few hit AI apps exist because LLMs are what i’d call very “strangely-shaped” tools.
most tools are built with a specific purpose in mind like a screwdriver or a car.
but LLMs were something we stumbled upon by predicting text and playing with RL – we didn’t design the shape of them beforehand, we just let them naturally evolve into what the loss optimized for.
it’s clear they’re good at many things, but they are so strangely shaped that it’s easy to fall into traps when making products.
AI agents are a good example of a trap (for now), where it’s easy to spend months trying to perfect your scaffolding yet never quite reaching the level of reliability you’d hope for.
long-term memory implemented solely via RAG is another trap. it’s just tempting enough to try, but the results aren’t as good as they should be.
other common inadequacies include poor search, hallucinations, and high inference costs. but there’s a long list of subtle weaknesses which few tinkerers ever notice as well as many weaknesses (and strengths) which remain unfound.
much of the frontier of LLM posttraining is currently concerned with these inadequacies – wondering how we can mold these strangely-shaped LLMs we have grown into a slightly more suitable form for the problems we face.
this is hard, even for the major labs. as we slowly progress on it, i’d expect to continue to see most AI products attempt to solve the same problems via the same methods, further suffering from lack of distinctness both in performance and aesthetic, because they don’t have the right connection between research teams and product teams (or perhaps the right vision to begin with).
it’s telling that among the few recent consumer successes like midjourney or perplexity, competitors are hyper-focused on directly copying winners rather than exploring the vast new frontier of things which could be built instead. this makes sense because the frontier is strangely-shaped, as a result of the underlying catalyst itself being strangely-shaped.
it’s not uncommon for services to launch a feature literally called “AI” which is primarily composed of literal magic wands and glitter emoji simply because the product designer has no idea how to actually convey the intended experience to the user. 2024 is certainly not a year one would be fired for using too much AI.
I expect it to get more interesting later this year and especially in 2025, but it’s still been a surreal experience continually contrasting my day to day life in san francisco with that of the actual real world (note: SF is not real in this example).
the above is also relevant to some of the reasons i have longer agi timelines than i did a few years ago. agi is not a strangely-shaped tool. in fact, it is quite literally the opposite.
This post has a bunch of unordered youtube videos with music I love A few themes: strong piano leads, polyrhythms, Japanese influence, OSTs, beautiful singing Some of them are niche (~1-10K YT views) so hopefully you find something new you like!
Logical Emotion: トライアングルどら息息子
Dimash Qudaibergen: SOS d’un terrien en détresse (Piet Arion Cover)
Polyphia: Playing God
Boa: Duvet [Serial Experiments Lain] (Extended)
Kevin Penkin: Hanezeve Caradhina [Made in Abyss OST] (Takeshi Saitou Cover)
Deemo: Marigold (ふぃくしのん / phyxinon cover)
Nobuo Uematsu [FFXIV OST]: Great Gubal Library (Hard) Theme
Masayoshi Soken [FFXIV Endwalker OST]: Piano Covers by SLSMusic
Tosin Abasi: Thump
Keiichi Okabe [Nier Automata OST]: 壊レタ世界ノ歌 / Weight of the World
Complex systems of life often contain a multitude of shortcuts: sources of alpha which, should you choose to exploit them, give notable advantage. Many classes of these shortcuts are features rather than bugs, and it is no accident of many systems that only a select minority are able to tactfully navigate them.
In many cases there exists zero-sum shortcuts, which, if all of society were to adopt them tomorrow, would have their effectiveness instantly curtailed to zero. Luckily there also exists many which are positive-sum and benefit both parties involved. This post contains a few notes and examples from both classes.
Venture Capital
In venture capital, it is strongly preferred that one receives an introduction to an investor prior to pitching them. This is, in general, a much easier way to meet with many classes of professionals than a cold-email.
At first glance this may appear shallow or nepotistic, but it’s more accurate to view it as one of the first tests to becoming a successful founder. If you’re unable to find any way to get an introduction to a person, it is more likely that you may also have difficulty with other similarly important roles that a founder must perform such as recruiting, sales, management, and further fundraising.
This warm-introduction requirement therefore functions less as “this person happens to know someone”, and more as “this person has the right set of traits in order to acquire this warm introduction, which we consider a modestly bullish investment signal”.
Due to the generality of this phenomenon, this paradigm repeats itself in many categories of society.
Job Hunting
It is much easier to get a job somewhere by messaging someone at that company and asking them to help you out, preferably with some baseline level of evidence that you are at least reasonably competent and aligned with the organization.
This may seem obvious, but at any given moment there are millions of reasonably-intelligent individuals bulk-sending their CVs to hundreds of unsuspecting organizations, when their time may be better spent narrowing their hit list down to only a select few companies, then delegating several hours of their time towards each of them.
You can go much further than this, of course. To give an example: the few times I’ve had an employer other than myself were because I specifically asked to be hired for a role I made up. Rather than seeing an available position on a job posting, I looked at the intersection between the needs of the organization and my own abilities, and proposed that intersection directly to the CEO as my job description. Many find this to be much more agentic than something like “asking the neighbor with overgrown grass if he will pay me $20 to mow it for him”, but the exact same thing is happening in both of these scenarios. Negotiating your salary is in a similar category of actions.
The reason why the above two sections describe intentional shortcuts is because they’re positive-sum. Negative-sum shortcuts are often unintentional (for example, stealing merchandise from a store), and zero-sum shortcuts can be of arbitrary intentionality.
User Support
Many are familiar with the basic techniques of escalating one’s user support channel with a large corporation to an agent which is both more responsive and more capable. Some classes of individuals may formalize this as e.g. “I’d like to speak with your manager”, but there’s often more effective methods depending on your use case. Patrick McKenzie has many good examples among his blog posts, and I’ve included a wonderful excerpt from him on banking and credit reports below.
On occasion, when I’ve had a particularly egregious and frustrating issue with a large company, I’ve emailed an executive in the relevant department with concise and kind language explaining the issue, where its alleviation is in the self-interest of my counterparty. This can sometimes be done all the way up to the CEO, but results vary depending on who both parties are, what the issue is, and how it is communicated (this is, however, a skill you can very much learn and perfect).
I’m fortunate to have a twitter account with a large amount of founders and investors in my following, which affords me the luxury of sometimes having CEOs fix issues I complain about. You don’t need a twitter account for this though; there are many executives and engineers that read forums like e.g. Hacker News and will directly respond to the right classes of issues on occasion.
Every Day Life: Flying
If you spend time thinking about the systems you regularly interact with, you can forecast some potential shortcuts by modelling both the incentive structures of the arbitrators of the system as well as the behavior of the average system participant.
Simple example: I fly pretty frequently. I often do things like:
Changing my seat an hour before takeoff to get two or three seats to myself. Laying down and taking up a full row is a much better experience than first class! This is done by combining 1) last-minute seat selection with 2) picking flight times where the flight is likely to be <80% full (which is unfortunately not a given for an arbitrary itinerary)
If I’m feeling particularly voracious when flight attendants decide to hand out biscuits, I might ask for three of them. I’ve never had a response of ‘no’ as there’s no reason for them to decline. I never ask for additional pretzels, should my choice of airline condemn me to such a fate.
If I want to board earlier than my boarding class, this is generally not scrutinized. I don’t abuse this, but sometimes it is simply more convenient both for myself and others (one reason it can be positive-sum is that I’m particularly quick both with my movement and with handling any luggage). Some airlines are okay with you taking up a first-class seat without paying for it, should one be empty.
Should the airline lose you your flight (or they require a set amount of passengers to switch flights), the compensation offered to is often highly negotiable (as most things in life are!), and can take many forms (flight credits, class upgrades, lodging, etc).
If you fly frequently in the US you should get TSA pre-checked. The advantage is more “reduces the variance and maximum time through security” rather than “reduces the average time through security”, as the former allows you a significantly more generous grace period. It’s also worth looking into credit card optimization if you travel frequently, but I’ll consider this outside of the scope of this post lest it turns into the equivalent of “they don’t want you to know this but you can bring candy inside of the movie theater”.
Exercise for the reader
Think about a system you regularly interact with and take some time writing down the incentives of the actors within the system. Think about actions which could be taken which are not frequently given as examples to follow, but which nonetheless match the ‘desires’ of the system.
It will be easier to find zero-sum examples in systems which are less heavily-optimized by market structures, e.g. searching for a secret to getting rich by trading derivatives better than anyone else will probably result in disappointment, whereas acquiring multiple snacks while on a flight won’t be a problem. I’d suggest picking something fun which is a quotidian yet mostly unscrutinized part of your daily life.
Try to come up with novel ideas, ideally by writing down things that come to your mind with as few stimuli to distract you as possible. I find this to be a really good exercise both in critical thinking and in agency.
If you enjoyed this post you may like other posts or my Twitter account. Thanks!
If you have important video calls (for example, you fundraise as the CEO of a company), you should have a good webcam setup. This post contains everything you need for one, at a cost of $700-$2,000, depending on which options you choose.
