looks like."
I don't know that that's proven. I think it has been shown that index mutual funds generally do as well as actively managed funds. One explanation is that the fund managers don't know better than anyone else. Another explanation is that the fund managers do know better, but their fees are so high that it cancels out the benefit of their expertise. That is, their expertise is real but overpriced.
On a practical level, there's also the matter that, even if some fund managers do beat the market, some other fund managers don't, and it's hard to tell which is which. By going with an actively managed mutual fund, you take on "how do I know my fund manager is one of the good ones?" risk, which you don't have with index funds.
> It's been my experience that you can't tell who's smarter than who by what they do for a living.
There are always exceptions of course. But it is most definitely true that (for example) the average IQ of people doing high end physics is way higher than the average IQ of people laying bricks.
You're ignoring GPs first sentence: "It's been my experience that you can't tell who's smarter than who by what they do for a living."
This first sentence indicates that they are writing about individuals with a vocation, not a group average. Statistically, in developed countries, any given manual laborer is likely to be less smart than any given venture capitalist, but Elon Musk, for instance, has been both. If you'd randomly picked him, in December of 1989, from the pool of manual laborers, you would have been wrong.
I view investors like I view critics of media: necessary for society in small doses, but otherwise contributing little value of their own into the world.
And my threshold for having "too much" of these is pretty low...
Even so, these people of the Power Elite were visibly much smarter than average mortals. In conversation they spoke quickly, sensibly, and by and large intelligently. When talk turned to deep and difficult topics, they understood faster, made fewer mistakes, were readier to adopt others' suggestions.
Nice find! The author, it seems, falls for the same sorts of things I mentioned. He talks about an "executive-nature" that sets these people apart. Their "aura". Whether they "sparkle with extra life force." People who "just came across as... formidable, somehow." And over and over through the article, he confuses these things with genuine competence and intelligence.
The author, it seems, falls for the same sorts of things I mentioned.
That was not my intent. The point of the essay was exactly the opposite. Maybe I fall for the same stuff, but Eliezer is a very smart guy who was predisposed (as he makes clear in the essay) to believe that the people he met were all fluff. He was surprised that they were not just demonstrably knowledgeable, but, in addition, had other appealing characteristics.
Having sat on the other side of the table reviewing pitch decks and proposals, most investment decisions seem to be taken on either a very obvious "this is complete nonsense", or on a completely gut feel of: does this sound reasonable, do the numbers look sensible, does the team look good.
> a completely gut feel of: does this sound reasonable, do the numbers look sensible, does the team look good.
That's really the only way you ever could do it. But the key words there are "reasonable" and "sensible". Reasonable and sensible things don't revolutionize the entire world. They're not brand new, unprecedented technologies. It's not sensible to claim you'll create a ten-billion-dollar+ market overnight. It's not reasonable to claim that a problem that 10,000 smart scientists have worked on for decades was just solved in an unexpected way by this twenty-something "wunderkind" upstart and no you can't see behind the curtain. And yet these people get hundreds of millions in investment anyway. That's the question: why the hell did that ever sound reasonable; why the hell did those numbers ever look sensible!?
To me it's a natural consequence of wealth inequality. When you have mega funds like the oil countries have, where even losses like this are not really relevant, you will have this behavior. They know it's a moonshot. It's high risk high reward. And many will fail - but in the end, it doesn't really matter that much.
I sometimes think that the real reason ChatGPT scares/excites so many tech business types, is that it has automated the one skill they have and are looking for in startup founders, which is to BS convincingly.
> It's pretty sad that "look like you know what you are doing and convince gullible people" is probably the best future career advice I can give to my school-age daughter.
I would like to think that you would want your daughter to get more out of life than just raw cash.
we really need to stop talking about these situations with legitimate terminology. They aren't "VCs" or "Investors". They're marks, and they got scammed.
"you can't cheat an honest man" definitely applies.
