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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 :)
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.
"Geometric" intuition is basically the way that the 3Blue1Brown YouTube channel would explain things. I'm not sure if you're aware of it, but their "Essence of Linear Algebra" goes through the broad high-level concepts of linear algebra and explains them, with a very visual/geometric intuition for things like basis change, inverses, determinants, etc.
Unfortunately, they never covered transpose :)
Also, I'll take a look at your blog post, thanks!
Theoretically, I'm most interested in things related to Data Science/Machine Learning/Deep Learning, as that's my day job. However, since this is my day job, it's also the area that I know the most about. So e.g. I've studied Linear Algebra, Probability, Statistics etc quiet a bit.
I'm mostly interested in rounding out my specific knowledge with everything else I need to know to have knowledge equivalent to a well-rounded math major.
In terms of what personally interests me the most, that'd be logic/foundations-of-mathematics type stuff, e.g. Set Theory.
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!
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!
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.
Why do you want to buy a hat?
Almost all "non-geeky" / "normal" people don't regularly wear hats. If you're trying to look "better" and "more fashionable", the best solution is to skip the hat, and get sunglasses to protect your eyes
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).
So, do you have a specific marketing plan for getting the word out there about these books?
More specifically, you have access to an entire community rooting for you... how can we help?
(Also, I've been convinced by other commenters here - I normally don't buy physical books anymore, but here I'll make an exception for '"fanboyism" and "gifting" purposes).
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.
It's less the "why do they act that way", more "if you had this superpower, what kind of really weird but powerful stuff could you do with it".
Worm is full of people using superpowers in really inventive ways, in a way that Steelheart/Firefight aren't.
Tl;dr of my post: If you liked Steelheart, I heavily recommend reading Worm.
Long version: So, Sanderson is in my top 5 favorite authors, I think almost every book of his is amazing, and I loved Steelheart.
But shortly after reading it, I started reading the (now finished) online web serial Worm (from Yudkowsky's recommendation on HPMOR). It has a very similar premise to Steelheart, at least initially.
And let's just say, Worm makes Steelheart look terrible in comparison. Worm is just so much better.
Again, I'm a huge fan of Sanderson, and I still like the Steelheart series, but I now read it and think to myself that it's just not even close to realistic, Worm is how people with powers would actually behave.
Seriously, read Worm. And if you happen to read this comment and not have read Sanderson, read his books too (I would start with the Mistborn trilogy, possibly the best trilogy of all time).
FYI, you're mostly right, at least based on my experience. I tend to have a much harder time listening to Audiobooks of SF/fantasy, and a harder time listening to any fiction vs. non-fiction.
I also have a much easier time listening to SF/Fantasy when it's in a setting I already know (e.g. sequels, books I've read before, etc). Also easier to listen to books from authors I read a lot (but that may be true in general, come to think of it).
I still highly recommend anyone who can to listen to Audiobooks, at least of non-fiction, as one of the best and easiest hacks around.
Do you listen to Audiobooks at all? Are you only specifically against SF as an Audiobook?
I ask because I'm a huge fan of Audiobooks, but I've long believed that SF (and fantasy) are both particularly hard to like in Audiobook format. Non-fiction is by far better.
(I do still listen to some SF/Fantasy on Audiobooks, but it's usually authors I already know, or in worlds I already know).
Thanks! Fixed in comment.
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 agree. Perhaps this should be qualified as "most important habits that are only recommended in the Rationality community". Otherwise there are plenty of other skills we can add (another example - start saving money early, etc).
Backed!!
This is amazing news, both that the book is coming along, and that there will be a professional Audiobook version. This will make it easier to spread the sequences, and may even mean that I'll actually finish the sequences myself, something I still haven't done.
Btw, two logistical questions (for Luke mostly):
- Was there any similar campaign for the book version?
- I understand that MIRI isn't paying for this Audiobook version? I ask because my donations to MIRI are now employer-matched, as are I assume other people's, but this Kickstarter campaign can't be employer-matched afaik, which is a shame and a "waste" of potential donation. Any way around this? (I also donate to MIRI, but I want to specifically donate for this Audiobook being made).
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.)
Did the survey. It felt much shorter this year.
(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'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?
Question for anyone that's taking the course: is it worthwhile for the average LW'er? I assume most of us have an above-average familiarity with these topics.
Isn't that just technological progress? Except for asking people for advice, nothing else there changes how people think, so it's hard to call it a rationality technique IMO.
I believe there are meaningful things people believe/do nowadays that they didn't 300 years ago (e.g. using the scientific method).
Unfortunately, for all these things, they're either: a) adopted only by some people, not the majority. b) As DanArmak says, adopted only because of "peer pressure" or other social reasons.
Now, that's not to say CFAR's mission isn't still worthwhile - raising the sanity waterline of just certain segments of the population, e.g. the top X% in terms of intelligence, is still of great importance.
