One of the most thoughtful pieces I’ve read about looking forward and the changes coming from AI. Treybig doesn’t focus on societal changes, but changes to the production of software systems themselves. Programming languages, development frameworks, and libraries are tools built to make it easier for humans to read and write code. Soon we’ll start seeing new ideas popping up here to make it easier for LLMs to read and write code, too.
An interesting observation of cultural differences, looking at AI generated selfies to explain how nuance and slight variation get papered over by ML models. Training datasets make a huge difference in the output we see. A different flavor of the world globalizing and flattening, and the loss from that process.
Exploring different UX ideas for how to improve calendars. I hate both Google and Apple calendar, and would love to try something like this out.
Automation, and thinking of LLMs as an army of interns who can perform most tasks reasonably with some supervision. Evans drives us towards Jevons’ Paradox, pointing that the falling cost of getting some things done with LLMs actually increases demand for those things, increasing, rather than reducing our use of them. From coal, to oil, Xerox machines, and typewriters… why is this time different?
On data engineering, redundancy, and “looking for hundreds of needles in a haystack approximately the size of Mars.” Reminds me of my Apple days, and the challenges of working in insanely large scale systems. Turquoise is working on some cool stuff.
A 14 line python script with 0 parameters that can outperform a bunch of the deep transformer-based LLM models everyone is so crazy about.
Most companies fail because they don’t solve actual problems. This is a good problem sizing framework, based on his experience building WP Engine.
A visualization of hashing functions, what they are and what makes a good one. This would have been a great resource back when I was taking intro to programming classes.
Most LLM applications I’ve seen so far are still just demoware, things that look cool and shiny but don’t really work at scale. This piece is a few months old, and good chunks of it already feel outdated.
A post pointing out problems with one of the most popular frameworks in AI-land these days, and the perils of picking the wrong abstraction.
I’m bullish distributed-teams long term as companies grow, but early-on technical teams working on startups should be in one place, and that place should be San Francisco.
The set of topics that can be openly discussed online these days is shrinking. That is a problem. I couldn’t agree more with Albert’s position here: “we need to be willing to explore new and more fundamental solutions rather than trying to patch the existing systems. […] patching our Industrial Age systems won’t do.”
A fairly abstract essay about how our ability to build narratives breaks down when our lives revolve around an ever growing knowledge base. Its incompleteness implies deficiency in our understanding of the world. Narratives hide this lack, or at least allowed most of us to ignore the inadequacy until now. “Narratives seek closure (the story must end). The Database is open-ended (it assimilates new data indefinitely). The Database resists the Narrative impulse to control and stabilize meaning.”
An odd case of Balaji going Marxist. I can’t really reconcile the fact that I agree with the premise but disagree with the conclusion. If value comes from humans crystallizing our time into objects (very much in line with Marx), and technologies are tools to improve the rate at which we transform time into value, then it follows that all resources are ultimately denominated in time we spend creating them, and that more time means more value. If that’s the case, and time is the ultimate source of value, “creating more time,” or lengthening lives, is surely the ultimate purpose of technology… and yet, I don’t agree that the purpose of technology is immortality. In part, because I think the value of life comes from the fact that it’s finite, and that experiences are almost by definition not repeatable, special in their uniqueness. The logic is sound, but something is off.
I very much enjoyed this. Wenger “proposes a theory of history in which technology changes the binding constraint for humanity.” As foragers, we were constrained by access to food. With the rise of agriculture we were constrained by land, and as we shifted to the industrial age we were constrained by capital. Today, he proposes the binding constraint on humanity is attention. I’m not fully bought into this last claim, but I still haven’t read his book, and I’m sure he has good arguments for it. In this piece he builds on that idea, pointing out that the complexity of measuring the impact of our decisions increases over time, making our incentives murkier. As in, it’s easy to see how much food hunters bring back, or how much grain came out of this years harvest. In today’s world, it is much harder to measure the value created by physical capital - there’s whole disciplines on this kind of measurement and optimization. Network effects are deeply linked to this. One of the reasons measuring gets tougher is that, previously, the impact of any one decision was isolated. They mostly had local effects; today, they’re global. Obviously, uncertainty plays a role here too. Measuring the value of an evening hunt is easier than the value of a harvest, because there’s less uncertainty than in the yearly cycle of weather. Increased societal complexity means increased uncertainty. It’s all about attribution. I’m really excited to see him develop this idea further.
Not the most informative piece on O’Reilly’s views, but I read his WTF a couple of years ago and I think I agree with a lot of his points. This is more of a fluff piece on his new fund though. He argues that optimizing for shareholder-return is a decision, and that that decision leads to financial instrument that don’t really benefit society as a whole. Instead he suggests that companies should make decisions based on whatever their values are (ie, local manufacturing vs outsourcing, or support for employee benefits vs gig economy contractor model) and that the market still gets to allocate capital based on those ideas, moving the market away from being a weighing machine for financial returns, and instead a weighing machine for “value.”
I have pondered some of these questions up-close myself, and I don’t like where they lead if the metric that defines the decision (at least for our side) is short-term “shareholder-value.” This is especially important when we look at the other link on China shared above.
I ran a poll on Twitter that showed most people, at least in my circles, are members of many different Slack groups. It’s interesting to think of Slack not as a vertical company that is trying to lock-in enterprise customers one a time, but instead as one that brings multiple enterprises together in controlled environments.
On conflict as entertainment, and its evolution from bad TV to bad social media.
An oddly prescient text from Lanier. It predicted the rise of an entity that’d fill the hole of Facebook as the ultimate bottleneck for our attention online, the devolution of the media industry into either more extreme or more average versions of its old self, and the fact that Wikipedia would become a central asset in the battle to train artificial intelligence models.
An interesting analogy based on the idea that Zoom “feels 1.0.” It’s not new technology, it’s the one people use though. That makes it similar to Skype or Dropbox. Once video is ubiquitous, who will ask new interesting questions and build products around them? Probably not Zoom.
The internet went crazy in the past few days over what people were speculating to be a new gen-Z focused social network app. It hit #1 on Product Hunt using a wacky website with just a web-form. Turns out that it was not a tech thing at all, but instead a guerilla marketing campaign to push people to donate to civil rights! It was what it was.
Random cool thing of the day.
There is real value to pseudonimity, and Slate Star Codex is one of those treasured corners of the internet that wouldn’t exist without it. There are times when the value created for society by exposing personal information can eclipse personal losses. Not knowing the details behind how the NYT makes decisions about anonimity, nor what this story was actually supposed to be about in the first place, this doesn’t seem to be one of those times. The essay above clearly lays out a good set of reasons why Alexander should remain pseudonymous. Unsurprisingly, the author makes a good case for himself. I’m not more than an occasional SSC reader, but there’s been a lot of noise about this incident in my circles online recently, and it’s hard to see how the NYT could justify this. Now the onus is on the NYT to decide whether whatever story they were planning to write is actually worth publishing, outweighing the logic presented by Alexander and backed by a wide array of very-online-people.
In which Sinofsky, a long time Microsoft executive, explains what in his eyes is special about Apple in the context of the recent WWDC announcements.
An essay on similar ideas to Ben Thompson’s recent pieces on zero trust information but perhaps more grounded in theory. Towards the end, the author quotes Hayek, saying that “civilisation rests on the fact that we all benefit from knowledge which we do not possess.” Today, having the capacity to figure out which knowledge comes from a trustworthy source and which doesn’t is more important than ever.
I probably learned about the Cobb-Douglas model a couple of lectures into my economics degree. In one short essay, Stucchio explained more about why it matters than any of my micro professors did.
A bit of history. Now that we’re finally on macOS 11.0, let’s look at the operating system’s roots and heritage, to predict where it could be going.
A three part series, here’s two and three, touching on labor participation in the attention economy, and the potential redistribution/taxation schemes that could reorganize the economy.
An explorable on the mechanics of gears and how simple machines work.
The two most important questions raised by this deck are about decentralization. What happens when regulation is no longer local? What happens when there is no individual to answer to your regulation?
In which Elaine lifts the veil on the ulterior motives behind making the move to work from home permanent. There’s money to be saved.
Using a lego robot, and a camera to brute-force the iOS passcode blacklist. I never would have thought of attacking the problem this way!
This is one of the first infinite scrolling visualizations I’ve run into, although the genre has become more popular since. Worth checking out.
