Did the survey. It felt much shorter this year.
edanm
Karma: 464
I just donated $100, in large part because of the detailed writeup and because of the many people writing here how much they donated. So thanks everyone!
This is a topic I care a lot about, thank you for bringing it up
I’ve been an entrepreneur for 5 years. I started out like most Software Developers—by starting a startup. After a few years, I became convinced that this is NOT the best way to achieve the outcome you’re talking about (financial independence, aka ~5mil USD).
My basic problem with your post is simple, and others have pointed it out—you can make up all the numbers you want, but empirically, MOST startups fail. The usual figure given is 10% of startups fail, but this is a gross simplification, and I tend to think the number is much higher. More importantly, the number of years that it takes to fail can be long—the number of years before a successful exit is usually >5. Failures can happen earlier, but the worst-case scenario is to “fail at the last minute”.
To convince me that you’re going to achieve your goal within 10 years, you have to show that for some reason, you’ll do better than the statistics suggest.
The problem with #1 is you have no real reason to think you’ll do better than anyone else. This is where a lot of people get lost—they hear this statement, they nod, but they think to themselves “but I’m [better/smarter/more rational] than everyone else.” But here’s the thing—even if that’s true, it doesn’t mean you’ll succeed where others failed. Why? One of several reasons:
Being better/smarter/more rational might simply NOT be important in startup success. It’s possible that luck is more important. It’s possible that other things are more important, and we simply don’t know what they are. A lot of things are possible. The best minds in the world still don’t consistently pick winners, why do you think that is?
Even if you ARE better/smarter/more rational than most people, and even if that trait IS important, the statistics of 90% failures includes a lot of people who are clearly, demonstrably better than you. It includes the VC’s son, who has unlimited funds and a lifetime of learning. It includes the serial entrepreneur building his 10th startup after 9 successes. It includes the co-founder of Facebook, who has a billion dollars in the bank, unlimited press, and obviously some amount of familiarity with building startups. These are some of the people WHO STILL FAIL 90% OF THE TIME. So even if you’re incredibly confident, do you honestly believe you’ll do better than THEM?
So where does that leave someone who wants to apply intelligence/rationality to making money (like me)?
Well, there are lot of routes to take. I hope I’ve at least given you food for thought as to why startups are not necessarily the best route. Personally, I still think becoming an entrepreneur is a net win, at least if you like the idea. What I personally did after my failed startup is build a Software Dev Shop, and started selling software services. This will (probably) not get me a big exit, but the expected value of my money in this is still higher than in a startup.
Another route to take is to build a bootstrapped company, which will fail/succeed on a smaller scale, but which has other benefits: it might fail/succeed faster, it might need less work to get to the FU money stage, etc.
When you’re rationally weighing your options, and aren’t stuck in “Startups are the obvious way to get rich” thinking, then you can start learning about the wider world of business which has plenty of other interesting opportunities.
I’ve started watching TV Shows at 2X speed. This has been incredible:
I can watch twice as much TV in the same amount of time.
Lots of TV shows which are very interesting, but are slow (e.g. Breaking Bad, Sopranos) become MUCH funner to watch.
I started doing this a few months ago. It started when I realized that I already listened to Audiobooks at 2X-3X, and that TV Shows are basically the same thing.
Some tips:
You should use the VLC player, which lets you 2X while preserving proper audio.
In VLC, you can hit the “+” button to go to 1.5X, then again to go to 2X, 3X, 4X etc.
You can start with watching things at 1.5X speed, then go to 2X when you feel confident.
At higher speeds, you should watch with subtitles, which makes things much easier to follow.
Over the last 2.5 years, my co-founder and I grew the Dev Shop we founded (Purple Bit) into a very profitable small company, employing 7 people.
Purple Bit has just been acquired by a former client of ours, Autodesk Inc. Autodesk are the makers of AutoCAD, 3D Studio Max, Maya and many other professional 3d software products.
(Note: this didn’t happen this month, but it wasn’t public until now).