But if there really aren't general "rationality techniques" that have been adopted by most people, if the average person today is no more rational than a person 500 years ago, then I suppose you're right - my bottom line might need to change to "maybe we can't reach the general populace".
That's a very good point, although I think a good a first stage is to find what techniques people are actually using, then try and understand why.
Perhaps, but I'm trying to convince intelligent people that there are real changes we can introduce that will be adopted by most people, so I'm not sure the lottery fits the bill.
" 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.
I agree that textbooks are undervalued, but I'm still unsure that textbooks that meet my requirements exist.
Do you have any examples of textbooks that help a layperson understand economics in the way I envision that's better than a more "popularized" book?
Relatedly, The Law of Superheroes is a funny look at applying Law to pretend cases that could happen in a world with superheroes. Very recommended.
It works well for what I want, but isn't in-depth enough to really leave me feeling that I've learned law. But the law is tricky in that, afaict, it's a lot of details and unofficial know-how, so many it's not a field where a book like I describe could exist.
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).
I once read "I will Teach you to be Rich" by Ramit Sethi. It went into a fair bit of detail on this.
I didn't finish the book and can't really recommend it, since most of the advice was very US-centric (e.g. optimizing credit scores isn't relevant for me). But it might be a starting place.
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 find most interesting the question of which God/religion to believe in. How do they deal with the fact that the actual, historical reason that they believe in their specific God/religion is because they were born into it (most likely - not true for everyone). Have they ever considered switching religions? What was their reason not to do so?
This usually leads to very interesting discussions on the "proofs" of their religion. And they tend to be interesting indeed.
Also, I might start the debate off by more general questions, e.g. "how do you define evidence, what do you consider knowledge to be", etc. E.g. I really want to understand how they know that their God/religion is founded on truth, and not on "alien teenagers", Matrix, etc. At least theoretically.
Like Anatoly, I also really liked the book. It's not very deep in my mind, but it's just good ol' fashioned fun, for the kind of people who love hearing of highly technical matters (about which they honestly know little, at least in my case).
Glanced at the "Have a nice day" article. I'm absolutely shocked by how much can be said about a banal expression, especially how much negative stuff and criticism people level at it. Wow.
What made you stumble on it?
It gets worse. Most of his fantasy novels are actually connected into one world (called the Cosmere).
He guesses there will be a total of 30-40 books in this world.
Btw, for anyone that doesn't know, Brandon Sanderson was chosen as the author of the final Wheel of Time books, the ones that came out after the original author Robert Jordan passed away. So yeah, he knows what happens to people who start 10-book series.
What I meant by that was:
The magic system is basically comparable to him inventing a world with extra laws of physics. The magic is usually well understood, at least eventually, and is basically treated like just more physics.
E.g. (ROT13'd for minor spoiler): Bar bs uvf obbxf pbagnvaf n flfgrz gung, jura crbcyr qevax inevbhf xvaqf bs zrgny, gurl ner noyr gb "ohea hc" gur zrgny gb tnva pregnva cbjref, sbe rknzcyr, gryrxvarfvf. Guvf vf irel jryy haqrefgbbq naq hfrq, lbh haqrefgnaq gur zntvp, gur yvzvgf, vg erdhverf fbzr xvaq bs ryrzrag gb cbjre vg, rgp. Va bgure jbeqf, vg fbhaqf yvxr ryrpgevpvgl jbhyq fbhaq gb fbzrbar jub qbrfa'g xabj nobhg vg.
Guvf vf abg gur xvaq bs zntvp flfgrz jurer enaqbz crbcyr ner noyr gb qb guvatf juvpu lbh arire ernyyl haqrefgnaq, naq gung ner oneryl hfrq. Guvf vf zber n jbeyq jvgu rkgen ryrzragnel sbeprf.
Just finished Brandon Sanderson's book "Words of Radiance". It is the 2nd book in a (projected) 10-book series, and came out last month.
I thought it was a wonderful book. It developed the story from "The Way of Kings", some parts in obvious ways, but also in some new and unexpected ways. The world that Sanderson developed for this series is clearly huge, with many different actors and sub-stories going on.
Also, one sub-story in particular was very fun for me as an LW'er. I'm talking about: Gneninatvna, naq uvf VD punatvat rirel qnl (rot 13'ed).
Btw, I love Brandon Sanderson's work. It combines very "realistic" magic systems with awesome characters, and an epic back-story. I highly recommend reading the Mistborn trilogy, I consider it the finest fantasy work around.
The biggest problem I have with this thinking is that it's a false dichotomy - it's not "Salary or startup" at all, and the fact that most young software professionals see those 2 as their only options saddens me.
There are plenty of other routes to go - freelancing, for one, which done well can give both higher earning potential, as well as more flexibility in terms of how much money you can earn. An effective altruist may well decide to work slightly longer hours for more money, something that isn't as possible in a normal salaried position.