I’m used to seeing the yearly AVC round-ups, of what happened in the last twelve months. Taking the broader view of what are the trends from the last decade. In short Fred highlights: The emergence of the big four web/mobile monopolies, the massive capital flows into startups chasing the “capital as a moat” model, ML becoming table stakes, subscriptions becoming a viable business model via tech platforms, Silicon Valley’s position in tech/startups started weakening, crypto showed up, the effects of tech in society deepened, the rich got richer, and China emerged as a tech superpower and a global superpower. Don’t miss out on the predictions
In which Fred compares the change brought about by COVID to our urban centers to that of white flight in the 50s and 60s. “Will cities remain attractive for the quality of life they offer[…]? Or will the suburbs stand to gain? Or will more idyllic locations […] become the location of choice? Or will 2nd and 3rd tier cities become more attractive?” This thought is stuck in my head now.
An in-depth piece on tech and centralization. The Hamiltonian/Jeffersonian axis had been popping up in a lot of places, and reading pieces like this one, at the intersection of tech, economics, and history, is what ultimately made me want to learn more US history.
I’m a big fan of Albert’s idea of fully interoperable APIs as a way out of the curation/moderation/editorializing problems in social media. There’s something to it, I’m just not really sure how you build this out. Where’s the business model?
I read this, as well as Cory’s less formal blog post after his conversation on the YC Podcast. If there’s one thing I’m excited about of the new decentralized crypto-backed promise it is how many of these new interoperable services it will enable.
I don’t know how Maciej is always so persuasive. I’m afraid of the ratcheting once we’re past this, but this is gold. The data is already being collected, so why not use it to empower healthcare workers instead of selling skin cream?
After reading O’Reilly’s book, WTF, I am pretty sure that his argument is not “blitzscaling is good” nor “blitzscaling is bad” but instead “we shouldn’t aim to build this kind of company.” Growth for the sake of growth, and profits for the sake of shareholders are not tenets of capitalism set in stone. Leaders can decide to make their companies true to a mission, and true to a predefined set of values, and invest their resources accordingly.
Since we are now all running on the same operating systems with the same applications, there isn’t a two-tiered arrangement where the public and government officials are running different software. That means that the government slowly has to come to terms with the fact that we can’t have both security and backdoor surveillance. Schneier seems uncharacteristically optimistic about where the debate is moving.
The internet as a whole is built around a protocol where no one trusts each other by default. Instead of having a centralized system to tell us what is or is not worth trusting, there is a (mostly) decentralized system that allows each participant to verify the source of the data they’re receiving. This kind of decentralization means that good and bad things alike are out there, and no one can remove it at the source. Here, Thompson makes an analogy between misinformation on social media and packets being routed on the internet - it’s not just access to misinformation that has increased, but access to really high quality viewpoints, too. The verification is on us.
The rate at which entrepreneurs are starting “pure tech” companies is decreasing, but that doesn’t mean that tech stops being interesting. Instead, technology will continue to shape our lives, in ever more nuanced ways.
Progress is not inevitable. Evans makes a pretty broad and hand-wavy point, which is unusual for him, but I have the same question: where are the optimists? What are the good trends that will come out of this moment?
I played a lot of Animal Crossing back when the original title came out for the Nintendo GameCube. My video game career has pretty much ground to a halt since then, but I can understand the pleasure of having an avatar who lives in a much simpler environment, with little risks and an escapist outlook. I wish I’d found something that cathartic early in the quarantine.
“The goal is to treat, not merely to understand” is both an amazing and a scary ideal. The fact that their view of what a “successful treatment” is aligns with mine helps, but in a way this smells like meta-scientism. Nevertheless, I’m excited to watch what Cowen and Collison come up with as they push this movement forward. The salvo is that they are prescribing experimentation, not just solutions.
A funny and pretty ridiculous write up on the strategies that Doordash and other food-delivery startups employ to build up and then shape their demand. It’s pretty interesting to think of the kind of schemes they could come up with to dynamically alter the market they’re in - all via pricing.
It’s not just our faces. It’s how we walk, how we type, and more. Regulation must define detailed specifics of what is accepted and what is not, but more importantly it needs to strike a balance between what we know exists today and what is coming down the pipe.
I heard about this story after seeing Cory Doctorow speak at Berkeley. I hate the idea of a two tier system like this, and I understand why the building owners would think it’s a good idea, but it goes against the spirit of section 8 and the rent-control regulations in big cities. To a much lesser degree I live this situation, as I am a near-market rate tenant in a really old building in San Francisco. Every once in a while, one of my neighbors asks me to email our landlord, to ask him to fix small issues that he’d ignore if they came from someone who’s been living here for decades, and who pays a fraction of what I pay.
A frightening article. This data is being collected in so many different places, by so many decentralized players that it is impossible to put the genie back in the bottle.
You’ve heard of it before - an army of monkeys hitting keys at random for a long enough amount of time will almost surely type out your favorite masterpiece. Here’s the proof, as a live experiment of increasing complexity.
It must have been wild to work on the hardware teams behind the first generation iPhones. I’m looking forward to hearing more stories and seeing more artifacts as the original devices become history, and people feel more comfortable sharing their insider views.
So far this feature has turned out to be less interesting than I expected it to be given the initial excitement, but to be fair I also have not lost any of my devices in the last year.
Having services “without humans” is not a new story. This episode is a mix of history and modernity about restaurants hiding the people running them behind a one way mirror. Honestly, I am not going to miss Eatsa.
I heard Rushkoff give a talk about his book Team Human at City Lights a few weeks before he went on Making Sense. Some of his arguments err on the too simplistic side, but I do agree with his broader message of highlighting the connection between people and that the decisions we make individually affect us collectively.
A conversation on existential risk. Bostrom is the proponent of the vulnerable world hypothesis, which states that there is some level of technological development at which civilization almost certainly gets devastated by default. In his view, it is very likely that humans can create technology that’s so powerful that it can destroy the world. You can think of nuclear war, genetic engineering gone awry, or in a much more present-day kind of scenario, our world gets so connected that a pandemic wipes us out easily. This and more in a very interesting conversation.
Planned obsolescence is not a new thing.
Perhaps, not all content should remain available forever.
At the scale at which my code operates, I’m sure some of my stuff has been at some point affected by a bit flip. I wish I could blame my errors on this, but really it’s just that coding is hard, even when you don’t have to account for solar flares.
Open source encryption tech, early internet days, and an international crime ring? What’s not to like?
Careful how you set up your integration tests. You might end up on a podcast.
What is this, a crossover episode? This was one of the most interesting mysteries I’ve heard the Reply All guys solve, and the fact that Roman Mars was in the mix made it all the better. The worst part is that I thought I knew it was a dumb encoding thing all along, but… just listen!
A deep dive into the insane world of TurboTax and the strategies that enable them to keep squeezing money out of the public while offering the “free option” required by regulation. This is one of the most absurd cases of regulatory capture in the US today.
It’s interesting to hear about how CES works, and the sourcing process for some of these hardware products. By now we should start to see the trends discussed by Evans and Sinofsky in this episode, a year and a half later.
A lot of this episode resonated with me, and how I choose what to read or listen to. I’m excited about the viability of ideas that play with the “negative interest rates of the attention economy.”
Even though I have been working at Apple for 5 years, I don’t feel very exposed to this kind of thinking. The cycle of client development permeates everything in the company, and we all run on the yearly release of new features with the next OSs. However, my role leading a software engineering team building analytics tools means that the stuff that Kocienda proposes goes completely against the principles our team pushes for. It often feels like we swim upstream, but the symbiosis works out.
Merry christmas, shit hit the fan.
“How could I use this product to do harm? […] Can I use this platform, this API, this plugin, this app, this feature to do something that, as reasonable moral human beings, we feel a little uncomfortable about?” These questions matter. The author’s point is these things shouldn’t exist, but instead that there are trade-offs in building them. We should think more about trade-offs.
I’ve been interviewing a lot of people, and a few weeks ago I was asked to cover architecture for the first time. I had never built a distributed system until I started working at Apple. Sure, I’d used Heroku with a Redis instance and a Postgres DB, but all of that was totally abstracted away from me. Reading this was an eye-opener as to how much I’ve learned in the past few years, and it made me reflect on some of the interviews I had while switching teams - even two years ago I already felt skilled at systems design, and that experience is rare. Working at a place like Apple can really distort your perception of what’s normal.