“ This is obviously and offensively wrong. Does the risk of robbery improve living conditions? Does the risk of death improve life? Also, a future society where consent is optional appears to be a terrible dystopia: assuming a free democratic government, lack of consent implies that advertisers and corporations could force consumers to buy things. This quote needs A LOT of additional justification and qualification (and ideally deletion) to avoid implying that “raising the sanity waterline” means “abolishing liberty and ethics.””
That part of the story wasn’t trying to say “this is something that needs to happen to raise the sanity waterline”. Remember, it’s just a fictional story. Rather, it was trying to show an example of something that we today would find incredibly offensive and morally unjustifiable, and yet that became a part of humanity.
Remember that for someone 500 years ago, many of our current practices seem absolutely repugnant and morally unjustifiable, even though today they’re just part of culture. Even 100 years ago, the idea of a black person sitting next to a white person on a bus was considered terrible, not to mention women having any kind of rights at home. In some parts of the world, a woman showing her hair is considered immoral and unjustifiable.
The story just wanted to give something that could happen but most people would think is wrong.
Reading “The Selfish Gene” teaches enough evolutionary biology to understand what the field is about, to understand the basics of the field, and to be able to converse on it intelligently.
What book can I read that will do the same for me in:
Medicine/biology/physiology (e.g. able to understand the very basic concepts of what a doctor does)
Law (e.g. able to understand the very basic concepts of working as a lawyer).
Bonus points—if the book on Law explains the practical difference between common-law and civil-law.
Thanks!
(I’m Edan Maor)
Thanks a lot to all of you! I really appreciate both getting a gift, and the way you did it—I agree with you in wishing that more people would make donations as a gift.
You guys made my day! :)
I remembered it too. Found the quote you’re referring to, I think:
“He ran a quick self-predictive model. There was a ninety-three per cent chance that he’d give in, after a kilotau spent agonising over the decision. It hardly seemed fair to keep Karpal waiting that long.”
Egan, Greg (2010-12-30). Diaspora (Kindle Locations 3127-3129). Orion. Kindle Edition.
Something I’m looking for:
A list of habits to take up, to improve my life, that are vetted and recommended by the community. Preferably in order of most useful to least useful. Things like “start using Anki”, “start meditating”, etc.
Do we have list like this compiled? If not, can we create it? I’m a big believe in the things this community recommends, and have already taken up using Anki, am working on Meditation, and am looking for what other habits I should take up.
FYI, I thought of this as I was reading gwern’s Dual N-Back article, in which he mentions it’s probably not worth the time, as there are much higher-potential activities to do.
(Here’s the relevant excerpt from gwern: N-BACK IN GENERAL
To those whose time is limited: you may wish to stop reading here. If you seek to improve your life, and want the greatest ‘bang for the buck’, you are well-advised to look elsewhere. Meditation, for example, is easier, faster, and ultra-portable. Typing training will directly improve your facility with a computer, a valuable skill for this modern world. Spaced repetition memorization techniques offer unparalleled advantages to students. Nootropics are the epitome of ease (just swallow!), and their effects are much more easily assessed—one can even run double-blind experiments on oneself, impossible with dual N-back. Other supplements like melatonin can deliver benefits incommensurable with DNB—what is the cognitive value of another number in working memory thanks to DNB compared to a good night’s sleep thanks to melatonin? Modest changes to one’s diet and environs can fundamentally improve one’s well-being. Even basic training in reading, with the crudest tachistoscope techniques, can pay large dividends if one is below a basic level of reading like 200WPM & still subvocalizing. And all of these can start paying off immediately.)
I agree with VAuroch that this won’t help much, because in general taking the inside view is a bad idea.