I. Camera
Most webcams are not very good, and you’ll want a real mirrorless camera instead, optionally with a better lens:
Buy a capture card for the camera for the best video quality and lowest latency: Elgato Cam Link 4K ($90)
IV. Mounts
You probably want to mount your camera behind and above your primary monitor. I use a large desk mount for this, but if you are often travelling or on a laptop, a smaller one works.
You’ll have to change a few settings on the camera to have a good streaming experience.
It’s a popular camera, so if you don’t know how to do something, just search on Youtube. I found this video which helped me with a few settings such as: set the overheating threshold to high, add ‘USB streaming’ mode to the quick menu if you are not using a capture card, and turn the steady shot option off.
The most important item in this list by far is the camera – the microphone and lighting isn’t nearly as crucial for a good setup. Special thanks to Cory, CEO of Spellbrush, for helping me with all of this myself!
Twitter/𝕏 is one of the best social networks in the world.
It’s among the best places to make friends, find a job, find co-founders or investors, attend events from, date from, learn from, and now even make some cash on the side from. This is still true as of 2024 (last updated: Oct 10 2024).
Despite this, many people haven’t given it a serious try and are missing out, likely because it takes time to learn how to make your Twitter experience great. In order to help remedy this, this post will cover:
X premium (previously Twitter blue) is generally worth it. Although the value it adds in some areas is subtle, if it helps you out even a bit socially, it will easily be worth $8.
An example of this is if it encourages someone to respond to you, check out your profile, or read your DM, when perhaps they otherwise wouldn’t have. Premium is purported to give algorithmic boosts, making you more likely to appear in the For You feed and causing you to appear higher in responses to parent tweets, but I don’t have explicit data to support this.
If your account has a large amount of impressions (5M+/month currently) you will make money from X Premium, so this should be a no-brainer. Based on the numbers I have, you should get a CPM of $0.01, although some accounts get higher rates. If you have 5M impressions per month, this should make you $50/month. Some accounts that I surveyed have a CPM of up to 5 times this as much. This may be due to having a much higher-value audience from an advertising perspective (many founders, investors, etc), or due to other unspecified favoritism.
I looked at the accounts I consider the highest-value, and around 50% have premium, so it’s a good signal that you’re a strongly above-average account.
Strongly consider trying out the lists feature of twitter! Lists are a collection of accounts that you choose which constitute a separate feed that you can browse. Twitter lists can be public so that anyone else can browse and follow them, or private so that only you see them.
The best two ways to use lists are 1) to make lists for specific topics you are interested in so that you can just browse that topic, and 2) to make lists of high-quality accounts which you don’t want to miss any tweets from.
You can add someone to a list by clicking the ‘…’ on their profile and then ‘Add/remove from lists’.
I personally use a ‘high priority’ list with ~140 accounts on it, allowing me to check this list in full daily with only a few minutes of time. This makes sure I don’t miss anything from the accounts that I think are the highest value. A subset of this list of people on my links page.
Bonus #1: lists do not have any advertisements on mobile
Bonus #2: you can pin a list on the mobile app so it appears at the top of the main app view next to the ‘for you’ and ‘following’ feeds. This can be done by visiting the lists page and then tapping the pin to the far right of a list.
Although my lists are not public, some others are! Here are a few examples compiled by Lama:
Twitter has a DM feature. You’re probably under-using it.
You can just talk to people. It’s okay if they are a famous researcher, a CEO, or even a billionaire. Many of them not only have their DMs open, but will check them. The worst that may happen is you don’t get a response, and that’s okay too.
This isn’t to say you should be spamming people – you should definitely focus on starting a conversation when you think it will provide value to both participants. But Twitter is simply a network of humans, and humans love to socialize and make friends and help each other out, and it’s important not to forget this. No matter how much fame or money someone has, there is almost always something they are looking for more of in the world.
A cold DM on twitter from someone who you have ‘seen around’ is significantly less cold than a cold email, where you see nothing but an email address and name. If you are, for example, looking for a job at a company, you may want to look at who is hiring for that company on Twitter and ask them how you can improve your chances.
When I went to San Francisco for the first time I didn’t know anyone there. I had zero friends. But what I did have was an anonymous Twitter account with 400 followers! I sent 6 cold DMs to some people who seemed cool and 4 of them agreed to hang out with me (one non-response, one busy). I had a great time with all 4, and I still chat on and off with two of them to this day.
I know a lot of people who have dated off of twitter and many others who have met their wife or husband from Twitter. I haven’t done this myself so have fewer tips in this area, but it probably beats the state of most dating apps.
Make sure your Twitter DMs are open (not verified-only, explicitly check this setting as for some users it was modified!) unless you have a good reason to close them.
IV. Muting & Blocking
You can mute keywords of things you don’t want to see. This was useful to many users during the NFT bubble, and in general can be a good way to keep politics or outrage-bait out of your feed.
You can also mute or block users. Muting a user ensures that you don’t see what they say, while blocking a user also ensures that they cannot respond to your tweets. Blocks can be considered rude the user will know you blocked them if they try to visit your profile), so muting may be a better idea in some cases (which has plausible deniability, should you desire that).
Some users strongly advocate for the liberal usage of mutes and occasional blocks, although if you aren’t overly political and don’t engage with trolls (which I encourage!), your need for them should be minimal unless you’re otherwise excessively controversial and/or popular.
With that said, your twitter account is yours and your time here is likely limited, so make sure you’re enjoying yourself rather than spending your nights arguing with strangers.
V. Likes
Liking a tweet makes the twitter algorithm more likely to show you tweets similar to it. I don’t use the For You feature frequently, so my personal usage is a little different. I sometimes use likes in a manner almost close to read receipts: the cost of clicking like is very low, it’s nice to notify people that I have read their post, and it also means that my likes are not particularly indicative of what I actually like, so it creates plausible deniability should someone point out that I ‘liked’ a tweet which goes against a given narrative.
If you subscribe to twitter you can hide your likes page from other users if you don’t want anyone to be able to visit your profile and see all of them in one place. As of late 2023 Twitter has also added a bookmark feature within the app which can be useful for saving content.
If you see tweets from someone you don’t like, either unfollow them, mute them, or block them.
I generally unfollow accounts which are excessively political, and my Twitter experience is vastly improved as a result. Whenever something outrageous is happening that is covering the headlines (e.g. every day of ‘US politics’), I often don’t even see a single tweet about it. If it is something that actually matters and affects me, it’s likely someone I follow will bring it up. Twitter has been experimenting with many low-quality For You feeds to increase engagement as of mid-2024, so sometimes this isn’t enough and you’ll have to stick to using alternative feeds.
Experiment with using the Following feed rather than the For You feed. I find my For You feed to be mediocre at best, and an easy way to waste time without getting much value.
VII. Advanced search
Twitter has an advanced search feature which lets you search by account, engagement, date range, included words, excluded words, and more.
It is not the default search or accessible via the app, so many people do not know about it. You can use it by visiting this page: https://twitter.com/search-advanced
VIII: Desktop Keybinds
If you use twitter on a desktop or laptop, you may find the keybinds useful!
Frequent-used keybindings are shown below as well as the full keybind list from twitter.
Frequently-used Twitter keybinds
Twitters’s full list of keybinds, itself accessible via ?
IX: Security Features
Performing an audit on your account security is strongly suggested.
Here is a great guide showing you the features available and how to set proper 2FA (TOTP rather than SMS).
How Twitter Accounts Grow: 0 To 1,000 Followers
I. Foreword
Being popular on Twitter is probably not what you want.
You probably want something that correlates with it, like reputation, influence, friends, or money. You can make great progress on these metrics without having an absurdly high follower count. If you think do in fact desire true fame, my suggested reading for you is Reasons Not to Become Famous by Tim Ferris, or the replies to any tweet Elon makes.
Ask yourself which is more valuable, a twitter account with 100,000 followers randomly sampled from the Earth’s population, or a twitter account with 1,000 followers entirely comprised of CEOs, journalists, billionaires, and heads of state? I’d take the latter any day myself.
This may be an extreme example, but it’s true that higher-quality conversation is harder to find in the replies to larger accounts. Elon Musk may be an interesting person, but the average reply to his tweets is anything but that. I personally find the sweet spot of good conversations to occur with accounts in the 1K-20K range, but your mileage may vary.
Starting from zero followers sucks. Even if you post something good, it may go entirely unnoticed. Here are some tips to help you out.
II. Put an unreasonable amount of effort into your content.
This is the most important tip here, and that is why it’s first. The Internet is filled with content, and if yours is significantly better than average, it’ll help your odds tremendously.
If you’re summarizing a research paper, don’t just paste it into ChatGPT and tweet whatever comes out. Go over sections of it yourself, help explain it as clearly as possible, add or even hand-annotate and crop images yourself, and so on. A good example of an account that quickly grew from 0 -> 70K in a matter of months with this strategy is AI Pub.