Perhaps I’m too much of a cynic, but I welcome these little time saving technologies. They help me more than they make me doubt my humanity. Thompson says near the end that “to see these technologies in action is to be confronted with the fact that we are not so very special or unique.” Good, someone had to break it to us.
As I read this wonderful piece I kept thinking of Robert Gordon. Unsurprisingly, the authors invoke Gordon’s pessimistic headwind thesis but, unlike him, Nielsen and Collison are optimistic, demanding “large-scale institutional response” to a problem they see as solvable. The thing is, progress is non-linear. Most science isn’t worth the time and effort invested in discovering it. I was a bit bummed out that the domain they are hosting their appendix at (http://scientificreturns.org) is empty. I was excited to click around and learn more about their position, and hoping to find proposals they were bringing to the table. I assume they have more than just this op-ed up their sleeves, so I’m looking forward to hearing more.
People want to help, you just need to make it easy for them to do so. I have been lucky over the years to have naturally found mentorship in family members and friends alike, but the kind of specific pointed requests for advice that Bethany recommends here seem like an art that I should spend time perfecting. If I weren’t at Apple, I’d probably make a bigger effort to tell people about what I’m working on, and what I’m struggling with on a day to day basis.
While I’ve thought a lot about incentives in startups, I had never thought of the kinds of conflicts that arise when a founder fully vests an initial grant. The fact that something like this can trigger a bigger conversation seems especially mis-understood.
The fact that some “huge successes are the results of pivots” does not mean that all pivots are successful. I agree with Fred that in most cases, hard pivots are a bad idea. There’s probably enough data around to calculate whether P(success | pivot) > P(success).
The internet is scary. I have multiple factor auth in most sites, and somewhat understand the intricacies of phone spoofing. My mom does not, and most of my non-techie friends don’t either. This is a problem we have to solve via easy to use products that abstract away all this complexity, or we’ll have to pay for it later on.
Fake news! The problem is that people are gullible, and that we don’t question what we see and hear, not that we are presented with false information. This episode is a good case study with a couple of extreme historical examples, but for a wider overview on the topic you can also check out Sam Harris interviewing Matt Taibbi for his podcast
This episode makes a great point about privilege being geographically bound, which is a recurring topic for me. We can’t agree on values globally, as we don’t all have the same preferences/views. We can’t expect FB (or other companies!) to police that. We can’t make FB, Twitter, or any other company the arbiters of morality globally with a single set of rules. A company can pick what to censor according to one set of beliefs, to be applied equally, or it can respect local belief systems. Since that’s a choice, A company can’t be neutral.
Over time, I’ve gotten used to thinking of cities and neighborhoods as accidents of path dependence. Here, Gans makes the point that the infrastructure that powers all our modern technology suffers from that same phenomenon. Leapfrogging a step or two in the chain aside, every piece of technology we interact with is directly influenced by the same old ideas, and built atop the same old networks as everything else. People are generally amazed when they hear that the internet runs on huge submarine cables between continents, just like the telegraph used to, but even though our systems are much more advanced these days, they are ultimately just iterations in at least some dimensions.
I’m fascinated by the Hirschmanian notions of exit, voice, and loyalty. Here, Mann explains how the rise of cryptocurrencies allow for more use of exit where traditionally people would have leaned on voice. It is exciting to think about how this new technology might reshape the world.
A long piece on Silicon Valley history and ideology, the formation of its origin stories, its organizational structure culture, and its hero-worshipping fantasies. Worth your time.
I first heard about digital celebrities during a conversation with Chris Messina. We were discussing the power of voice interfaces, and he brought up Miquela, which just blew my mind. What happens when my niece or my nephews start thinking of me - their uncle who lives far away and never get to see other than through an iPad’s screen - in the same way they think of these characters? What makes me different from Siri, Alexa, or Miquela? This is only starting.
Clearly I am biased here, but Evans makes good arguments. It is easy to blame big tech for problems. He doubled down with this argument in a different direction [over here]. Tech has caused negative changes, but let’s not pretend that Tech is guilty of everything.
If you’re a blockchain skeptic, this might change that.
Our current policies around labor don’t match the new reality we live in, and neither stopping the “the gig economy,” nor shoehorning it in the old paradigm will do. “…technology does not usually drive social change. On the contrary, social change is typically driven by decisions we make about how to organize our world. […] Uber is a symptom, not a cause.” We can change the status-quo.
We’re headed into a world of protectionism. It is scary to think what won’t exist because of it. "…officials admire Beijing’s tight control over citizens’ data and how it has nurtured homegrown internet giants like Alibaba and Baidu by limiting foreign competition." If India goes down this path, and closes itself off to western companies like China has, the market dynamics of working on new products change completely. When your addressable market goes from being the world to excluding the two economies that are forecasted to be the largest in a few years theres way less incentives to build new things. That’s bad.
When so much of our lives is mediated by giant corporations like Apple, Amazon, and Google, how do we deal with our data? Sure, it is behind a password in the cloud, but someone at whichever storage provider you pick has the keys to some of your data, and most if not all your metadata. This is one of the reasons I like working at Apple - I believe in our commitment to privacy, even if it is just a ploy for market differentiation. Ultimately, this means that I trust Apple, and that the engineers who work on these products are doing the right thing. I could also trust Satoshi, or Vitalik, or Linus’ Law but ultimately, I have to trust someone, and hope that they’ve done their homework.
I’ve talked about this before, too. Google is pushing SoMa as “The East Cut” on their maps now. I literally spend half my waking hours in this neighborhood and the only times I’ve heard it in conversation were either (a) people making fun of Google, or (b) referring to the uniforms that cleanup crews wear, emblazoned with “The East Cut,” which ends up leading to (a). There is a very Orwellian aspect to this story, and to how the digital world can reshape the physical world.
I’m biased, so not much to say here, other than my full agreement with Noah. This broken city would just finish breaking if the tech industry collapsed.
I wonder if Chinese newspapers write about the generation of Americans growing up without WeChat and Baidu. Probably not. Cultural relativism is a recurring theme in my life, and this is one of the most glaring examples I’ve seen recently.
Another one I probably can’t say much about. I am worried about the progress of technology and where this kind of censorship might take us, though.
For all the talk going around about conservatives becoming Keynesians, it’s strange how government spending keeps sliding down. It’s easy to forget how much influence military spending had on Silicon Valley’s success, and how we’re still riding the momentum of previous waves of investment. Innovation isn’t free. It must come about from an empowered, educated citizenry, and the government can take part in that. As Manjoo explains, “every key component in a smartphone, from the battery to GPS, is based on research first done for the American government.” It’s time to fund more of these experiments.
What’s most illogical about the stance that Evans rails against here (policies around data that the gov makes inaccessible “for our security”) is that much of this data could be compiled from observation by the public. “X could lead to terrorism” is one of the worst possible arguments against X, ∀X.
By far, the most interesting aspect of this podcast was around the 1hr mark on why mega-corp moving into your niche business is not necessarily a problem, followed by a fascinating discussion of M&A vs buybacks. I had never thought about M&A in that way, but it is interesting to hear the public markets side of the coin after reading so many positive comments about acquisitions from people like Elad Gil and Marc Andreesen about the early startup stage M&A.
Technology does not automatically make the world better. Most tools can be used for both good and bad. The solution to bad outcomes due to technology is not more of the same technology.
What kind of patterns arise if we look at the street grids in various cities? It’s not all orthogonal cross streets. Open Street Map data, and the tooling to manipulate it, seems to have evolved a lot since I looked at it a couple of years ago. Big props to Boeing for open sourcing OSMnx and sharing so much of his work. Maybe it’s time for a side project…
I’m still going strong on my quest to fight recency bias by going back to old EconTalk episodes. I’m doing this partially to get away from the current “everything is politics” environment, but also to unlock knowledge that’s trapped in the recent past.
A great framing of the set of technologies that everyone is so excited about but which in many ways doesn’t yet live up to expectations. Sometimes, even people deeply embedded in the Silicon Valley/San Francisco tech world get stuck in the “We’re not facegoopplemazforce, so we don’t have the data, and can’t gain from ML.” This is a mistake. The value is in the domain specific low cost solutions. Echoes a lot of ideas in Tim O’Reilly’s What’s the Future, which I’m reading right now.
When I sent Hannah this article, she said “Wait, was that what you were working on? secretly? It’s weird that I never knew.” And well, that’s Apple for you. Having worked on some of the tech behind this, I’m quite happy to finally have it see the light of day. No matter how small my contribution was, it’s exciting.