Not sure why you were flagged, but many people handling millions say that they can do it because they know how to do it. There is a case to be made that some of them actually don't.
VCs aren't marks. They're fencers, hoping to get rid of the product before anyone realizes it's worthless or stolen. The (possibly sometimes subconscious) reason they don't care to deeply investigate is because if they're convinced by a shallow inspection, they're pretty sure they'll be able to convince others.
It's a greater fool shockwave, pretending to buy into something and betting that you can get someone else to buy into it before the bottom falls out. Not that you know for sure the bottom will fall out, but if you're going to buy in based on how marketable the pitch is, examining it too hard might weaken that pitch or make it fall apart. In that case you've wasted time and money and have to find something else. If you're committed, the last thing you want to do is examine the business; you're shortening your bullshit runway.
I know of a company, in a totally different field, operating on the same principles, with the same warning signs. They raised close to one billion and are in the process of raising 200 million more. Happens all the time, but never to me (quoting a line from the classic Margin Call).
That sounds a little bit like "If I can tell this company is defrauding investors, how can I get in on the fraud?" Whoever you borrow that stock from is now your mark that you are defrauding -- indirectly, of course, since you're not forging fake results or something. It still feels icky.
> That sounds a little bit like "If I can tell this company is defrauding investors, how can I get in on the fraud?"
That's not how I meant it. I was thinking more generally about pre-IPO companies that you think (for reasons that you can legitimately use when investing in this manner) have dim prospects.
Look at the stock market and fixed income investments around you. There is nothing there, very modest growth. That explains in part why so many people shifted part of their pile of cash to VC investments. The pile is not growing fast enough. Too many suckers out there who have not realized that we are in a new normal: low growth, low productivity, an aging, less dynamic society.
> Man how insane is it that these guys and gals raised 400 millions on tech without any raw data, nothing to show for it? It was never reproduced? They just said they got it?
Got to stop thinking that people with money are smarter than anyone else.
I think that it is easier to spot warning signs in hindsight. Simply based on this article, it seems possible and even likely that the lab head was deceitful. And the article suggests that the company management was either naive to the point of negligence or possibly they were actively defrauding investors.
No matter what is the case, legitimate mistakes made by egotistical scientists compounded by negligent management or outright deceit and fraud, it is amazing that hundreds of millions of dollars were invested before it was discovered.
Sometimes I lament the fact that I feel nervous asking for a raise even though I have demonstrably provided value and delivered massive projects. One the other side of the spectrum is the gall to ask for 100 million with nothing to show. It sometimes feels like there is a missing middle.
Witholding data, explanations and assistance from those who want to evaluate and reproduce an experiment is obvious and immediate hostile and antiscientific behaviour, not a flaw that is only recognized in hindsight.
It is easy to believe that is what happened based on the details in the article but what we are seeing is a filtered view in hindsight.
It's like when you watch a movie with a twist that you didn't see coming. But then you go back and re-watch it knowing the ending and you gleefully point out all of the places the film makers put subtle clues which you didn't catch. Imagine telling the ending to a friend. He then watches the film and says: "how could anyone not see the twist? it was so obvious the entire time!"
What seems in hindsight as "withholding data" might have been seen at the time in a completely different light.
It reminds me of situations I heard stories about at two workplaces. Both were cases where a new hire was given a task to complete. They were giving excuses, showing partial progress, dodging inquiries. In both cases the new hire lasted over 3 months before it was realized they were doing absolutely no work at all. In all cases it was obvious in hindsight but during the course of the deception all of the excuses added up.
Sometimes excuses are true, but plausible excuses for not making progress (like those of your interns) are different from the extraordinary excuses needed for persistent and objective actively harmful behaviour.
These patterns of bad research tend to go on for a while because the involved people might be powerful and in any case calling them out requires effort and exposure, not because discovering that unreasonably defensive behaviour hides bad research is a surprising "twist".