If you have years of interesting experience in a field, you may just be able to tweet stream of consciousness thoughts and takes on things successfully, in which case the above doesn’t exactly apply: the unreasonable amount of effort that you put in was applied elsewhere (e.g. in your career), and you’re just translating your knowledge from there to Twitter. In general long posts are not a great idea and should be separated into threads, although Andrej’s tweets are particularly high-quality, so I included him as an example.
III. Make your tweets as easy to consume as possible
Most tweets which go viral are very short and easy to consume. The exception to this tip is ‘essay’-style threads like the example shown above which have a different art to them. You should generally delete as many words as you can from a tweet, space out any sections of a tweet which are long, and then apply this style of thinking to everything else too. Images should be cropped so they’re easy to read and quick to consume, videos should be shortened to not be too long and have an alluring thumbnail, and so on.
IV. Respond frequently, early, and with high-quality content
When someone popular tweets about something you know a lot about, respond to it with something useful (or funny). If you do this shortly after the parent tweet was made, there’s a good chance you will appear near the top of the responses, enabling you to piggyback off of the popularity of the original poster.
One of the best things about this is that people will notice. If you give high-quality responses, even accounts with 6 figures of followers will read them and notice. That’s all it takes to talk with the main characters of the world: your desire to post a response to them on Twitter.
V. Source followers from external locations
If you have other social media accounts (or any friends), you can direct people to your twitter there. I like to include a link to my profile at the end of blog posts in case someone wants to follow me. If you have a friend who has a lot of followers, a single good quote-tweet or endorsement can really speed up starting a new account!
Most growth is based on your current number of followers (e.g., you should expect to gain a given percentage of followers per month), so it can take high-quality accounts months to go from 0 to 1,000 followers. Don’t give up and stick with it, and you’ll make it eventually!
How Twitter Accounts Grow: 1,000 To 100,000 Followers
After you have a few thousand followers, you’re at the point to where your tweets have a large initial seed userbase. This is great, because now if you post something with the propensity for virality it has a much better chance of getting thousands of likes and being ‘picked up’ by the algorithm.
To help demonstrate how social media growth generally works I’ve made a few charts of my Twitter metrics from a period where I was having fun growing my account.
Aggregate followers over time
This first graph is my followers over time. It is going up, and the slope is mostly increasing. That’s good.
To make it more useful, now we’ll adjust for the amount of followers that I had in each month to show the relative growth instead of absolute.
Despite the number of followers increasing more and more over time, the percentage of followers that I gain in a month is surprisingly constant. My month-on-month growth was around 24% on average.
If you are familiar with the power of compounding this should strike you as a very impressive metric and is the exact type of thing venture capitalists look for in the revenue or usage metric of companies. A 24% MoM growth rate would amount to 1,300% per year or 40,300,000% across five years.
But in some months I tweeted more, and in other months I tweeted less. Let’s take that into account to make another chart.
This graph is answering the question “for each tweet that I made, by what percentage did it cause my account to grow, on average, per month?”. Although it’s a bit messy, it is still surprisingly consistent and its data has the lowest standard deviation out of all three graphs.
Thus, numerically speaking, to grow your twitter account:
Tweet frequently
Tweet consistently
Do this for a long time, ideally for years
The best example of someone that has done this well, but for Youtube instead of Twitter, is MrBeast. He consistently made videos for years, getting very few views, but kept at it and kept improving until the subtle 10%/month gains compounded. The first few years sucked, but now 2% of the Earth’s population watches every video he releases.
With that said, none of this will matter if your tweets are low-quality. The above guidelines assume both that there’s some value in your content but also that your goal is to maximize follower count. This isn’t the same as my personal goal, so I usually don’t tweet more than once or twice a day, if that.
Okay, but what do I actually post?
Well, that depends on what kind of followers you want. You can become popular by posting 4chan memes, but if your goal is to network and get a job, this probably won’t help you very much. You could also become popular by posting research summaries of arxiv papers, but if your goal is to hang out with the boys and joke around, this might not hit the spot.
Broadly though, you should decide who you want to surround yourself by (you will become more similar to them, so be careful!), and what type of value you will provide in order to achieve this.
Most social media accounts can be mapped into a category based on the type of value they provide. Broadly those categories are:
Funny
Interesting
Useful
Sexy
Entertaining
These are rough categories, but if you think of some of your favorite twitter accounts, you should be able to map them onto one or more of the above categories.
The next section will go over more explicit advice that might help you to have a good time on Twitter.
Social Tips for Success
I. Be positive and constructive
The most important tip I have is to be positive and constructive. You can get engagement with dunks, but the followers and network you’ll end up with won’t be pretty. I’d avoid the political areas of Twitter at all costs.
II. Err towards saying things rather than being shy
This is hard for some people, but exposure therapy is the best way to fix it. Never be scared to tweet something because you have a lot of followers, or overly important followers, or anything like that, as long as it’s something you actually want to say. This is good advice for life in general. Trying things is good, and not trying things is bad.
III. Optimize your content for twitter
Linking to a 30 minute youtube video will generally get very low engagement, but specifically cropping out the best 30 seconds and adding a quick summary, quote, or thread will do much better. You should keep most posts short and crop images accordingly.
IV. Don’t tweet walls of text
Both spacing out your tweets and tweeting with images are usually good ideas. If the first one or two sentences of your tweet aren’t interesting, few people will finish reading it. It’s possible to succeed with long-form essays and threads if you have good content, but this is usually more difficult and vastly depends on your niche. I strongly advise reading Scott Alexander’s writing advice as well, even if it wasn’t made for Twitter.
V. Make your own images
There’s a lot of value in making custom images. Most of my best performing tweets contained images that myself or someone else made, some which took as long as 5-30 minutes to make.
Having a pseudonymous account can be advantageous. A lot of people are scared to tweet their true thoughts publicly in a permanent form with their face and name directly adjacent to them. This is understandable and there’s nothing wrong with that. Even if you don’t have your name and face on your account you can still make friends, meetup with people, and even network professionally or get a job as long as you’re willing to share more details with individuals. A great example of someone who has managed this well is roon.
You can probablyget away with tweeting more provocative content than you think. Cancellation may have been a formidable force a few years ago, but as of 2024 unless you’re diving straight into hard-politics you shouldn’t let it scare you out of trying to live your life.
If you’re fortunate enough to be skilled in a field like software engineering, you have strong marketplace value and leverage. Consider working for an employer which has courage and will not fire you over a few people on the Internet typing mean words into a text box (thanks @patio11).
VII. Cold DM people more
You should cold DM people more. It’s a great way to get a job, make a friend, find a partner, and much more. If you’re curious why this tip has been repeated twice, it’s because it’s at least twice as important as the other tips.
VIII. Only follow people you want to become more similar to
Only follow someone if you want to become more similar to them in some way (at least with respect to the content that they tweet about). Following someone gives them a limited type of write access to your brain, which for powerusers may be reinforced multiple times a day over the course of many years. This will significantly alter the type of person that you become, so use this super power wisely.
A relevant quote from Moxie Marlinspike on career advice is to look at those senior to you in a field and decide if you’d truly like to become just like them: “They are the future you. Do not think that you will be substantially different. Look carefully at how they spend their time at work and outside of work, because this is also almost certainly how your life will look. It sounds obvious, but it’s amazing how often young people imagine a different projection for themselves” (source)
IX. Optimize for virality only at the cost of your soul
I would advise not purely seeking virality, even if you manage to avoid politics. Our best selves are probably not consistent with the versions of ourselves that maximize engagement online. I’ll leave you with the below quote from Dario Amodei, CEO of Anthropic:
That’s all I have here for now! If you have feedback to add, please add it to my tweet for this post or send a DM. If you made it this far you may also like some other posts on this site.
FAQ / Addendum
Hasn’t Twitter gotten worse with Elon?
I don’t personally find that the amount of value I get from it has gone up or down by much since the acquisition. but I do find that it takes more effort to get a good experience (for example, the default feed is worse for me). Although some updates have been negative, I’m glad new things are at least being tried. I also exist in an area (AI, startups, tech, San Francisco, etc) which likely uses and enjoys Twitter more than average.
There are of course many alternatives to twitter, and if you prefer their leadership and product choices over the ability to actually have a large and influential audience, that is a choice one could make. As of 2024, Twitter remains largely influential to the world, and that’s why I continue to use it. You don’t have to be a fan of the CEO or ownership of a company to use a product from them, and Twitter is no exception.
Scott Alexander of SlateStarCodex / AstralCodexTen recently wrote Pascalian Medicine, in which he looks at various substances purported to improve covid outcomes, but which have relatively low amounts of evidence in their favor, likening administration of all of them to patients to a Pascal’s wager-type argument: if there is a small probability of a potential treatment helping with covid, and if it’s also very unlikely that this treatment is harmful, should we just give it to the patient regardless of if the quality of evidence is low and uncertain, as it would clearly have a positive expected outcome regardless?