Hearing Sonal Chokshi and Marc Andreessen interview anyone together is generally worthwhile, but this one with Brian Arthur was exceptional. Arthur is an economist and complexity researcher. He pretty much came up with the idea of lock-in, which is elemental in how we think of business strategy and product development today. His paper on the topic, from 1983, was rejected by 4 leading econ journals, and was only published 6 years later. He kept getting reviews saying "We can’t find fault in this but this isn’t economics!" This is a conversation about that topic, as well as company formation in general.
The story of a startup I had never heard about, and the B2B2C wonder that they built via channel partnerships. The model is super interesting - consumers get something for free in exchange for buying/trying the product of another TrialPay advertiser. The merchant is then paid for by the advertiser. Say you needed softwre X. X costs $10, which is more than you can pay, but if you sign up for a month of Netflix, you could get X for free. If you were on the fence on Netflix, now you have a good reason to try it - you were going to spend the $10 anyway on X - but Netflix’s LTV from acquiring you is much higher than that, and the cost of acquisition ends up being a payment to TrialPay and a payment to X, which can be much much lower than that LTV. This is something that I had never even thought of, and overall a really interesting business model.
A crazy dive into the rabbit hole of unexpected packages landing on our doorsteps, and the fake reviews they enable on the internet.
There were a bunch of things I love reading about here. There’s history, there’s complexity science (that’s how I got into CS in the first place), there’s python, there’s UX, and more. If you’re interested in the future of education and the spreading of scientific knowledge this is a must read.
Obviously Gurley is biased about this company, but he makes some really great points about the gig economy, and Uber’s role in kickstarting it. If there’s a single thing that we should thank Kalanick and the company he’s built for, it’s the availabilty of flexible work options.
An extension of Albert’s well known idea of bot representation. For most people “bot representation” is too abstract, but his rephrasing to “any system with 1 million+ users should by law be required to issue users with personal API keys” is quite clear. Brings up questions about the boundary of one user’s data and the next user’s data (ie, MY post on YOUR profile), what constitutes enough APIs to meet said standard, and who gets to decide these terms. These systems do things on many layers, not all available via UI. They’re different per user and change over time. The data that the API consumes and produces today looks different than it will tomorrow. The software engineering side would be a nightmare. But that can be solved with incentives. The more interesting question is whether we get access to the derived data, or just the raw. Am I only allowed access to my data points, or also the aggregates computed over time and in relation to other users? It’d be awesome to see something like this implemented.
A discussion of how we consume information, and the cyclical nature of how we share things online. Evans’ comparison of the number of items in your news feed to the number of invitees to a party is a clever analogy (kinda like Big O!) but the essay is fraught with uncharachteristically bad assumptions. Stories are less so about “units of content” than about market segmentation. Stories are a news feed, even if in a different format, and don’t solve the oversharing problem - you still get N*M pieces of content.
This problem has existed for ages. Technologists and scientists work on things because they are cool, and because they want to push science forward, regardless of the implications. The debate about whether technology is inherently good or not will keep going.
I still use RSS daily. It aggregates the tiny blogs that produce content at a very slow rate, which I have no motive for visiting between posts, as well as socially ranked content from sites like Hacker News. The volume that I consume is relatively high, but the top of the funnel is limited on purpose, in ways that maybe it shouldn’t be. Going back to Evans’ post above, I think that having something with levers and knobs would be amazing, but I know I’m part of the fringe. The closest I’ve gotten is RSS.
This column asks questions about the future of technology, and which technologies are worth supporting. As you’d expect, it brings in some “marginal cost of 0” ideas, along with questions about what the structure of society should be, and what should be the role of corporations in a financialized world. Ultimately, it pushes us to remember human agency. Being a cog in one of these machines, I can tell you how easy it is to forget we have that.
I’ve been on a Sam Harris binge lately, and it all started from this podcast episode. I’ve been meaning to read Ferguson’s work for years, and this discussion of his latest book gave me an even stronger reason to do so. At first I was interested because of the analysis of power networks and institutions throughout history, but when I realized that the use of the word network was not casual, but actually referring to network science, I was totally sold. I’ll make a big effort to read it this year.
Stripe is a really interesting company, and hearing John Collison talk about where it is going is fascinating. First, he talked about the idea of pitching a company for customers that don’t yet exist, which is kind of crazy, but by definition visionary. Then, they also discussed being seen as a value-add or a toll-taker. I’ll probably re-listen to this one in a few years, just like this other a16z episode on marketing and positioning. Neither is relevant to my current role, but eventually they will come in handy.
As a heavy Twitter user, this is not at all surprising. The platform does not try to hide its spam. Notifications for automated likes, follow/unfollow schemes, and unrelated replies from random bot accounts are daily staples. Twitter staying away from politics has nothing to do with them not addressing the bot accounts. The reason this has not been fixed is that the yardstick Twitter gets measured with is the number of active accounts, and being able to say there are millions of accounts pumping content into the network is valuable to them - it props up their stock price, and keeps investors interested. Don’t get me wrong, I think some bots are valuable to the platform, and have coded up a few myself, but bots that merely amplify the reach of someone else’s account don’t improve the experience of any Twitter user. Of course all these bots disappered right after the NYT published this piece.
We’re all obsessed with our phones. Notifications come and go, and we’re glued to the screens. There isn’t much new in this piece, but I agree with Manjoo that if anyone is strategically placed to do something about it, it is Apple.
Yes, more crypto. I’ve slowly started to become more bullish on the idea of the Ethereum network taking over Bitcoin, and Gil makes several good points in that direction here. In a vacuum, I think that Ethereum has more fundamental value, making it stronger even without the network effects that come from being the first mover, but what will end up deciding whether the number one network is BTC, ETH, LTC or some other coin, is a substantial reduction transaction costs while increasing throughput. Whether that means Lightning, Plasma, Truebit or something else (Gil mentions Bulletproofs), will matter just as much as other versions of SGML matter to us today when using HTML on the web.
Ok, last crypto one. The last month or two have been crazy, but I still think we have a fundamentally different thing going on with the crypto market. And when I say fundamentally that’s exactly the word I’m looking for. When people discuss valuations, cash flows, and discount rates, they’re using concepts that were invented by people to explain prices. Humans made these up, too. That the current model doesn’t apply here doesn’t mean there isn’t fundamental value underneath, it means it is time we come up with a new way to explain prices.
Having had an Echo for quite some time, and a HomePod for a few weeks, I agree with Evans’ view of voice not being the next platform. His analysis on the incentives of different players is probably the most interesting part of the essay - Samsung fighting within itself when trying to figure out how to position itself and how to design its new products, Shenzhen leveraging the supply chain and pushing complexity onto hardware while the SV startup does the opposite and tries to differentiate on software. It will be interesting to see this one play out.
The main point here is that people are willing to pay for niche content that is relevant to them - this is not news. You’d assume that the spending patterns would be different for finance and tech (where money flows more freely) than for individuals and their local news, but in the end its the same people. People paying for Stratechery or The Information probably care about their kids schools, the local events on their neighborhood, and whatever else their hyperlocal publication has to offer. This is why I’m so interested in initiatives such as Hoodline’s hyperlocal news wire.
My friend Leon got me hooked on O’Shaughnessy’s podcast. This one is full of interesting ideas about how to value online assets such as accounts on Airbnb or Instagram, and how one could potentially set up an incentive system to transfer the cashflows of these accounts without corrupting the quality of the underlying service being provided by the creator. See also the episode with Chris Dixon on the future of tech.
A great episode on the surprising origin story of air conditioning. I never would have thought that the original purpose of A/C was to control moisture content in the air for publishing plants, where paper and ink alignment would constantly go out of whack. Human pleasure quickly took over, of course.
And to keep going with the thread on platform companies, here’s one on Amazon enabling lots of new products to come to life. The whole thing is worth reading, but the last paragraph in the article was extremely sharp: “There is this erosion of what it means to be a traditional consumer product brand,” Mr. Wingo said. “In a way, Amazon is providing all this information that replaces what you’d normally get from a brand, like reputation and trust. Amazon is becoming something like the umbrella brand, the only brand that matters.” Amazing.
It seems like Evans took Farhad Manjoo’s article (the one right above this) and ran with it, taking it an extra few steps. Two pizza teams, and shipping the org chart are not new - I thought the new insight was Evans’ third consequence “those atomised teams don’t actually need to work for Amazon.” which totally resonates with Manjoo’s argument.