Another option is starting a consulting practice (e.g. what I do), again, I'm still early in this game but it may well offer a higher expected value. (Or not - I don't have figures).
Another option is to start a small bootstrapped product company. If your aim is simply to maximise your personal cash in order to donate it, small non-VC product companies have a lot of merit - I think (again, no real proof and totally anecdotally) that their expected value is higher. And if you're into maximising expected value irregardless of how, this may make sense, even if a small product may have less chance of "changing the world" (one of the reasons that it's more likely to succeed).
I'm just saying, there are plenty of options besides being a salaried employee or taking VC money, and money of them seem to be better, on the whole, especially for young software professionals who could use to run a real business and gain valuable information on how running a business looks like.
General information-getting (most of this is general "stuff I recommend to anyone", but some of it does require money):
- Get a Kindle. Easily worth its price, if you can afford it.
- Get books. Much easier to get buy them from Amazon than getting them from anywhere else.
- Make a subscription to Audible.com and start listening to Audiobooks. Incredible life improvement to be able to turn moments I'm otherwise not mentally occupied, with more time to read.
- Get stereo bluetooth headphones. These are headphones you can easily stick in a pocket, turn on quickly and start listening to your audiobook. Makes the experience of audiobooks MUCH better.
Some other obvious stuff:
- Turn money into time. Hire a cleaner/others to do chores you don't want (laundry service that picks stuff up form your house? etc.)
- Hell, you can probably hire a chef or equivalent to cook great and healthy meals.
- Use taxis/other expensive but time-saving choices for travel.
Oh, and in general, live closer to your job. Incredibly important, easier to achieve with money.
I've just scratched the surface for now, but that's off the top of my head.
- People can change (e.g. update on beliefs, self-improve).
- How to choose your actions - think about your goals, think what steps achieve them in the best way, act on those steps.
- There is such a thing as objective truth.
Amazing how the basic pillars of rationality are things other people so often don't agree with, even though they seem so dead obvious to me.
IS this a good book to start with? I know it's the standard "Bayes" intro around here, but is it good for someone with, let's say, zero formal probability/statistics training?
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.
Your post is exactly why "how many startups can I conceivably do" is an important question. If failed startups take on average 5 years to fail, which is a reasonable assumption for a semi-successful but ultimately failed startup, then doing 4 startups takes 20 years of your life. For most people, working 20 years at a startup and making relatively low wages is not feasible or desirable.
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.
That's great, thanks for the info!
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.
So, we're what's called a "Professional Services" firm. This term is usually used when talking about e.g. Accountants, Lawyers, etc, but is just as relevant for a Software Consultancy. I'll go a little into the idea behind professional services firms in general, then get back to talking about us in particular.
There are many, many different types of Professional Services firms, but the basic business model is usually the same - you're selling your time for money, and people pay because of your expertise and experience in the field.
But here's where large firms make their real money: the firm gets projects based on the expertise and experience of the "managing partners", and then a combination of the managing partners and juniors perform the actual work. For example, a law office will win a contract because of their experience and the expertise of its "Name Partners", and they'll charge let's say $500 an hour for an hour of Partner time. But they'll also charge $450 an hour for an Associate lawyer. The firm pays huge salaries for the name partners, so they're basically not making any profit there. But they pay tiny salaried to the Associates, for a large profit.
This is called "leverage". This is how a professional services firm grows and makes a profit - leveraging the skills and reputation of key, highly payed employees, to sell the work of lower-payed employees.
Most Professional Services firms can be placed on a moving scale as to how much expertise vs. leverage they have. An example of a highly skilled "firm" - a team of brain surgeons. They're basically paid amazingly well, and have minimal leverage. An example of a consultancy with a lot of leverage - a company that builds websites for restaurants. Building a website for a restaurant is 90% repetitive work that can be given to junior employees, with senior employees focused on finding work and growing the reputation of the business.
So where do we fit in all this? In our case, as a rather small firm, we're mostly on the "expertise" side of the equation. We have a few people in the company, and we're all very experienced Software Devs. Companies hire us for consulting based on our experience, and for development because we get things done quickly and well.
Of course, the founders of our firm (myself and 2 partners) are much more experienced than most of our employees, and as we grow, that gap will continue to grow as we take on more junior programmers who need more training, but are underappreciated by the market and just need someone to give them an opportunity and teach them the ropes.
So there's an answer about the basic business model of a Professional Services firm in general. I didn't go into any of the specific of a Software shop in particular, but there's a lot to say about that as well, e.g., there are 100's of niches of Software dev shops - are you targetting large companies or small? Startups? Tech-savvy customers? People who want software projects? Putting people on-site at a customer's company? Each one of these niches is very, very different, and it's a fascinating topic for me at least, since 2 years ago before starting this company, I would never have realised how different all these niches truly are, or even that they exist.