But if you want a few examples of places you’ve gone wrong—both getting a good idea, and executing a business, any business, are much harder than you imagine. For example, you wrote:
“Failure to think specifically about benefits.” “The big issue here is the first bullet point. As spelled out by Eliezer’s article, people are horrible at thinking specifically about the benefits that their idea will bring customers. They’re horrible at moving down the ladder of abstraction. They think more along the lines of “we connect people” instead of “we let you talk to your friends”. Even YC applicants (probably the best startup accelerator in the world) suffer from this problem immensely. I think that this problem is the single biggest cause of failure for startups. (They say that 90% of startups fail? Well >99% of people can’t think concretely.) However, I think that it’s something that could be avoided with willpower, reading the LessWrong sequences, and taking some time to practice your new habit.”
Well, not thinking specifically is one issue, sure.
But the other, MUCH BIGGER issue, is that you might not know what people want. If you’re building something for consumers, there’s a problem in that most people don’t know what they themselves want (imagine describing Facebook to someone years before it existed).
If you’re selling to businesses, then you have to actually understand the business and the market. And understanding markets is incredibly difficult. That’s not to say it can’t be done, but it’s hard even in the best case.
Remember—Some people fail at startups built to serve an industry, after working for 30 years in that industry. They still don’t manage to create a product that’s good enough.
As for the idea that just executing a business is so easy:
Let’s say you decided to build a restaurant. You know exactly, specifically what people want, so there’s no problem with finding a good idea, and you know how restaurants work. Talk to 10 restaurant owners and you’ll even have a much better understanding. Hell, you’re building a business that’s been done millions of times before. This is the polar opposite of a startup in terms of “idea risk”.
And yet, restaurants fail ALL THE TIME. Because the execution of any business is hard. Hiring is hard. Understanding your market, TRULY understanding it, is hard and takes years of experience. Understanding how to hire and manage people is hard. The thousands of little things you do every day, are all amazingly hard. Each one takes time, each one takes experience.
I’m not sure I agree re: lawyers, or about how people/society thinks of this. For one thing, I don’t think most people are that OK with lawyers—they tend to get a lot of flack, and e.g. criminal defense attorneys will often get pushback from people who identify them with their clients, irrespective of the fact that they know the lawyers don’t necessarily condone their clients’ actions.
Another thing—most people absolutely hate hypocrisy. I think it’s considered a death-blow to most people’s arguments. People compliment politicians on their speaking skills, but if they discovered that the politician’s are not saying things they believe in, they’d turn on them. (Well, theoretically—President Trump is a good counterexample).
Btw, an aside, but I also think you misrepresent what lawyers do in some way. They’re supposed to be advocating for the rights of their clients, and supposed to persuade, but they can’t for example lie. They are a check on the system that works from within the system—they need to make sure everyone is playing by the rules, but they can’t just make up their own rules or anything. That said, of course rhetoric is important for trial lawyers.
I’m not sure where, but I remember Eliezer writing something like ~”one of the biggest advances in the economy is the fact that people have internalized that they should invest their money, instead of having it lying around”.
I’m looking for 2 things:
Does anyone remember where this was written? My google-fu is failing me at the moment.
Can anyone point me to any economic literature that talks about this?
Thanks for the generous offer! What kind of requests would you like to get? Specific questions? Certain subjects? etc.
In any case, I’m going to write a bunch of stuff I’d love to have explained more thoroughly, some general, some more specific, if you can explain any of them that would of course be amazing from my point of view. Most of these are just things that came up for me while (re)learning a bunch of math.
Linear Algebra—I have great intuition for most matrix operations based on Strang and 3blue1brown videos. E.g. inverse, change of basis, etc. One thing missing: what is the intuitive “geometric” interpretation of matrix transpose? Considering the transpose is used all the time, I still don’t have an intuitive sense of what it does.
An intuitive explanation of the SVD.
More general: I’m trying to recreate a math degree from scratch, more or less. There are tons of lists of best textbook for each subject, but I’d love more of an overarching “here are the subjects you need to know, here’s the best order to study them” kind of list. There aren’t many great lists for these.
Set Theory—an explanation of the difference between transfinite induction and regular induction. I.e. IIRC, there needs to be defined a whole new kind of induction in order to do transfinite induction vs the base induction used to define things a little past N. Why is another mechanism necessary?