This is probably the best survey I’ve read about BTC’s growing pains and the tech being developed to solve them. It doesn’t dive too deep, but will expose you to a bunch of ideas, from the Lightning Network to MimbleWimble (yes that’s a thing). I’m only bullish on crypto long term because I know the community is working hard to build solutions to these problems, even if vanilla BTC is not the one to succeed.
If you haven’t seen O’Beirne’s series, you should definitely click through. The first couple of posts he did on the topic came out while I was working in Maps, and honestly some of his points were disheartening. What Google is doing with their geo data is just amazing.
I try not to post more than one article by the same author at a given time, but this one was too good to pass up. Ties nicely with other posts about technology and society I’ve been sharing over the past few months. I’m looking forward to what scandals the tech sector will give us in 2018.
Whenever I see stuff like this I regret not taking any graphics courses at school. Modeling reality is very hard. I remember a few years ago learning about how Pixar did hair simulation and finding it fascinating. The Incredibles was one of the first ones in which they seriously took on the physics of moving hair, and then went all out with their physics engine for Brave. In this article they discuss surface modeling, and a new technique they’re using to speed up rendering.
I recently started re-listening to some older episodes of EconTalk, trying to see whether the talking points have changed in the past couple of years. The episode focuses on labor economics, and O’Reilly makes a few good points about changes in how we view labor and reputation today, and how that is changing. Listening to this again made me bump up his book a couple of spots for my to-do in 2018.
This post is full of non-crypto/non-blockchain interesting ideas, from basic coordination and incentives, all the way to full fledged frameworks to replace democracy, like Hanson’s Futarchy (which I had never heard of before, and found super intriguing!). Framing the problem of governance as one of dispersed information in a changing environment is very Hayekian, which lines up nicely with what I’ve been reading recently. Toward the end, Ehrsam suggests players should focus on the metaprogramming of systems (ie, the decision making workflows/processes by which these systems evolve) instead of the systems themselves. I like this view.
A good intro, with both the bull and the bear cases well summarized. As usual, Suster does a good job of making complex topics available to non-technical users. This seems especially important these days.
This investigation of the publication Peter Thiel started while at Stanford was fascinating. Surely, there are other such clubs, at Stanford and elsewhere, with similar outsized influence in the business world. What makes the Stanford Review so interesting is the ideological aspect in this moment in history. I played a bit with the data and built a simple network visualization. As Granato mentions in a different piece, it is strange that by virtue of having been to an elite institution both him and I are just one link away from the people in this group, and of each other.
If you have been following along lately, I’ve been talking a lot about tech and politics. Here, Ben Thompson summarizes last week’s hearings. He describes the controversy as “largely centered within the coastal tech-media bubble,” and I could not agree more. The real question is what average Jane and Joe in the rest of the country think about this, and those are exactly the voices that these politicians (in theory) represent. I’m convinced the hearings were useless in the grand scheme of things, but the arguments presented will be tested in other arenas in the months to come - I can’t wait to see where this ends up…
…Especially because government doesn’t seem to be the right answer here. Regulation of tech companies is especially hard because the zero marginal cost model in which they operate does not match the original point of antitrust. Consumer surplus might be high, but the real problems being tackled here are not simply about prices, supply, and demand. Having the government police feeds is a freedom of speech question, but we also don’t want Zuck & friends to explicitly start censoring what can and can’t be seen. Lots of stuff to think about.
The internet has changed a lot in the last 20 years. Ford does a little recounting of his time online, and the rise of walled gardens versus the open web.
Square is a more interesting company than Twitter. They don’t sell ads, nor nudge customers into buying things. Their product reduces friction in other companies’ transactions, which sets them apart from the rest of the pack of Silicon Valley startups. I am particularly intrested in how quiet Square (and PayPal and Stripe and others) has been about crypto. I wonder not what Chase and Goldman are planning to do with these new technologies, but what Stripe and Square have in store.
I like Evans’ analogy of Facebook as a company that surfs on user behavior. As he says, “we attribute vastly too much power to a handful of product managers in Menlo Park, and vastly too little power to the billions of people who look at their phone screen and wonder which app to open.”
In a short conversation, Levine and Cowen discuss recent innovations in the fintech space. From blockchain, blockchain, blockchain to index funds and globalized diversification, the two bring up good examples across the spectrum. What’s interesting, and which neither Cowen nor Levine really discuss is the fact that the surplus of innovation in finance has not really gone to the consumer. Perhaps the only exception mentioned is the expansion of access to credit products, which is not necessarily a net positive.
Brown brings up Vonnegut’s Player Piano, which features a dichotomous society where “only engineers and managers have gainful employment and meaningful lives.” Connecting the novel’s dystopia to the present isn’t too hard to do. What’s interesting is Brown’s connection to retirement investing. The origins of retirement come from not being able to do your work - i.e., losing your good hand, and with it your ability to work the land. Only in the past few decades did this financial structure evolve to the 401k’s and IRAs as we know them today. What if we’re going back to the origins of the model, except not as insurance for health, but for disruption? Replacement insurance. We invest in FAANG and reap the benefits.
Uber, like most modern companies utilizes randomized and semi-randomized experiments all the time to imporve their product. In most cases, these are externally labeled as promotions, or offers. In a strange case of these “deals,” Uber recently offered its drivers to pay a fee for the chance to get higher pay rates in the future. However, since Uber has nearly full control of the system - and specifically, the dispatch - this smells like a scammy pay to play. How can drivers trust that Uber won’t throttle their rides as they get near the break-even? This is hard to prove, unless you’re Uber. Over on HN, the discussion turned to ways that Uber could be cut up in an antitrust case. One company as the dispatch, the other handles the rest. That could work. We’ll have to wait and see what happens now that Lyft has some new air.
I can’t remember where I read (heard?) this argument, but I think the real issue is not so much that there is no upcoming technical revolution, but that the behemots have learned to disrupt themselves. The FAANG companies are pouring resources into areas that undermine their cash cows. Google is investing in one-shot answer voice assistants that can’t show ads. Apple is developing hardware like the Watch and the AirPods, whose goal is to distance us from our iPhones. Whatever can’t be done in-house in a reasonable timeline is solved by acquiring or copying. This hampers bottom up Clay Christensen style disruption for sure, but I am by no means as bearish as Jon Evans is in his piece. Technology never ceases to amaze us, and the paradigms keep changing. More on this topic, by Farhad Manjoo here.
More on the social cost of Twitter, and the kind of dynamics enabled by having social networks without strong principled moderation. It is always intriguing to read opinions that have morphed over time, and to go back to the origin story that most observers can’t tell first hand.
Hearing Benedict Evans and Tim O’Reilly discuss O’Reilly’s new book was good, but a lot of it was a rehash from the previously shared EconTalk episode. About halfway through there’s an interesting discussion on optimization. We’ve created institutions that optimize for certain metrics at all cost. At the micro level, we have companies building machine learning models to drive engagement, but at the macro level we expect companies to maximize shareholder value. This is a human decision, codified into law to maximize welfare - at least in theory. Perhaps trusting the market mechanisms and the individual search for arbitrage opportunities is no longer enough. There might be other trade-offs to consider in how companies, and the market at large, are run. In a way, the market acquires a life of its own, not too differentt from a paperclip maximizer.
As I’ve mentioned again and again, the value of ICOs, tokens, and cryptocurrencies is in the new economic structures they enable. In her post, Ou goes through some late 90s/early 00s history of failed protocols and ideas which are now actually possible thanks to blockchains. However, the point of her post is that the potential benefit of the introduction of blockchain comes hand in hand with an increased friction in the form of transaction costs. Whether the benefit of deploying these ideas is greater than the friction introduced remains to be seen, and that is what will make or break each of these crypto projects.
I have long held the view that governments operate with relative ignorance from what their constituents want - not because of nefarious reasons, but because humans are humans and communicating our needs and desires is individually really hard, and nearly impossible at the collective level. The Silicon Valley mindset has its blind spots, but the fixation on experimentation and short feedback-loop iteration is something that could improve policy decisions. It is good to see the top brass realize some changes need to happen outside of the market.