I wish we had more details, but something stinks. There's always a conflict with "science" when somebody tries to monetize it. A possible explanation here is a desire to keep some elements of the process proprietary, but I don't see how that could apply to sharing within the same organization.
> There's always a conflict with "science" when somebody tries to monetize it.
Sadly, the replication crisis in science shows that the causes are equally present in purely academic settings as well. Status, power, job security or ego can be as powerful as money and the effects can corrupt someone subtlety and even entirely unconsciously. It's good to remember that no human is immune from confirmation bias or self-deception.
> Status, power, job security or ego can be as powerful as money and the effects can corrupt someone subtlety and even entirely unconsciously.
Yeah. How many times have any of us had what seemed like a good idea, tried it, and found it didn't work? It just takes a little more effort to try it a few more times thinking that something was wrong. Eventually you might get a result due to random chance. And at that point you've convinced yourself that your idea was a good one all along.
In that case I think the “monetization” is in the form of misaligned incentives with scientific endeavors. The incentives are having a job, getting grants funded, and obtaining prestige.
Everyone always decries these as failures of venture capital. There is fraud in every industry. You cannot conceivably check everything and there is a level of trust required. Even if someone sends you raw data you are taking their word that it’s the true data. There can be deception at every level and smart people will be deceived by criminals. Where there is money there will always be crime so I am grateful to see our justice system working even if it takes many years.
That's facile and ignores that VC is supposed to be a vetting gatekeeper: the reason they keep a fraction of all the money going through their accounts is because they're supposedly vetting the investment opportunities and have money and access to knowledge as necessary to validate claims, etc. If they're not doing this, what is the value add the VC company is providing, other than being a skimmer on the money flows?
The reality is that as long as there is no liability for passing the buck (ie the scammer's and middemen's beloved caveat emptor), the system continues to encourage bad players.
My point is that no matter how much due diligence you perform, there is still a chance to be deceived. No amount of money could get you to 100% diligence and cover every edge case.
There is liability for knowingly passing the buck. VCs have been sued before.
> Even if someone sends you raw data you are taking their word that it’s the true data.
With hundreds of millions on the line, is it so much to ask that VC firms employ a couple statisticians to at least do a sanity check on the data? Fake data can often be identified as fake.
VCs differ wildly. A small VC will certainly not earn enough in fees to employ multiple dedicated statisticians. They will likely have a CFO/other analysts who can check the data but there's no guarantee they will catch cleverly manipulated data. Obviously this is a much later stage investment so different diligence is expected but there are many ways to deceive. Certainly some VCs saw red flags while others did not.
Hmm. This is kinda the opposite of what I'd expect.
I'd think a smaller VC would be more conservative with their risk, while a large one would be more liberal, in that the larger VC could withstand more failures to get the even bigger infrequent wins
That’s an interesting thought, I’m not really sure how different the risk tolerance is. If you’re allocating 5% of your fund into a deal I imagine you’d be similarly conservative at both levels as the dollar amount is different but the risk is still the same portion of your fund. If anything the smaller may be more liberal as the multiples are higher in early stage. Both are expected to have failures but a larger VC has more resources at their disposal; A small VC can’t do the same diligence that a large VC with an army of financial analysts can do.
>>> Laronde, a Boston/Cambridge area biotech firm that seems to have had some major problems reproducing the data that helped raise them hundreds of millions of dollars last year
VCs: How the hell you put 100MM+ in a company without having a 3rd party verify that the "thing" works ?
The level of fraud going on in life sciences seems absolutely astounding. I used to think that fraudulent research was mainly “paper mill” stuff.
But in the last couple years there are so many cases of outright data falsification from famous scientists’ labs and in Science/Nature/Cell publications.
It seems even worse than the social science replication crisis, and with worse consequences.
It's like doping in sports, the cheaters get all the money and glory - until they get tested. The solution is more tests. If the study can't be replicated then there is a problem. There should be more tests in science, without tests it's not science.
What is the test though? Can you make it big before the tests matter? Would you be punished if the tests eventually fail?