The naive answer to this could simply be to attempt to calculate an expected value (note: I use the term expected value often here, but in some cases the terms hazard ratio, relative risk, or odds ratio would be more appropriate) for each treatment, and administer it if it’s positive. But there could be some unintended consequences of using this methodology over the entire set of potential treatments: we could end up suggesting treatments of 10 or 100+ pills for conditions, and apart from something just feeling off about this, it could magnify potential drug interactions, some treatments could oppose others directly, the financial cost could start to become prohibitive, and it could decrease patient confidence and have many other undesirable second-order effects.
Pascalian Longevity
There are many counter-arguments presented to the above concept which become less salient when the goal is changed from ‘find drug treatments to prescribe to all covid patients’ to ‘find personal health interventions that increase your own lifespan/longevity’.
I am fortunate enough that I am able to evaluate potential longevity interventions myself, pay for them myself, administer them myself, and review their potential effects on me myself. I might not do a perfect job of this – research is difficult, time-consuming, and lacking in rigor and quantity, and finding appropriate longevity biomarkers to quantitatively asses the effects of interventions is also difficult. But uncertainty is a given here, and that is why we incorporate it into our frameworks when deciding if something is worth doing or not by calculating an expected value. Furthermore, any harm that I may accidentally incur will only be done to myself, reducing the ethical qualms of this framework to near-zero (I would strongly oppose arguments that I should not have the right to take drugs which I think may significantly improve my own health, although some may disagree here).
My modus operandi with respect to longevity may have many uncertainties in its output, but still operates with a very strong (in my opinion) positive expected value: If a substance significantly and consistently increases the lifespan of organisms similar to humans (ideally in humans), and is also very safe in humans, then it is something that I want to take
This is how I operate personally with longevity, and it does result in me taking quite a few things (currently I’m at around 15). I do still try to minimize what I take as a meta-principle (for example, setting a minimum threshold of expected value that a substance must provide to warrant inclusion, rather than simply accepting any positive expected value) for a few reasons: firstly, to reduce potential drug interactions (which we do attempt to asses on a per-substance basis, rather than account for as an unknown, but unknowns are unfortunately a very large component of messing with biology regardless). Secondly, to keep my costs relatively sane, although I am not too worried about this as there are few ways to spend money more effectively than on trying to improve your health. Thirdly, to reduce the occurrence of interventions that may have the same or opposing mechanisms of action (taking two things with the same mechanism of action may be okay, but sometimes dose-response curves are less favorable, and taking >~2x of something will result in diminished or even negative returns). Lastly, to minimize potential secondary side-effects that could be cumulative over large classes of substances (for example, effects on the liver).
I don’t intend to promote any specific substances or interventions here as I don’t give medical advice, nor do I want anything specific to be the focus of this post, but I do want to remind us that just as we can calculate expected values in a utilitarian fashion and get effective altruism as a result, we can do the same for longevity interventions and get a very strong chance at notably increasing our lifespan/healthspan as a result. I do have a list of some of what I take here, but it is definitely not intended to promote anything specific to others.
Why Not?: Potential counter-arguments
Algernon’s Law
Algernon’s Law is sometimes brought up, suggesting that evolution has already put a lot of effort into optimizing our body, and thus we are unlikely to find improvements easily. But, as Gwern notes in the above link, there’s at least three potential ways around this reasoning: interventions may be complex (and/or too far away in the evolutionary plane) and could not have easily been found, they may be minor or only work in some individuals, or they may have a large trade-off involved and cause harm to reproductive fitness.
Although some areas of future longevity treatments may fall under exception one and be complex enough that evolution could not have found them, I would suggest that the majority of today’s potential treatments fall under exception three: evolution optimizes for reproductive fitness, not for longevity, and for this reason there are many interventions which will improve our longevity that it has not given to us already (this is part of why I am more optimistic about longevity interventions than I am about intelligence interventions/nootropics).
For an extreme example of this, it has been noted that castrated males often live longer, and that this is obviously something evolution would not be very interested in exploring. Although this has been found with median lifespan in male mice (maybe in females too?), there is also purported historical data on Korean eunuchs suggesting that they may have lived a full 14-19 years longer (there are definitely potential confounding variables and/or bad data here, but we don’t have RCTs on this in humans for obvious reasons..), and a more recent study in sheep that is also highly relevant: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, where epigenetic aging clocks that look at DNA methylation are used in castrated sheep. There are other traits that seem to improve longevity as well, for example decreased height. It seems quite plausible that there are a lot of trade-offs that optimize for strong reproductive fitness early in the lifespan of organisms, which end up costing the organism dearly in terms of longevity. These trade-offs may be involved in many areas such as testosterone, estrogen, growth hormone, IGF-1, caloric restriction, mtor activation, and many others.
Large error in estimating unknown risks
One other counter-argument here is often along the lines of “you are messing with things you don’t understand, and you could be hurting yourself but be unaware of this; the damage may also be difficult to notice, or perhaps only become noticeable at a much later time”
It is true that our understanding of biology is lacking, and therefore also that we are operating in highly uncertain environments. I would be open to evidence that suggests reasoning for why we may be systemically underestimating the unknown risks of longevity interventions, but given how strong the potential upside is, these would have to be some pretty terrible mistakes that are being made. It is often noted how curing cancer may only extend human lifespan by a few years, whereas a longevity improvement of 5% for everyone would provide much more value (and is also much easier to find in my opinion). One could make an argument here that even if I was doing something that notably increased my risk of e.g. cancer, if the expected lifespan increase of this intervention was as much as 1-5%, this could still be a huge net positive for my health! I don’t take approaches that are this extreme regardless, and I try to keep the risk side of my risk/reward ratio low independently of the level of potential reward in attempt to account for this uncertainty. I am also not aware of many interventions that seem to have very high numbers in both the numerator and denominator here, although I am pretty certain that they do exist; I don’t currently take anything that I think has notably detrimental side-effects for the time being.
Is it fair to call this approach Pascallian?
The original nature of Pascal’s wager is that of extreme probabilities resulting in positive expected values, but the numbers that we are operating with are nowhere near as extreme as they could be. It is probably not a good idea to take 10,000 supplements, each of which have a 0.1% chance of extending your lifespan by a year for many reasons (similarly, if 10,000 people that claimed to be God all offered me immortality for a small fee, I would hope to decline all of their offers unless sufficient evidence was provided by one).
As I’m not arguing in favor of taking hundreds or thousands of supplements in the hopes that I strike gold with a few of them, it may be worth noting that ‘Pascallian Longevity’ would be a poor label for my strategy. Regardless, taking just 5-10 longevity interventions with a strong upside potential seems to be significantly more than almost everyone is doing already, so I still stand by my claim that there are many free lunches (free banquets, if you ask me) in this area, and I am very optimistic about the types of longevity interventions we’ll find in the coming decades.
17α-estradiol is a relatively (or completely) non-feminizing form of estradiol (E2), or estrogen. It is a naturally occurring enantiomer of 17β-estradiol (the much more common form of estradiol, usually just referred to as ‘estradiol’) which is found in both male and female humans. This post a a brief essay that discusses the prospect of it extending lifespan in humans. There are two primary types of estrogen receptors, ERα and Erβ, and as you may expect, 17α-estradiol appears to show a stronger binding affinity for ERα. It has a very low binding affinity in locations that generally induce feminization (which appear to be sometimes be both ERα and ERβ), so it’s also possible to take as a male without significantly altering one’s appearance towards the opposite gender. Although we can definitively point to a plethora of effects of regular estrogen, it is difficult to tell what the true purpose of 17α-estradiol is in humans, with Stout et al. (2016) stating “the physiological functions of endogenous 17α-E2 are unclear”. There is evidence it has neuroprotective properties, can help treat Parkinson’s disease, cerebrovascular disease, and much more. This likely involves ER-X, which in turn activates MAPK/ERK and many, many other things down the line (as usual..), but it’s difficult to know for certain. Although these reasons were among the reasons that researchers took into account when deciding to dedicate funding to testing 17α-estradiol in mice for longevity effects, subsequent papers have found more exciting mechanisms of action which are elaborated upon below. For some interesting further reading on this topic that goes into more detail exploring possible mechanisms of action here I’d also suggest reading the following papers: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, Hypermethylation of estrogen receptor-alpha gene in atheromatosis patients and its correlation with homocysteine.
17α-estradiol has been found to consistently and significantly extend the median lifespan of male mice, including by the NIH’s Intervention Testing Program, the closest thing we have to a gold standard of longevity RCT experimentation in mice, where three studies are rigorously performed at three separate locations, allowing the results to be instantly compared and reproduced by the two other parties and locations upon completion. Strong et al. (2016) find that 17α-estradiol extends median lifespan of male mice by an average of 19% (26%, 23%, and 9% from the three independent testing sites), and increased the maximum age by an average of 12% (21%, 8%, and 8% from the three testing sites, using the 90th percentile). Harrison et al. (2014) similarly find that median male lifespan was increased by 12%, but did not find an increase in maximum lifespan, and these results have been replicated even more in recent years.