Today, unlike in the past 50 years, there isn’t one big tech company at the helm directing the path of technology a-la IBM/Microsoft. Instead, incessant competition between the big four means these companies are always on their toes, and that they are always thinking of how to reinvent themselves. This is a point that Evans has been making a lot lately, and which makes me optimistic about the future of technology. However, these companies are huge, and growing bigger day by day in a way we have not experienced before. The implications of that are not clear. Pardon me the long quote, but it’s too good to pass up:
There probably won’t be a technology that has 10x greater scale than smartphones, as mobile was 10x bigger than PCs and PCs were bigger than mainframes, simply because 5bn people will have smartphones and that’s all the (adult) people. There will be something, though, and though ’something will change, but we don’t know what’ is an unfalsifiable point, so is ‘nothing will change’, and I know which side of that argument I find more likely.
A highly dystopian article. The presentation of this gig economy company as a consumer education platform is frightening. The fact that a team of engineers is building this, consciously, makes me upset. This is not an algorithm pulling the wrong thing into a feed, or acting upon the biases in a training dataset - these are people building the infrastructure for an ominous future. Why watch Black Mirror when non-fiction reads the same?
The article was really good. However, it’s something that the average person outside SV does not find problematic. People think of FB/Google/Amazon/etc as benign - we use them because they’re better than alternatives. The problem is, the more we use them, the more they become irreplaceable. Network effects/economies of scale here are a strange loop. Google is good because it has all our data, it’s bad because it has all our data. There’s a lot to be worked out here. How much of it is narrative, versus actual skepticism.
I knew that Amazon employed a ton of seasonal workers, but I had no idea of the extent of the program, nor the fact that most of the laborers were retirees. Bruder does a great job in this exposé, giving us a window into the dystopian labor conditions that her protagonists endure. Most interesting is the fact that for a non-insignificant group of the population, the pangs of the financial crisis are still very much alive. I also read a review of her book in the NYT, where the reviewer pointed out a fact I kept thinking about as I read the column - this is all about old white people. A big error of omission in an otherwise great read.
To close on a good note, here is a cool project - training crows to collect cigarette butts, with computer vision and creativity!
A great summary of how social media’s influence creeped into the political landscape. Madrigal’s account is more thorough than I could even imagine. Perhaps the most interesting point about his piece - one that I had not seen made this clearly elsewhere - is that the 2016 election was not so much about blind-siding, but frog-boiling.
The reason cryptocurrencies, and the technology behind them, are exciting for me is not their insane returns, but the economic and political implications of creating totally new incentive systems. Matt Levine has a good summary of how these differ from the traditional VC backed company in yesterday’s Money Stuff, but Elad Gil’s post goes much more in depth into what kinds of corporate structures are enabled by crypto.
The notion that Trumpism arose thanks to the 2017 equivalent of a DDoS attack, or an SQL injection on social media has been going around for a while. Here, Thompson makes a good analogy between Facebook today and Microsoft in the early 2000s, and exposes the dangers of assuming people’s good intentions on your platform.
An unusual EconTalk, where the topic is a mixed bag of technocracy and an optimistic outlook of the current technological revolution.
In case the Stratechery post above was not enough, here’s Ben doubling down. Aggregation theory paired with politics. Towards the end of the episode there is a discussion on how, via regulation, increased transparency in the decisions made by algorithms could enable journalists and citizens to openly review the outcomes of machine learned systems, which in turn would change the behavior of the advertisers and scammers. Overall, a good way to spend an hour.
Resource allocation is hard, and only gets harder with size. That’s why startups can carve themselves a niche and take over huge companies. Most projects are not worth pursuing, and not useful. Focus gets the win. Pretty related to this a16z episode on growth strategies and how to handle cash.
One of those articles that make me wish I had been a CS/CE major. The things we do to make computers go fast are crazy.
My experience of technology, and that of most readers of this blog, is one predicated on high speed access, tens, if not hundreds of gigabytes of storage, and last generation processors paired with large amounts of memory. How does the internet work when “fast” means you’re streaming over 2G? What do your apps store when the drive on your phone holds only a couple of gigs? How do you find content your when you’re illiterate? This article doesn’t try (and can’t!) answer these questions, but provides data and anecdotes of why they are questions worth asking.
Organizational behavior is insane. Moving thousands of people towards a common goal is hard, and I hadn’t thought about how insane this 10x personnel increase that Evans brings up is. You should listen to the related podcast, and if you haven’t read Sinofsky’s Functional versus Unit Organizations, you should probably do that first.
I absolutely hate Buzzfeed’s super optimized methods to grab my attention, and knowing that’s the goal I try to avoid their non-investigative content. However, Tasty is a great idea, and it is very well executed. I probably have burned hours of my life looking at their cooking videos, and yet not once have I tried one of their recipes (even though I cook almost every day!). There is just something about melting cheese oozing out or chocolate drizzling that makes you want to keep watching.
I wonder how much of an actual trend this is. I haven’t paid for cable since I moved to the US, but I also have no interest in local TV, and I don’t think any of my friends do either. Yes, yes, we’re not representative, blah blah, but still. The craziest thing about this is people’s reaction to the fact that some things are free ‘No, you can’t live in America for free, what are you talking about?’ 🙄
The ethics of journalism, and the history of how modern journalism itself came about are interesting topics that I don’t know much about. I should work to change that. In the current historical context, it is important to understand how and why the content we consume is created. This post was a little too consparicy theory heavy for me, and yet I thought it was a worthwhile read. As I mentioned to my friend this weekend, I worry about the future of journalism. Laurene Powell Jobs buying a majority stake in the Atlantic or Bezos buying the Post kind of works in the short term, because their ideologies align with mine, and I kind of trust their intent, but tell me that the Koch brothers are buying the WSJ, and my reaction would be different. Creating incentives to keep the editorial integrity while maintaining a viable business is a tough 21st century problem.
Holding the keys to the content is not as important as it used to be. Partially, I think this has to do with the fact that the market for content has been totally flooded, an aspect that Evans does not touch at all in his article.
I would love to spend some time in China and understand how some technologies are being leapfrogged over there. The article reminded me of Charlie Warzel’s cashless Swedish adventure, which I shared when it came out last year, and is totally worth your time. Especially interesting here are the aspects of consumer lock-in to these two companies (Alibaba and Tencent) mobile payment systems, and the lock-out experienced by foreigners.
I had never thought about the political implications about generating electricity at home. This episode discusses “net-metering,” or the billing mechanism that allows someone with PV panels on their roof to get credit for generating more electricity than they consume. How did it come about? Some guy plugged his PV panels into his meter, and it started going backwards!
It’s ridiculous to think that spreadsheets were so revolutionary only a few years ago.
Is it illegal to study how a system works, to the point that you understand it so well that you can exploit it? No, that’s the whole point of open source software. Patch the issue, give the gray hat his bounty, and move on.
If you think about it hard enough, everything is made up. Countries, money, companies, the constitution, everything! And, blockchains, too…
Identity online is hard - and I don’t mean tying your persona to social media, but actually tagging bits and bytes with other bits and bytes to identify them across machines. The self-incrementing column of integers is a mainstay of traditional databases, but what happens when scaling across machines becomes necessary? Here’s some history of how that’s been solved across the years.
Posted without comment.
Posted without comment.
In a strange melding of worlds, Ben moves away from the usual tech talk and goes deep into the history of financial manias. Using Yuval Harari’s notion of shared myths, this post makes a clear difference between bubbles of irrationality, and bubbles of timing. I firmly believe that crypto is one of the latter.
Evans with the counter-narrative: “It’s easy to envision how and why an interwoven mesh of dozens of decentralized blockchains could slowly, over a period of years and years, become a similar category of crucial infrastructure […] while ordinary people remain essentially blissfully unaware of their existence.” Ah, and nice Fred Wilson burn. I also thought the Rare Pepe story was nuts.
The writing has been on the wall for a while - is not a surprise - but the numbers are staggering: “42% of Chicago’s taxi fleet was not operating in the month of March […] The average monthly income per active medallion has dipped from $5,276 in January 2014 to $3,206 […] medallions hit a median sales peak of $357,000 in late 2013, just before Uber arrived on the scene in Chicago. In April, one medallion sold for just $35,000.”
Initial coin offerings (ICOs) are all the rage these days. Some people will get screwed in this process, and I am staying away from buying any ERC20 tokens for a good chunk of time.
See also, The Squid.