Thanks!
Ray Dalio. Businessman, founded Bridgewater Associates, the largest hedge fund in the world. He is one of the richest people in the world.
From descriptions of Bridgewater, he seems to run it very much in line with most LessWrong principles.
In fact, if you want an instrumentally-rational and (slightly) business-oriented version of LessWrong, Ray Dalio’s principles are it. You can read here, I highly recommend it: http://www.bwater.com/Uploads/FileManager/Principles/Bridgewater-Associates-Ray-Dalio-Principles.pdf .
He is also trying to spread his take on how the economy works, in his video The Economic Machine. See it here: www.economicprinciples.org.
All in all, a fascinating person.
I don’t think that’s the right approach.
A textbook is in many ways the opposite of what I want. In-depth look at a narrow part of the field. I want just the opposite. Also, something that’s more about giving the story behind the field and making the field interesting.
Another good example—Thomas Sowell’s Basic Economics taught me enough to understand the idea behind economics, the basic vocabulary, how an economist approaches things, etc. To learn more, I’m now looking at textbooks on Economics, but I definitely wouldn’t have started there. And for the vast majority of people that I want to just know a bit of economics, Basic Economics is perfect. (Potentially even some lighter texts cold work, e.g. Naked Economics).
Can I take this opportunity to ask about HIIT? What kind of HIIT workout do you recommend? I ask because you’re putting it on the same plane as Anki, so it must be truly amazing.
Very interesting, and I kind-of agree with the conclusion. However, as a few people pointed out, it wasn’t as simple as just buying bitcoin, you had to sell at the right time, etc.. And buying bitcoin was complicated.
But the other problem is that there are thousands of opportunities, things you should do, etc, lying around, with a possibly good payoff in expected value terms. And how many of them do we do? How many of them do we even think about seriously?
Just a few off the top of my head (first two are obvious, then some others):
Cryo, obviously.
AI safety—tons of people in the community agree that’s it’s a serious issue, but how many actively work towards fixing it? (A decent amount, but I’d guess not as much as the “could” do).
CPR training—how many people do it? What is the chance that you’ll one day be in a situation where you need it? I have no idea of the numbers, but considering this is a life-and-death situation, have you looked up the numbers and decided it’s not worth doing?
Similarly, buying an emergency survival pack in case of a natural disaster. Again, not idea of the numbers here, but people do find themselves in situations where they’re without food/water for some period. Do you know the numbers here to decide it’s not worth buying canned goods?
How many people have even bothered to sit down and make sure their health insurance/life insurance/unemployemnt insurance/etc is handled properly?
Even more obvious—sending out resumes every year to find better job opportunities? Or taking a course/reading about finding a better job? This is likely have a massively higher impact than buying bitcoin, not only in monetary terms, but also in life satisfaction impact.
Etc, etc.
Most of the above are pretty obvious and trivial things almost anyone can do. I can probably list a dozen more, some more “standard advice”, some more out there but still probably high in expected value. If I or anyone were to actually sit down and work through these one by one, we’d probably do little else for the next year.
So while bitcoin, in retrospect, may have been the most obvious and immediately high-value payoff, I’m not sure it’s easy to seperate it from all the other things above. Then again, I’m not sure you should—maybe we should have a list of “these are things you need to take care of ASAP” somewhere.
Great overview!
I can give a few words of advice on where to continue from here, if you’re interested. My own background is as a software dev for many years (13 years professionally plus a few years as a kid). I’d bene involved in many different fields, from embedded systems to web development, and recently ran a team of algorithms researchers in 3d printing, so was mildly exposed to computer vision and 3d concepts, but had no serious machine learning. Then a few years ago, I started to get much more seriously interested in ML/DL/Data Science, and have seen been working in the field (running a dev shop).
So, my take: first of all, I personally didn’t much enjoy Andrew Ng’s course, both because it was much too theoretical for my taste, and (in retrospect) because I didn’t remember enough maths from my CS degree to work with the concepts as easily as I should have.