These are some impressive results for such a common and simple endogenous substance! One of the first things we notice is that this effect only applies to males, with female lifespan (both median and maximum) being unaffected. As the substance in question is an estrogen, we can assume that this is either due to female mice already having this benefit, as they already have a sufficient level of it, or that something more complex is at play, and there is a different downstream pathway that is only being activated in males for some reason (more on this later). I had initially assumed the former hypothesis was at least a partial explanation, having known that females consistently live longer than males when it comes to humans, and that this was obviously biological in nature. However, it’s much more complicated in mice as females do not always outlive males, and in fact many times the opposite is true. One meta-analysis (good overview, original book source) finds 65 studies where males lived longer and 51 where females lived longer, with this often depending on the strain of mice used, which varies greatly depending on the type of reseasrch and time period. Regardless, it’s clear there is much more at play in this scenario, and perhaps something special about 17α-estradiol in particular.
Although the ITP studies initially included 17α-estradiol due to the reasons mentioned in the first paragraph, later research such as Stout et al. (2016) has now found that 17α-estradiol not only increased AMPK levels (as some other notable longevity substances such as Metformin also do), but also reduced mTOR activity (complex 1!) in visceral adipose tissue, which is rather reminiscent of Rapamycin, which has extended the lifespan of every organism we have performed an RCT with thus far (and likely can in humans too, if you ask me). In a way, this is significantly more exciting, because it gives us a much more plausible way to explain the lifespan extension effects we are noticing. However, it is also partially a disappointment: if these effects are the real reasons why 17α-estradiol extends male mice lifespan, then this substance may offer us nothing that we do not already have via rapamycin and metformin, among others. The paper also noted that fasting glucose, insulin, and glycosylated hemoglobin were reduced along with inflammatory markers improving. These are similar to the types of positive side effects we would expect from a longevity agent, and the study also notes that no feminization nor cardiac dysfunction occurred.
How do these effects (such as AMPK and mTOR modulation) occur? I don’t know, and apparently neither does anyone else. As is often the unfortunate case in biology, the paper has this to say: “The signaling mechanism(s) by which 17α-E2 elicits downstream effects remains elusive despite having been investigated for several decades”. Perhaps just a few more decades to go and this section will be updated with more information, then. Mann et al (2020) find that male mice without ERα do not benefit from 17α-estradiol, which helps us narrow down the first step by excluding Erβ, ER-X and other less-predictable initial mechanisms. Interestingly, they also note that “both 17α-estradiol and 17β-estradiol elicit similar genomic binding and transcriptional activation of ERα”, which would leave us with the question of why we are focusing on 17α-estradiol specifically, if 17β-estradiol (which is much more common) suffices as well. Importantly, they also seem to think changes in the liver might be involved. Garratt et al. (2018) add that distinct sex-specific changes in the metabolomic profile of the liver and plasma were found, and also notes that the longevity benefit for males disappears post-castration. They first supplement males and females, showing many differences related to metabolism including with amino acids. Then they use castrated males and notice that their profiles are the same as the control group, and thus conclude that they are no longer being positively affected by 17α-estradiol. I am unsure if we should be focusing on the AMKP/mTOR effects (which arevery relevant to longevity) or on the liver/metabolic effects (which are also very relevant), or if these are in fact just two different temporal points on the same biological pathway which we don’t yet fully understand, but this helps us connect at least a few more dots.
All of the above sounds exciting, but it’s also all in mice. Sometimes this is useful, as mice are actually quite similar to humans (more so than many may expect), but a lot of it is also less useful or outright misleading. I cannot find a way to take only 17α-estradiol in a safe way as a human, however there is a topical cream of it (alfatradiol) which is used to treat pattern hair loss.
Luckily, one thing that the ITP study found was that 17α-estradiol was among one of the substances that seems to perform well with respect to longevity (if not fully) when given later in life (this has replicated afterwards as well), contrary to some others which have the best effect when started in youth and continued until death. In theory I wouldn’t mind waiting a decade or two until we have a better idea of what is going on here, after which point I would hope we have more fruitful and actionable results (especially in humans); although at the same time there’s likely many reasonable and safe ways we can go about achieving this (hopeful) effect in human males (assigned at birth) already, either via a type of estrogen or an estrogenic drug such as a SERM.
It is worth reminding ourselves that 17α-estradiol is already present in humans, and in both sexes, with women generally having significantly higher levels, as one expects of estrogen. Similarly, regular estrogen binds to both estrogen receptors, including our target, which we now know to be the alpha receptor. Given this, is it possible that just taking regular estradiol (for example, estradiol valerate, which for most purposes ends up biologically equivalent to endogenous estradiol and thus also binds to both primary estrogen receptors) to increase the levels of estrogen is a potential longevity intervention?
This is a difficult question to answer with the data currently available, although there are millions of persons assigned male at birth that are already on various forms of estradiol for various reasons, one of them being to assist in gender transition from male to female. As the lifespan benefit only applied to male (assigned at birth) mice, there would be benefits to analyzing these cohorts for more information, especially if we were able to have DNA methylation clocks used on these groups alongside a control (although this would not be a true RCT, as which persons decide to undergo feminizing HRT would not be random, I suspect we could still get the information we’d want with a good sample size).
There are other potential avenues of statistical analysis that could be attempted here, although they prove to be difficult for various reasons. Most male to female transgender individuals decide to transition earlier in their life, and this was also a particularly uncommon choice to make many decades ago in comparison to the present, so we have very few deaths due to age-related causes that we would be able to analyze to attain a proper hazard ratio. Even if we waited a long time for this (or had this data already), it would be terribly confounded due to the lack of randomization and many potential selection effects. Even so, one of the following must be true:
17α-estradiol does not extend male (assigned at birth) human lifespan
17α-estradiol does extend male (assigned at birth) human lifespan, however this does not apply to most/any transgender (m->f) individuals. This could be due to insufficient dosage, insufficient affinity for the alpha receptor, the inclusion of 17β-estradiol, the common addition of other substances such as anti-androgens, or another unknown factors/confounders
17α-estradiol does extend male (assigned at birth) human lifespan, and this effect therefore does apply to most transgender (m->f) individuals, however we have either failed to notice it completely, or other effects/confounding variables ablate this, for example an increased risk of blood clots from estrogen supplementation (which depends greatly on the route of administration as well as type of estrogen used) or various potential side-effects from anti-androgen usage
Option one is certainly a possibility, as it always is in longevity when all of our studies are only in mice. We could differ too much from mice for the mechanism of action to apply to us (perhaps if it is related to metabolism or some newer subset of liver functionality), or if the mechanism of action is indeed the AMPK/mTOR pathways, perhaps 17α-estradiol does not modulate these in humans as it does in mice. This could have implications for other potential longevity agents such as metformin and rapamycin in humans as well, which also heavily involve these pathways, which could cause these agents to interplay synergistically or perhaps cancel one another out, as there may be no further benefit that can be gained after one of these agents is already taken at the optimal dosage. It is worth noting that many aspects related to AMPK/mTOR and DNA methylation are heavily evolutionary conserved as well (mTOR quite strongly, which is another reason why rapamycin likely extends human lifespan). We also already know that human females have longer lifespans than males for biological reasons, and that there are quite a few reports that the lifespan of castrated males is significantly increased. If 17α-estradiol (or estradiol valerate perhaps) does not extend human male lifespan, I would have to believe there is some other similar route that likely does, and we just have to find the best way to go about pursuing it.
Option two is, in my opinion, moderately plausible. It could the case that when we do have groups that supplement estradiol, the dosage taken is nowhere near sufficient for a noticeable longevity improvement, and that if we would simply increase it by some factor, longevity benefits would become apparent. There does seem to be a dose-dependent relationship for the longevity benefits in mice, and it may be possible that estrogen receptor alpha simply isn’t being agonized nearly enough. This may depend on the type of estrogen and route of administration used, as well as other drugs that may be taken (for example, most male to female transgender individuals take an anti-androgen as well as an estrogen, and this could potentially ablate benefits). My personal conjecture would be that estrogen monotherapy via injections would have the best probability of a longevity benefit for those assigned male at birth, although modulating or combining this with SERMs may also be of interest, although much more experimental and difficult to get right (I may add more to this later as this is a pretty interesting avenue to me for multiple reasons).
As for option three, it may seem difficult at first glance to think that millions of male to female transgender individuals are all currently supplementing a substance that may increase their lifespan by 5-20%, but yet none of us (or them) have noticed this yet. However, there are no preventative reasons for why this couldn’t be the case, nor statistical evidence against this possibility. It could even be that suppressing testosterone and activating estrogen receptor alpha are additive in nature, and we end up with a particularly impressive lifespan extension effect from conventional feminizing HRT.
Although I obviously cannot be sure of any specifics, I do think there is likely some hormonal intervention that should significantly increase male (assigned at birth) human lifespan, but that we just may need another decade or two to get the optimal intervention figured out properly. It would be great to have substances like 17α-estradiol in human trials already, as the potential ROI for successful longevity interventions is massive both in terms of billions of additional QALYs and trillions of dollars saved in healthcare expenditure.