Nothing about Farhad’s argument seems controversial to me. There are still unsolved problems in the vein of “finding a needle in a haystack” where separating signal from noise has become increasingly difficult, but the expansion of content produced by humans can only be a good thing. If we trust that willingness to pay will somehow sort out the good vs. bad content problem in the long run, we’re headed in the right direction.
All new technology can be seen as a double edge sword. Luckily, crypto wasn’t killed by the US government.
The cyber is hard.
This happens daily to me. Sorry. Not sorry.
Like I said last time Evans wrote about this, “voice interfaces seem to be adding more friction than they take away.” Changing people’s habits is hard. I constantly prompt my Echo by saying “Hey Siri,” and find myself thinking of ways to phrase my questions to make them intelligible by the machines. Once or twice a week I get developer emails about “What’s New With Alexa,” but after many months my Echo only acts as a gateway to Spotify, and a party trick whenever there are guests. Voice might be the new platform, but it is nowhere near.
Something I will never understand is how someone can enjoy poring over low level buffer management for hours to find an overflow condition or some obscure vulnerability. Luckily some people like watching water boil with their white hats on, and do it for the greater good, too.
2017 gave Uber a rough start. In an unusual post, Ben argues for a change of leadership, focusing on two questions: ‘Is Uber’s approach to regulation wrong?’ and ‘Is Uber wrong with regards to the specific issue at the center of this controversy?’
One of my favorite episodes of a16z ever. Touching on the subjects of nationalisim, imagined communities, religion, governments, etc, etc, etc, and how all of these are affected by the rise of technology. I had shared a related piece from Harari a few months ago, but this podcast episode is way better.
It has been interesting to see Ben apply aggregation theory to politics more and more. I agree with the views presented in this article about centralization (or lack thereof), regulation (or lack thereof), and market solutions (or lack thereof).
Since Snap’s S1 came out a couple of weeks ago, everyone has been discussing whether moats exists or not. The fact that their whole thesis revolves around the disintegration of sustained competitive advantages is fascinating. Evans’ index fund analogy adds an interesting idea to the mix: Facebook, Instagram, and Google must reflect reality and serve billions, while Snapchat will aim to create N things, each worthwhile to M million people, such that N*M becomes significant while not overtaking the role of the index.
I have previously discussed Szabo, and his view on human institutions as “trust-offloading mechanisms.” In a way, money is the ultimate trust-offloading abstraction. Until the last few years, money – American Dollars, the Euro, or the Costa Rican Colon – still relied on trusting several points of failure – states, the payments networks, the certificate authorities – and our human interactions simply assumed those costs. Bitcoin and the internet have started to changed that, and further developments in technology promise much more. This is a post I’ll probably re-read again soon.
I have seen the Snap <=> Apple narrative popping up over and over across the web. Except for the “obsessive-design-focused-mission-driven-CEO” story, which I can’t really ascertain (and neither can the media!) , I haven’t really seen any good arguments to back it up. Ben comes the closest, but doesn’t quite convince me either. The Facebook <=> Microsoft analogy is much more believable, given the market conditions. I am bullish on Snapchat, and I am enjoying my spectacles (a different blog post soon?) but we’ll have to wait and see how this one plays out.
There is a comment I especially liked here about how “…innovation in the modern economy isn’t just about snazzy new technologies, but boringly efficient systems. The Billy bookcase is not innovative in the way the iPhone is innovative. The innovations are about working within the limits of production, and logistics, finding tiny ways to shave more off the cost…” The iPhone example is coincidental, I’m sure, but I immediately went to “this is the argument against Tim Cook.” It is hard to appreciate how much of today’s Apple is dependent on the advanced supply chain operation that the company has built. Pushing atoms is also innovation.
What happens to our urban environments when car culture goes away? What kind of businesses are enabled due to autonomous vehicles?
A story of weather reports, demonstrating path dependence1000. “Choices we agree on now are going to stick around, and get baked into the foundational brick of our biggest, most critical systems. Be careful what you toss in there!”
What is your red line?
What is a nation anyway?
Ten years ago today, Steve Jobs unveiled two products that could change the world. One did. The other one was the Apple TV. Ben reminds us that how much he’s idolized, “it’s worth remembering that even Steve Jobs hedged his bets.”
Humans have learned to defer decision making and process to “things” since time immemorial. The main goal of this is to offload brain cycles into simple rules, and ease our interactions with the world around us. Szabo brings up examples like clocks ands traffic lights, which enable coordination between humans that would require way more effort otherwise. We can also think of learned heuristics, encoded in folklore and religion, as other means of offloading. Clocks ease friction as long as we agree on their time, just like ideas of good and evil ease friction as long as we agree on their base truth. Clocks and religion are trust-offloading mechanisms.
There are way more immediate ethical issues with AI than “oh noes, it’s going to kill us!”. We can keep researching and building better systems, and in fact I’d argue we should, but instead of thinking about how to regulate the companies’ ability to kill us, we should regulate their ability to collect data indefinitely, as we don’t know where it will land. I am more scared of humans than machines.
Time is complicated, especially in massively distributed computing systems. I’d love to understand this topic better. If you have recommendations on what else to read, please let me know.
I have had an Echo for several months now, and I still see it as a gimmick, but I understand why the strategy behind the device has so much going for it. Amazon is building a platform that makes a lot of sense, but the technology isn’t quite there yet. It’ll be interesting to see this pan out.
Twenty years after this article was published, both academia and industry are still struggling to understand the implications of increasing returns, network effects, and zero marginal costs. It is good to take a step back, and see how a view from the past can improve our understanding of business dynamics today.
How does pricing strategy work in a world where decisions are programmatic, and therefore can’t be viewed through the lens of traditional game theory or antitrust case law? Can you blame a supplier who “sets and forgets” his pricing scheme, and somehow ends up selling a book for $23,698,655.93 (+$3.99 shipping)? Interesting times are ahead.
A treatise on the nature of companies, organizational structures, and getting things done when there are thousands of independently moving pieces. Throughout my four years in college, I mocked the idea of a major in “learning and organizational change.” I still do, except now it’s for a different reason: even with years and years of experience, and several real products under their belt, managers can only have a sliver of the picture. People are the hard part about management.
The leaders of our industry are not bending their knee. At least not yet. Take it from Dave Pell: <a href="https://medium.com/@davepell/why-they-sort-of-have-to-go-77535544d2bd">they sort of have to go.</a> The real question is what will happen after the meeting, but Swisher got an important part right: “fuckfuckfuck.”
A fascinating story about figurative walls coming down. It made me think a lot about the inadequacy of the label “third world.” Coming from Costa Rica, which has the highest internet access rate in Latin America, the experiences told in this story are shocking. Widespread definitions and categorizations sometimes don’t make sense.
In this interview wit Joel Mokyr, Sonal Chokshi and the a16z team bring historical perspective into today’s economic environment. Building new things is easier when you have an understanding of the past. The episode reminded me of why I should have taken Mokyr’s class at NU, instead of signing up for an awful data structures course.
A piece that echoes a lot of my own thouhgts on identity, well-summarized by quoting Nassim Taleb’s Black Swan: “…a philosopher from Peru resembles a philosopher from Scotland more than a janitor from Peru.”
In classic Pinboard style, Cegłowski starts up high with evil armies, police, and governments, but shows how in the end individuals - in this case, technical individuals - are on the hook. Facebook, Amazon, Google, and yes, Apple, all are comprised of individuals. What do we do to make sure that our decisions remain moral?
Honestly, I don’t remember how I found this article. I assume Twitter. Finding who to give credit for it was impossibly hard. In any case, while the whole thing was interesting, the most valuable piece was learning about Pierre Jaquet Droz and his 18th century robots.
Aggregation Theory applied to Trump.
15 years went by quickly. I remember my first iPod, back in 2004. Hearing a bit of what the future looked like back then is worthwhile.
History definitely rhymes! “…here’s the deal. Most people aren’t power users” is exactly what I’ve been thinking the past 5 days after the Mac release event. I am convinced that this generation of MBPs will sell well. Even if I am not buying one, the majority will.
The big question about technology today is who will be the leader for the next platform. As usual, great insights from the Andreessen Horowitz hallway.
We are nowhere near a transparent general AI, and all the companies buidling voice interfaces know that. By now, Siri, Alexa, and Google Assistant have all been positioned away from such an all-encompassing solution, pushing for ever narrower use cases. Like the AIs out of Facebook’s bot fiasco of 2016, voice interfaces seem to be adding more friction than they take away.