I’d recommend a few things for you as next steps:
1. Coursera teaches more “classical ML” (not deep learning), and without many applications. The absolute BEST followup in my mind is the Fast.ai course (free).
It focuses on Deep Learning, and teaches with a completely practical-minded approach, rather than theoretical. The idea is to, within one lesson, actually *write software*, like a simple program to tell whether a picture is of a cat or a dog. In this course, you will literally be coding practically world-class Deep Learning code within a few hours.
They’re supposedly working on a more classical-ML course, but unfortunately it isn’t out yet.
Seriously, this is my #1 recommendation for anyone trying to learn machine learning, especially with a background in software development. You won’t be sorry.
2. If you’re at all interested in actually implementing ML as opposed to more reviewing the concepts, then you should try a Kaggle competition or two. If you don’t know it, it’s basically a site that allows companies to upload data, then pay prize money to people writing an algorithm that does something specific with the data. E.g. predict how many page views a certain subset of pages on Wikipedia will receive.
Kaggle does a lot of good things for learning ML: It abstracts away all the data-gathering and a lot of the data-cleaning work, which is the heart of a lot of data science/ML jobs, but is not what you want to actually practice, especially if you are a developer and already know how to deal with this. It also gives specific questions and answers that need to be answered, and has a large collection of existing answers.
In short, Kaggle is the place to go practice your ML skills.
3. Learn more math, especially if you enjoy it! I’ve personally been self-learning the equivalent of a math undergrad, partially for my work in ML, partially for fun.
Specifically, as you correctly understood, ML is mostly statistics, calculus, and linear algebra. Based on my own background, I can tell you that my calculus was perfectly adequate for ML. However, statistics and linear algebra I had studied in much less depth, and they’re both incredibly important, and fascinating subjects. Linear algebra, especially, is amazing, and depending on where you study it, you actually learn a good amount of practical implementations, including linear regressino and other ML algorithms. And not only do you learn these applications, you understand them from an entirely new perspective.
For studying linear algebra, I *highly* recommend Gilber Strang’s video lectures on the subject. He is an excellent teacher, not only engaging, but very practical-minded. You should also follow along with his Linear Algebra textbook, and I highly recommend doing the videos and textbook at the same time—the textbook is not a great resource without the videos, IMO.
The major “problem” with Strang’s videos are that he *really* focuses on the practical, engineering, matrix approach of teaching Linear Algebra, to the almost-complete neglect of the more mathematical approach. E.g. he teaches like half the course before he mentions linear transformations, which is *incredible*.
I still think these videos are the best approach for a software developer looking to *use* linear algebra, but I highly recommend following this up with a more mathematically-oriented textbook. Like many others, I like Axler’s “Linear Algebra Done Right”, which ironically takes the exact opposite approach—it takes him 3 chapters to get to explaining what a Matrix is :)
Other than that, I have recommendations for statistics (both Harvard and MIT have great courses on probability), and there’s lots of other great math to study, though not all of it is directly relevant to ML.
OK, hope this post was worthwhile for you/someone. Feel free to ask if you have any questions :)
First of all, I want to join all the others in thanking you for the honesty and for the sharing.
I’m going to give a few of my views of this, as someone who has a fair amount of experience in “startup-land”. Some of this will be “criticism”, but please don’t take offense—it’s really hard to get these things right, and we all made and continue to make mistakes. And you seem to have gotten to some of these conclusions yourself—I’m writing this for the hypothetical other people who may want to start a startup, so making it general. Btw, really long comment, so sorry! :)
First of all, I’ll tell you what was by far the thing I miss most from your post—any talk about money. You’re building a for-profit company, and maybe I missed it, but I have no idea how you planned to make money off of this! I have no idea of the busines plan, at all. Even if making money isn’t really the goal here, unless you plan to live off donations, it should still be priority 1,2 and 3 for any company: You use money to solve most problems (pay to create content; pay to advertise; etc). You also use money as a good proxy for success. You also use money to fix problems like “burnout” by hiring people!