In conclusion, 17α-estradiol might notably extend human lifespan for those assigned male at birth. There are many potential mechanisms of action that could cause this, with the most interesting one perhaps being activation of the mTOR and AMPK pathways, resulting in more ‘feminine’ DNA methylation. This longevity benefit, if it exists, may apply to many male to female transgender individuals, or could also be weaker or stronger for various reasons, such as due to the common usage of anti-androgens. If this longevity benefit does not apply to these groups, there may be alternative hormonal interventions that work instead, such as supplementing 17α-estradiol directly, using a SERM with a strong binding affinity in the right areas, or other modifications to the HPG axis that reduce some potential negative longevity effects of testosterone.
Disclaimer: I’m a random person on the Internet and none of this is medical advice. I’d like to rewrite and expand on the potential mechanisms of actions in this post and talk a bit more about what I do myself in this area some time too. Feel free to mention any corrections or comments to me (see: About page).
This post is a summary of some of the things that I dislike about Mozilla and Firefox. Given how passionate I am about user rights, privacy, decentralization, FOSS, etc, sometimes these remarks surprise people. I still am grateful Mozilla exists, I still use some of their products, and there are many amazingly smart and good people there However, donations to Mozilla for the purpose of improving Firefox are ineffective and are better spent elsewhere, and I really wish they would stay focused on making better products.
Mozilla has a lot of money, most of which does not go towards Firefox
Mozilla constantly mentions that they are a nonprofit, encouraging you to donate to them to help Make The Internet A Better Place. While the Mozilla Foundation is legally classified as a nonprofit, their subsidiary, Mozilla Corporation, is not. Its revenue is around $450,000,000 per year, almost all of which comes from their contracts with Google (Yandex and Baidu as well). Google pays Mozilla half a billion dollars per year because Mozilla has contractually agreed to keep Google as their default search engine, and presumably this gives Google a net profit, as having more ad views and user information is very, very valuable (I heard an explanation that Google also wants to avoid antitrust issues, but I’m unsure of the veracity of that).
The CEO of Mozilla (both the foundation and the corporation), Mitchell Baker, had an annual income of over $3,000,000 (official source, cannot find 2020 document yet) or around $1,000/hour, which has managed to increase for several years in a row, despite metrics related to Mozilla’s primary product, their web browser, significantly decreasing (do note: her salary is technically from the for-profit, not the non-profit). In case you haven’t seen a report on browser market share in the last few years, Firefox currently has around 3-4% of the market share, with the highest estimates I can find being around 7-8%.
Yeah, it’s kinda bad
Most of Mozilla’s spending does not go to software development nor Firefox, but rather to administration, marketing, and similar expenses (this is true both for the non-profit and for-profit, but the non-profit’s information is publicly available). Checking their most recent form 990, there was $4.5M spent on grants to random universities and groups, $3M spent on management fees, $1.8M spent on travel fees, and $0.8M spent on conference fees, which combined is significantly more than what is spent on employee compensation. This means when you donate to Mozilla’s nonprofit, your money is more likely to be spent on universities, management, and travel than an employee’s compensation.
Although there are not many publicly available details about the specific spending of the for-profit section of Mozilla (which would be ~10x more), the distributions appear to be relateively similar from what sources I can find. One reason why Mozilla spends so much on marketing is because their products are generally not as good as their competitors’, and attempting to purchase your way to a larger userbase is an expensive and constant uphill battle.
Firefox does little to stop you from being tracked by Google
One of the most popular reasons to use Firefox instead of Chrome is a dislike for being tracked by Google. While it’s true that Google recieves more information from Chrome users than it does from Firefox users, the majority of information flow remains a constant, and Mozilla relies on a plethora of Google services for basic browser functionality. Here are some examples:
Firefox uses Google search by default and sends all queries/address bar typing to Google
Firefox uses Google’s safe browsing service for ‘unrecognized downloads’, sending Google the filename and url that you visited
Firefox uses Google services for basic APIs such as their location API, despite Mozilla having attempted its own implementation, which one may assume they’d use. As Firefox polls your OS for information to send to this API, this sends information such as your wifi-network or nearby phone towers in addition to your IP address and a biweekly-rotating Google client identifier.
Apart from Firefox relying heavily on Google’s services, unless you use extensive tracking/blocking addons, you’re being tracked everywhere you go to begin with, as the majority of websites use Google Analytics, Google APIs, Google fonts, Google ReCAPTCHA, among many others.
There is truth to Mozilla working on and implementing important privacy improvements in browsers, such as DNS over HTTPS, third party cookie blocking by default, tracker blocking, and so on. Some of these appear to be helpful, however are easily mitigated by other parties, while others are more questionable (for example, the implemention method of rolling out DoH by opting users into it, bypassing their network configuration preferences, and sending all DNS queries to a single company’s servers, was not optimal). As of firefox 86 on Feb 23rd 2021, Firefox appears to be attempting full per-site cookie isolation, which if successful and usable could be a great improvement here.
Firefox includes tracking, advertisements, and backdoors
Mozilla takes almost every chance it can to tell you how much they love your privacy, and for that reason the tracking and default features that are included in distributions of Firefox are pretty surprising (this does not mean Firefox is worse at this than other browsers!).
– the number of open tabs and windows, the number of websites visited, the number and type of addons installed, the length of your browser session, all interaction events with ‘Firefox features offered by Mozilla or our partners’, your device information, OS information, hardware information, and your IP address
“Firefox uses your IP address to suggest relevant content based on your country and state”
“When you choose to click on a Snippet link, we may receive data about the link you followed”
“Firefox sends basic information about unrecognized downloads to Google’s SafeBrowsing Service, including the filename and the URL it was downloaded from”
Some of this information is reasonable, such as crash reports and the base OS/Firefox version, but I still found this to be more than many may expect.
Firefox now comes with a feature called studies, which allows Mozilla to remotely install and run custom changes and featuresets to your browser without asking you. This is turned on by default, which is generally all that matters as almost no users go through every setting in software to turn things off manually. In the past Mozilla used their ability to remotely control browser installations to install an addon into users’ browsers that gave them cryptic messages which were intended to be advertising for a TV show. I don’t know why they thought that was a good idea, as it seemed to be almost unanimously agreed upon that it was a terrible idea, but it still happened. If you visit about:studies in Firefox you can see which studies you have/are currently participating in. I could not find any resource from Mozilla that lists all studies that they run, or anything remotely like this.
Firefox continually pushes sponsored and clickbait content into their products
Firefox comes with many features for sponsored content and advertisements, such as Sponsored Top Sites. The Mozilla page about this feature says they send ‘anonymized technical data’, which is hyperlinked to a near-empty Github repositry. Firefox partners with adMarketplace for this, which states “We may also receive technical information such as your approximate location, browser type, language settings, user agent, timestamp, cookie ID and IP addresses”, which is very dissimilar to what Mozilla says about this tracking, but perhaps they have a special agreement with Mozilla to opt their users out of this or something.
There is also Pocket, which comes with all distributions of Firefox and shows sponsored stories and other content ‘curated by our editors’ by default. I’m not even going to pretend this is decent. This is is a terible feature, and the last thing I want to see when I open my web browser is a bunch of advertisements for clickbait. I find it sad that mozilla says Pocket “Trades clickbait for quality content”, when the majority of content Pocket offers is complete trash designed to make you click and waste your time, including a lot of content that suggests that surveillance and censorship of the Internet is required to keep me informed and safe.
Please keep your clickbait out of my browser’s default home page, thank you
Fortunately several of the worst features of Firefox are easy to turn off, and some features that are even worse such as Ion, which literally just sends your browsing history to ‘researchers’, are disabled by default and must be opted into. I’m unsure why these features are included in Firefox to begin with, as I can’t imagine the small revenue stream they introduce is significant nor in Mozilla’s best interest.
Firefox is generally a slower browser than Chrome
If you’re a Firefox user, I suggested using Chromium just for a few minutes. I usually use forks of Firefox or Firefox ESR, but when I use Chromium I’m sometimes stunned at how much faster it is. Finding fair and recent browser benchmarks is difficult, but but most of which I’m able to find seem to confirm this, and testing local website rendering myself results in Chrome not just being slightly faster, but often 50-300% faster with its rendering, network requests, and javascript execution.
Using Chrome for a few minutes instantly allows me to understand why it has dominated Firefox in market share over the last decade. While it’s true that Google has many inherent advantages in promoting software, I think its performance, speed, and UX alone goes a long way in demonstrating why Firefox has fallen behind so far.
Mozilla has strange and contradictory ideological goals
When visiting the homepage mozilla.org, the first article that is shown to me is titled ‘We need more than deplatforming’ written by the CEO Mozilla, which implores us to do things like “Turn on by default the tools to amplify factual voices over disinformation”, kindly linking us to a NYT article that discusses how ‘authoritative sources’ such as the NYT and CNN should be prioritized over independent voices.