If you do really well with life sciences, you'll convince people that you've got a miracle cure, while convincing regulators that you aren't selling a miracle cure. Like an ivermectin
I think what's unique about the social sciences, is that they went public with their problems earlier. It's probably about as bad in every field that has the same (or similar) set of incentives to publish and disincentives or lack of incentives to check the work of others.
Indeed. First I read of him were some of his articles on stuff he wouldn't work with. There's a passage in his article on dioxygen diflouride (AKA FOOF) that would sound delightfully wicked read in the voice John deLancie.
"people will find all sorts of ways to believe what they want to believe, to avoid hearing things that they don’t want to hear, and to avoid thinking about things that are too worrisome to contemplate"
Goodkind certainly didn't want to hear that he was a subpar example of a human being. And he wrote fantasy, regardless of how much he whinged that he absolutely didn't.
Is this what happens when research moves from universities to the private sector? Not sharing data and results seems par for the course for things like proprietary algorithms. Why would biotech be any different?
In fairness, one good thing about commercialisation is that if they don’t produce the goods in the end, it fails. In pure research it can go unnoticed much longer.
It would be interesting to know how many companies with these warning signs were legit. Is it possible that investors look at these as lottery tickets and hope that just a few hit?
One of my managers had a rule of 2 (different from my rule of 2).
You haven't proven you know how to do something until you've done it twice.
That was expanded by later managers to a more general sense of reproducibility, where 'we' don't know how to do it until two other people have done it.
There are certain aspects of my life that are informed by a general dread that some day I will leave my house and never be seen again. For instance I try to tell tell people I love them when we part, even if I'm mad at them, in case those are our last words for a long while, or forever.
If I really thought I was doing something at work that would forever change a corner of the world, I'd be super paranoid that the secret could die with me. That's the perfect recipe for me overworking. If I can't trust anyone with the information (eg, intellectual theft), then I positively vibrate. If I told people and they don't care, I have to finish it enough that I can demonstrate why they should care.
in science, if you make a prediction from a hypothesis, conduct a test, and what you predicted is borne out, that's not nothing; for example, if you look at historical records and hypothesize a reappearance of, I dunno, let's call it Halley's comet, and decades later Halley's comet reappears, why... they might name the comet after you!
Charts are for asking questions, not answering them. My life goes so much better when I remember that (or importantly, when I can find the right set of words to convince all the other decision makers that’s true).
An experiment gets you a little money and attention to try it a few more times. A few successful runs in different lab conditions should let you get a little money to start systematizing your experiment, and that should get you money and attention from industry, manufacturing.
That has always been an 8 year process at the best of times (most things take ten). Seems like a lot of people don’t have that sort of patience anymore, and they try to make things go from lab to shopping cart in three years or they endlessly loop on generating news articles (aka bullshit).
Precisely - these aren't "Warning signs" that are only clear in hindsight. They are proof of fraud beyond a reasonable doubt. If a person or organization has these traits and you continue to trust them, it is not an honest mistake.
Transparent audit protocols are the only solution - e.g. raw data should be immediately available upon publication, and even more rigorous protocols should be employed for grant application review (show us the daily log etc.), but those who oppose this approach say it'll expose intellectual property to outsiders causing the loss of competitive edge.
Open-source research is thus the only kind of research that should be allowable with public funds, and closed-source proprietary research shouldn't be publishable in any research journal. If people want to invest in the latter they'll be the ones responsible for due diligence, I suppose.
Computers mostly are
* well understood at every step (well, at least it was all designed by humans and the bits and bobs do what they say on the tin).
* mostly involve producing some kind of output for everyday normal people to use, in the end.
So they are easy to understand and evaluate. Even some investors can manage it.
Biotech stuff seems to mostly involve making tools for other technicians and scientists. And the process by which is works is some ridiculous, quirk-laden byzantine madness that evolution happened to throw together. At least from an outsider point of view it seems like an absolute nightmare.