Secondly: I loved Inadequate Equilibria. But the whole “conversation about startups” was by far the weakest part of it, and the one part I think I actively disagreed with. (Also the part I know the most about: Gellmann amnesia anyone?) While I understand the concept of a grand vision, I think Eliezer and probably you are misunderstanding the idea of an MVP. Or at least, the way I think about it.
The idea is not, as Eliezer put it, to build a product that shows one specific workflow. For one thing, you don’t need to biuild a product. But more importantly, the emphasis is not on showing a complete workflow and seeing if people like it. The emphasis is on doing fast experiments. You need to figure out what assumptions you are making about what you’re trying to build, then test those assumptions. This is something you can often do with minimal work, by faking large parts of the product, for example.
One of the pushbacks to this view is that you might not know the assumptions, but that’s all the more reason to have fast experiments—you want to uncover which assumptions you’re making and don’t realize it, as soon as you can. If you think the only way to do this is to build a product over more than a year—you’re almost certainly wrong, except in very tech-heavy cases, which is not your situation.
In Arbital’s, some assumptions you had and could’ve tested:
You believed people will write content, for free. Easy to test—ask people to write it before the product.
You believed you had a superior flow for reading content. I’m still not sure I understand what that full flow was, but again, easy to test—ask Eliezer/someone to write content, and make a static html site with all the “reading” functionalty, but none of the editing capabilties. You could reasonably make whatever workflow you imagine the reading experience to be with a week’s worth of hand-coding html/css, or even a Wordpress site.
You believed you could get people interested in reading this material, and then doing… something? I’m not sure, since I didn’t understand the business plan. But let’s assume it’s “decide to read more material”. OK, easy to test—put one guide up, and ask people to sign up to a newsletter. Or donate money. Or something.
(I want to emphasize that, although I think I’m right, just the fact that Arbital failed doesn’t prove it. Building startups is hard and usually fails.)
Another issue that stems from lack of a business model—what kind of company were you trying to build? It seems pretty obvious, at least in retrospect, that this kind of company is a bad fit for a VC-funded startup. You are not trying to build somethign with minimal chance of success, but with the ability to become a billion-dollar company. I mean, I don’t think you were aiming for a billion dollar company.
But in that case, you should’ve never expected to raise money (and probably shouldn’t have raised money). And you should’ve made sure this is something that could be profitable relatively quickly, to continue supporting the development.
Lastly, I really got the sense from your post that you are all with a very engineering mindset, and very enamored by the beauty of a complex system, and by wanting to build something. Hell, you worked on this for a few years, wrote an entire post-mortem about it, and still I and others in this thread don’t even understand what you’re building! This is not a good sign—systems usually aren’t this complex, certainly not ones that are made to be used by actual people other than Eliezer :)
One more thing about community projects—we’re a community with a lot of developers. We see development projects everywhere. But the real strength of the community is not necessarily in that—if the bottom line thing we want, as a community, is more things like Eliezer-style explanation of hard concepts, that’s hard enough—we should make the journey to creating that content incredibly simple, and while that is arguably what Arbital was, I’d say that “let’s spend a few years to develop a new software platform” is a huge burden. Much better to use pre-existing stuff, IMO. Let’s make a rationality-Stack Exchange. Or a rational wiki (or not :) ). (Not to crticize too hard because I’m not that much in the community and don’t know the details, but I kind of wonder the same thing about LessWrong V2.0 - do we really need to rebuild forum software from scratch just for us? Is that really where we should be spending our community’s talent and efforts?).
To conclude: building starhtups is hard. Building consumer startups is much harder. Building consumer startups that are marketplaces is really really freakin hard. You tried and failed, which is a shame, but you seemed to have learned a lot from this, both about startups and other things (based on Inadequate Equilibria, I think Eliezer hasn’t learned the lessons I would’ve learned). So kudos for trying, kudos for putting yourself out there with this post, and in general, good job!