Continuing to read blogposts from Mozilla (this is from their foundation’s website, I should add that they have some good technical blogposts in other locations) is a rather interesting endeavor as it becomes more and more apparent that Mozilla has large segments of their organization that don’t seem to have any clear goals, and just kind of write about random social and political things on the Internet and their opinions on it, sometimes throwing six-figure grants to random groups of students to make a game that no one ever plays to show us about how something is obviously bad, which I assume they thought was a better use of their money than hiring someone to work on Firefox (which 250 people were laid off from last year).
While Mozilla attempts to provide commentary on many important social issues, there appear to be many suggestions that go directly against their manifesto, which suggests that open expression and individuals freedoms should be prioritized. I respect the right for Mozilla to spend its funding on any social or political content it chooses, and I also think that many of the issues they dedicate time to are very important for our society and for the Internet, but I would rather their organization focuses on making a good web browser, because I would be much more excited about donating to them if my money went towards that.
I’m still glad Firefox exists
I’ve written some negative views about Firefox, but I’m still glad it exists. Making a perfect web browser is difficult, and trying to respect user privacy is difficult. I think Mozilla would be much better off if they were a product-focused company, and spent more money on technical innovation and additional engineers and innovators. For this reason I don’t think donating to Mozilla is a good choice, and as far as similar organizations go, prefer the EFF instead.
This article started to turn into a bit of a rant as I’ve continually found myself disappointed with decisions Mozilla has made, and I’m not surprised that their browser market share has decreased by almost 90% over time as a result. It’s easy to criticize, but difficult to build, so I do want to include this disclaimer to restate that I’m glad Firefox and Mozilla exist, and I wish the best for them and their browser, but I think their modern directions are distracting them from making products good enough to be widely used. I hope things improve, because it would be nice if more than one or two web browsers existed. In fact, I think that’s very important.
The Everything Store – Jeff Bezos and the Age of Amazon by Brad Stone is a book detailing some factors that led to the rise of Amazon as one of the largest corporate success stories of all time. I opened it expecting to skim through some parts, but ended up reading it in full in one sitting, and enjoyed it thoroughly. It left me with a strong sense of what makes Amazon, well, Amazon. And the best answer to that question is without a doubt, Bezos himself.
Rather than a full book review, I’m going to share some quotes from The Everything Store that stood out to me. One fun thing to note is that when this book was published in 2013, Amazon was ‘only’ a $150B company, but today is worth over 1.5 trillion. It’s a wonderful book and is worth buying if you want to read stories about Jeff Bezos’ extreme confidence in himself and his company as they overcome challenges one after another full-speed ahead, from local stores to Barnes and Noble to Ebay to Walmart and beyond. Below are some quotes that I particularly liked, only from the first fourth of the book. I was quoting the book more than anticipated, so I stopped this post early but will leave it up as an advertisement for the book.
Bezos is an excruciatingly prudent communicator for his own company. He is sphinxlike with details of his plans, keeping thoughts and intentions private, and he’s an enigma in the Seattle business community and in the broader technology industry. He rarely speaks at conferences and gives media interviews infrequently.
There is so much stuff that has yet to be invented. There’s so much new that’s going to happen. People don’t have any idea yet how impactful the Internet is going to be and that this is still Day 1 in such a big way. Jeff Bezos
Amazon’s internal customs are deeply idiosyncratic. PowerPoint decks or slide presentations are never used in meetings. Instead, employees are required to write six-page narratives laying out their points in prose, because Bezos believes doing so fosters critical thinking. For each new product, they craft their documents in the style of a press release. The goal is to frame a proposed initiative in the way a customer might hear about it for the first time. Each meeting begins with everyone silently reading the document, and discussion commences afterward
“If you want to get to the truth about what makes us different, it’s this,” Bezos says, veering into a familiar Jeffism: “We are genuinely customer- centric, we are genuinely long-term oriented and we genuinely like to invent. Most companies are not those things. They are focused on the competitor, rather than the customer. They want to work on things that will pay dividends in two or three years, and if they don’t work in two or three years they will move on to something else. And they prefer to be close-followers rather than inventors, because it’s safer. So if you want to capture the truth about Amazon, that is why we are different. Very few companies have all of those three elements.”
Bezos interpolated from this that Web activity overall had gone up that year by a factor of roughly 2,300—a 230,000 percent increase. “Things just don’t grow that fast,” Bezos later said. “It’s highly unusual, and that started me thinking, What kind of business plan might make sense in the context of that growth?”
Jackie Bezos suggested to her son that he run his new company at night or on the weekends. “No, things are changing fast,” Bezos told her. “I need to move quickly.”
Internet records show that during that time, they registered the Web domains Awake.com, Browse.com, and Bookmall.com. Bezos also briefly considered Aard.com, from a Dutch word, as a way to stake a claim at the top of most listings of websites, which at the time were arranged alphabetically.
Bezos and his wife grew fond of another possibility: Relentless.com. Friends suggested that it sounded a bit sinister. But something about it must have captivated Bezos: he registered the URL in September 1994, and he kept it. Type Relentless.com into the Web today and it takes you to Amazon.
They set up shop in the converted garage of Bezos’s house, an enclosed space without insulation and with a large, black potbellied stove at its center. Bezos built the first two desks out of sixty-dollar blond-wood doors from Home Depot, an endeavor that later carried almost biblical significance at Amazon, like Noah building the ark.
During that time, the name Cadabra lived on, serving as a temporary placeholder. But in late October of 1994, Bezos pored through the A section of the dictionary and had an epiphany when he reached the word Amazon. Earth’s largest river; Earth’s largest bookstore.3 He walked into the garage one morning and informed his colleagues of the company’s new name. He gave the impression that he didn’t care to hear anyone’s opinion on it, and he registered the new URL on November 1, 1994. “This is not only the largest river in the world, it’s many times larger than the next biggest river. It blows all other rivers away,” Bezos said.
One early challenge was that the book distributors required retailers to order ten books at a time. Amazon didn’t yet have that kind of sales volume, and Bezos later enjoyed telling the story of how he got around it. “We found a loophole,” he said. “Their systems were programmed in such a way that you didn’t have to receive ten books, you only had to order ten books. So we found an obscure book about lichens that they had in their system but was out of stock. We began ordering the one book we wanted and nine copies of the lichen book. They would ship out the book we needed and a note that said, ‘Sorry, but we’re out of the lichen book.’
A week after the launch, Jerry Yang and David Filo, Stanford graduate students, wrote them an e-mail and asked if they would like to be featured on a site called Yahoo that listed cool things on the Web. At that time, Yahoo was one of the most highly trafficked sites on the Web and the default home page for many of the Internet’s earliest users.
In the meetings, Bezos presented what was, at best, an ambiguous picture of Amazon’s future. At the time, it had about $139,000 in assets, $69,000 of which was in cash. The company had lost $52,000 in 1994 and was on track to lose another $300,000 that year. Against that meager start, Bezos would tell investors he projected $74 million in sales by 2000 if things went moderately well, and $114 million in sales if they went much better than expected. (Actual net sales in 2000: $1.64 billion.)
Bezos later told the online journal of the Wharton School, “We got the normal comments from well-meaning people who basically didn’t believe the business plan; they just didn’t think it would work.”11 Among the concerns was this prediction: “If you’re successful, you’re going to need a warehouse the size of the Library of Congress,” one investor told him.
When his goals did slip out, they were improbably grandiose. Though the startup’s focus was clearly on books, Davis recalls Bezos saying he wanted to build “the next Sears,” a lasting company that was a major force in retail. Lovejoy, a kayaking enthusiast, remembers Bezos telling him that he envisioned a day when the site would sell not only books about kayaks but kayaks themselves, subscriptions to kayaking magazines, and reservations for kayaking trips—everything related to the sport. “I thought he was a little bit crazy,” says Lovejoy.
The IPO process was painful in another way: During the seven-week SEC-mandated “quiet period,” Bezos was not permitted to talk to the press. “I can’t believe we have to delay our business by seven years,” he complained, equating weeks to years because he believed that the Internet was evolving at such an accelerated rate. Staying out of the press soon became even more difficult. Three days before Amazon’s IPO, Barnes & Noble filed a lawsuit against Amazon in federal court alleging that Amazon was falsely advertising itself to be the Earth’s Largest Bookstore. Riggio was appropriately worried about Amazon, but with the lawsuit he ended up giving his smaller competitor more attention. Later that month, the Riggios unveiled their own website, and many seemed ready to see Amazon crushed. The CEO of Forrester Research, a widely followed technology research firm, issued a report in which he called the company “Amazon.Toast.”
It was a distilled version of the dissatisfaction felt by many early Amazon employees. With his convincing gospel, Bezos had persuaded them all to have faith, and they were richly rewarded as a result. Then the steely-eyed founder replaced them with a new and more experienced group of believers. Watching the company move on without them gave these employees a gnawing sensation, as if their child had left home and moved in with another family. But in the end, as Bezos made abundantly clear to Shel Kaphan,family. But in the end, as Bezos made abundantly clear to Shel Kaphan, Amazon had only one true parent.
“You seem like a really nice guy, so don’t take this the wrong way, but you really need to sell to Barnes and Noble and get out now,” one student bluntly informed Bezos. Brian Birtwistle, a student in the class, recalls that Bezos was humble and circumspect. “You may be right,” Amazon’s founder told the students. “But I think you might be underestimating the degree to which established brick-and-mortar business, or any company that might be used to doing things a certain way, will find it hard to be nimble or to focus attention on a new channel. I guess we’ll see.”
“There will be a proliferation of companies in this space and most will die. There will be only a few enduring brands, and we will be one of them.”
During that time, no one placed bigger, bolder bets on the Internet than Jeff Bezos. Bezos believed more than anyone that the Web would change the landscape for companies and customers, so he sprinted ahead without the least hesitation. “I think our company is undervalued” became another oft- repeated Jeffism. “The world just doesn’t understand what Amazon is going to be.”
As the company grew, Bezos offered another sign that his ambitions were larger than anyone had suspected. He started hiring more Walmart executives.
Around that time, Wright showed Bezos the blueprints for a new warehouse in Fernley, Nevada, thirty miles east of Reno. The founder’s eyes lit up. “This is beautiful, Jimmy,” Bezos said. Wright asked who he needed to show the plans to and what kind of return on investment he would have to demonstrate. “Don’t worry about that,” Bezos said. “Just get it built.” “Don’t I have to get approval to do this?” Wright asked. “You just did,” Bezos said. Over the next year, Wright went on a wild $300 million spending spree.
“Walmart did not even have Internet in the building back then,” says Kerry Morris, a product buyer who moved from Walmart to Amazon. “We weren’t online. We weren’t e-mailing. None of us even knew what he meant by online retail.”
The venture capitalists backing eBay asked around and heard that one did not work with Jeff Bezos; one worked for him.
Bezos went skiing in Aspen that winter with Cook and Doerr and finally told them what was coming. “He said, ‘We’re going to win, so you probably want to consider whether to stay on the eBay board,’ ” says Cook. “He thought it would be the only natural outcome.”
If you liked these quotes, consider reading the full copy (perhaps even buying it from Amazon), it’s definitely a nice read about an amazing company and individual.
Midday on July 15th, 2020, many high-profile Twitter accounts were compromised and began posting scams to entice users into sending them cryptocurrency (generally BTC, but also some others such as XRP for Ripple’s account). I’m not going to write about this in detail since everyone else already has, but for more information check out an article on the topic: Coindesk, TheVerge, TechCrunch, BBC, infinite others
What if instead of posting low-quality cryptocurrency scams, the attackers did something else?
Sure, they could have tried to use CEO accounts such as Musk and Bezos to make millions (or possibly billions) on the stock market by tweeting about earnings and purchasing large amounts of far-out-of-the-money near-expiration call options on the underlying stocks. But we have a lot of ways to catch people that try that, and many regulations and organizations that would make it more difficult (many more than just the SEC) to get away with (although as a side note, $TLSA’s stock+option trading volume is absurdly high, and it would be very difficult).
But, what if they had tried something else entirely, something not motivated by short-term financial gain?
What if the attackers wanted to cause chaos and violence, perhaps alongside putting certain political movements and goals forward? What if they had pre-written thousands of tweets about a topic, perhaps a fake and outrageous event occurring, paired with fake images and videos, perhaps even some higher-quality deepfakes? How many people could they get killed? Could they start a war?
You might think this sounds absurd at first glance. But remember, most of the world’s most influential people use Twitter, including the leaders of most national governments. Although a private corporation that plays by its own rules, Twitter is still the means with which many elected officials communicate with the public. Entire social movements have started and ended through the power of a single viral tweet, sometimes resulting in significant violence or many deaths. Social media platforms have been used by extremists of every type imaginable in the past, and this isn’t going to stop any time soon.
What if the next exploit affects much more than some Twitter accounts?
But, I want to go much further than talking about Twitter. What if instead of an exploit that allowed attackers to compromise Twitter accounts, it had been something much worse? What if they were able to compromise any web server, or any online Windows machine, or industrial control systems for utilities, power plants and military operations? None of these scenarios are by any means impossible. Enough software and hardware exists at enough layers of abstraction that there’s generally always 0-days lurking in critical systems, sometimes for years or decades, before they’re found. We know that 0days are found often by securityresearchers, private companies, governments, and others (sometimes rewarding up to $2,500,000), but also that they are less commonly exploited in obnoxious and harmful ways (generally being hoarded by government security agencies or reported in good faith).
We were unprepared for covid despite epidemics throughout all of history
It was said by many that the covid pandemic could have been predicted, in a sense (which is why it was not a true black swan event). Perhaps not the specifics of it such as the date, virus, and origin. But the general idea of “at some point in the future, something bad is going to happen like this, and we need to prepare for it.”
Another one of these “something really bad is going to happen in the future” categories involves cybersecurity, data privacy, and AI. Just one of these topics individually can be involved in a terrible catastrophe, and indeed have been before, but I think we’re coming close to a combination of all three that can lead to events much worse than we’re currently prepared for.
Security: Billions of humans live digital lives, including the most influential, famous, and dangerous. These people all have email accounts, phones, Twitter accounts, and more, all of which can be compromised, controlled, and manipulated by others.
Data Privacy: The amount of data that social media giants (among others) have on most people is massive, and in my opinion vastly underestimated both in quantity and power. The majority of human communication is now owned by private companies that store things forever. A large proportion of all human social connections, conversions, movements, opinions, and thoughts are stored in databases that not only will not forget, but that the user does not have any control or often even knowledge of.
AI: Advances in the area of content generation have been happening very quickly in the last few years. We now have GPT-3, which can write plenty ofthingsbetter than humans can. We have deepfakes, which can produce believable fake images and videos. We can do the same for voices and much more. Much of this isn’t yet perfect, but it’s clear that we’re improving quickly.
So, take the three above topics of security, data privacy, and AI, and combine them all. Bonus points if you throw in some political tension, which we’re certainly not lacking right now either.
We are not prepared for a true disaster involving technology
As a society, we’re woefully under-prepared for disasters in all of these areas.
We’re not prepared for critical infrastructure, both physical and digital, to be compromised or attacked by highly-funded and competent groups, maybe even state-ran.
Not prepared for the massive campaigns of disinformation, fake news, and propaganda that lie ahead. If you thought things were bad in the last few years, just wait, because we’re on the verge of accelerating it by 10x, and fact-checking is not a solution. China’s government seems to be working very hard both on the offensive and defensive here. Is anyone else truly competing?
Not prepared for how to deal with database leaks that will contain the life history of millions of people, including their ‘private’ conversations and deepest secrets, and items so egregious that they instantly spark violence. Plenty of data breaches have led to murders and suicides already. There are still many countries where you can face imprisonment or death for being gay, being atheist, being of a certain ethnicity, or speaking outagainst thegovernment (yes, we really don’t have it as bad here, huh!). Do you know what happens when these people have their private information carelessly leaked? It’s not pretty. And this is just for normal database leaks, let alone if a database leak had some information in it falsified (with the majority left intact, thus offering plausibility for the fake parts) to maximize its effect.
Not prepared for how to face that humanity is becoming increasingly controlled by viral algorithms that do not prioritize human values of happiness and love and truth, but rather nothing but outrage and in-group bias as the only bottom line. Most of us already feel powerless against this, but it may only just be beginning.
Not prepared for how anonymity is becoming a luxury only achievable by ultra-competent tech gurus, with most people having been forced to move their communication into more and more centralized ways over time, feeding all of the above issues. Not prepared for how one of the many reasons anonymity is getting much more difficult to obtain is because the easiest way to tell if someone is a bot or a human is to require verification of phone numbers, addresses, and more. And don’t let me forget to mention how many governments are eyeing up ways to ban end-to-end encryption.
I’m supposed to end on an optimistic note
How can we do a better job of addressing these problems?
Promote education on the importance of cybersecurity, especially at the government and corporate levels
Promote decentralized solutions instead of centralized social media platforms, allowing users to have control over their discourse, their platform, and their own data
Promote anonymity, even when it is difficult, and fight to ensure end-to-end encryption is a right for everyone forever
Promote better regulations around privacy and data security so that hoarding large amounts of personal data is less of an asset and more of a liability
Although a lot of this post might read as alarmist and pessimistic, I’m still (mostly) optimistic about these things in the long-long-term. The best part about terrible events like covid is that they make us stronger and better prepared for the next (similar) storm to hit us. Security used to be a second thought (or not a thought at all) for most companies, but we’ve improved significant in the last decade, and bug bounty programs and significant security spending are now common. I used to get looked at like I was insane for talking about how big of an issue the amount of tracking and data-collecting our society performs was a big problem, but even this is something that a lot of everyday people believe now as well. I just hope the stepping stones along the way to becoming prepared for the future aren’t so terrible that we don’t make it there in one piece.