I am sharing this, even though I honestly did not read the whole thing. An 11 part epic on how the internet works. A good production, even if a bit overwhelming.
If there is one thing I have learned over the last year, it is that even small projects require huge overhead when your tolerance for error is small. Building services with acceptable uptime, reliablity, and performance is extremely complicated, if not nearly impossible. “I could do that in a weekend” is a strawman. In fact, I have come to the opposite realization… it is surprising that anything works at all, even when thousands of human hours are invested!
As usual with Maciej, there are many layers to this essay. The comparisons between libraries and the internet are not new, and his railing against large companies aiding online surveilance are more than expected. Much more interesting are the questions brought up about archiving the modern web - where content is selected, joined, and rendered dynamically per user at load time, with large portions behind walls: What is the point of building a community you don’t own? What should be kept for posterity? What is a the point of a site’s snapshot without the code that makes it work? What happens when a company dies, or misses, and we go beyond simple link-rot? The conclusion is hand wavey, but the future of the internet is, as Maciej put it, contingent.
We all fall prey to cargo cults: following our biases and finding patterns where there might be none, mimicking the inessentials and hoping we get the same results. Think hard about why you do things, and trim as necessary.
There is too much Apple speculation here for me to make strong comments, but go read it. Products don’t exist in a vacuum.
Similar to the recent Bloomberg article. Amazon seems more and more serious about their last-mile effort, and the incumbents are still incredulous.
There are clear tensions regarding how information is stored and accessed on the internet. In the OSS world, there is a loud group that constantly complains about the IRC => Slack trend, for example. Whether the fringe is becoming more or less accessible, I don’t know, I have not tried to hang out there, but there is an overwhelming feeling of the walls closing in on themselves.
Probably one of the best features in Spotify. Pretty cool story of how it came about.
A glimpse into the future of media/advertising, an interesting personal story, and a product I’d love to try. The back story of how this story got leaked by Business Insider, and the WSJ ended up being whipped into releasing it early says a lot about journalism in the 21st century, too. A lot to unpack.
Another piece about the perils of living attached to our screens, and taking a break from the addiction. These have become more and more common, but somehow Sullivan gives a refreshing view.
I wish I understood licensing better, but this is a first step. Open source software is amazing. It is one of the reasons computers today are as powerful as they are.
Another cool project on image processing by Zucker. Code that solves a real problem, however tiny, is always worth reading.
A few weeks have vindicated Ben’s comments. While everyone was thinking about the missing headphone jack, this article explained the latest iPhone release for what it most likely is: set up.
Slowly, one abstraction at a time, software engineering has become more and more accessible. The advent of Ruby on Rails marked the beginning of a wave that lowered the barriers to entry for programming, particularly web development, for thousand of engineers. I am one of them. Now it is time to put in the hours and master the craft.
Real innovation takes time. It is, however, important to remember that cycles are contracting. Innovation itself is accelerating, and that needs to go into our decision making models, too.
The events that are developing in the EU right now are potentially more important to the future of global culture than most people realize. Whatever conclusion comes from this case might define sovereignty and jurisdiction across national and supranational borders. As Tim Cook posits in his letter, “at its root, the Commission’s case is not about how much Apple pays in taxes. It is about which government collects the money,” and that is the actually interesting question here.
What is the point of work? What should people spend their time on, and why? Wenger argues that we are about to enter a post-capital and post-labor world. I still haven’t decided if I should read his book now, as a draft, or when it is published in a few months.
No data was released, but here is the original paper, in case you want to take a look.
Amazon is an impressively interesting company (as an aside, the old timey look of the photos is great, too). The original bits and atoms startup, which somehow keeps innovating.
Starting a career in software engineering during the days of AWS and Heroku gives me a strange vantage point. The story of how Netflix switched their whole infrastructure would not be half as impressive if I didn’t understand the role of culture in organizational change. The fact is that “this is how we do things around here” can make or break you. This episode talks about the architecture that underlie the modern web stack.
Harari discusses the jump from religion, to humanism, and now Dataism: Letting go of “religion” and “feelings” to guide our choices, and allowing computers to make decisions for you. As much as “knowing thyself” is great advice, making good decisions also requires knowing the rest of the world. No matter how much you know yourself, there will be unknown unknowns about the people and things you interact with. Computers might be able to help us there.</br>A specific case I’ve thought deeply about is “choosing what content to consume,” which applies to books, articles, podcasts, MOOCs, etc. Objectively, there is some optimal solution to this question, and Harari’s Dataism probably has a better answer than humanism, regardless of how uncomfortable that thought makes you feel.</br>The idea is powerful, and we can similarly extrapolate to other questions.
Lately I have been bringing up Maslow’s hierarchy over and over. I am one of the few lucky people in the world who (like you, probably, since you’re reading this) get to only worry about the very top of this pyramid. Food, shelter, health - all these are non-thoughts for me. My concerns are much less important. In the context of this article, I have been spending many hours considering how to be happier at work, and spend my time to maximize my learning and my future opportunities. Even in the tech bubble that I live in, things can be much worse, and it is sobering to remember that.
The filter bubble, v2.
Software engineering, and the tools required for it, have evolved significantly over time. Barriers to entry have been lowered, making programming accessible for “normal” people, both in terms of monetary costs as well as in the amount of effort required to get started and build something significant. For better or for worse, modern programming languages are english-like enough that they can be grokked by children. Writing machine or assembly language can be seen as an esoteric exercise by today’s standards. On the shoulders of giants, we’ve climbed up several levels on the ladder of abstraction, and as Wenger implies, this is not stopping any time soon.
Whether penny auctions can be classified as gambling or not, they could be a source of really interesting decision theory/behavioral economics research. If you know of any studies particularly worth looking at, please send them my way.
A follow-up on last week’s post on Docker, and the state of distributed systems on the web. This one being the non-satirical version.
Being on the inside, I can’t say much about this, other than: I’m still bullish.
Incentives rule all our decisions. If the mandate of fiduciary duty is to “maximize shareholder value,” that is what any board will do. Whether the “business decision” was correct or not is a question of short-term vs. long-term thinking, discount rates, and how much the company values its employees. When labor is interchangable, this is not a surprising decision. If the well-being of the employees were somehow baked in into the pricing model, there could be a different outcome.
As usual, Evans gives us a lot to think about. Our phones aren’t really just phones, and our cameras aren’t really just cameras.
Overengineering is a real problem. I need to learn more about this new dev-ops world, and play with Docker et al, but the fact is that to get started, a monolith running on Heroku is more than enough. Scaling will be harder? Yes, but you might actually get something done and sell to real users. Good enough is good enough. Once again, short-term vs. long term incentives.
“Serverless” is the Next Big Thing. Serve static stuff on S3, make everything stateless, and plug a bunch of functions in Lambda. AWS once again changing the paradigm.
I like to think of myself as a much more fox-ey than hedgehog-ey person, and I think success comes from getting a fox to surround themselves with hedgehogs. This is true in the AI context, as well as many others. “To think about tech now is to think about many things.”
The internet: where nothing is really private.
Some really cool research by Francesco Corucci et al.
It is always interesting to see how others do things. Especially interesting is the migration from python/node to Java/Go, and the heavy usage of OSS projects. I agree that having less languages is good, however, this might be a bit quixotic.
In the modern office, email defines workflows. Communicating over email is hard. Do it right.
Related, and somewhat more in depth, is the a16z podcast on emoji. Why do these icons carry so much weight?
Leadership is hard, and requires personal sacrifice. People appreciate that, and can tell when a person in power doesn’t put in the required effort. According to Woehr, Marissa did.
Because who wouldn’t tip $3 on a cup of coffee?
In a recent post, I shared Charlie Warzel’s analysis on the future of payments. This episode of the a16z podcast takes a deeper dive.
An inside look at how Facebook runs. The content is a little wordy, but I’d like to read more about this story. Will probably end up buying the book.
The evolution of programming languages depends not only on what new languages allow you to do, but what they don’t. Taking away an engineer’s ability to do X also removes a concern from the picture. Thinking about less things at once means you can focus more on what’s left.
Watching this show would not be half as fun if I didn’t interact with the people it mocks on a daily basis. The caricatures are spot on.
Ross Goodwin keeps pumping them out. Non-sensical, bizarre, and a bit over-dramatized, but interesting.
San Francisco and the Gold Rush, both old and new. Labor, unions, and narratives of success.
HTML, Flash, Video, etc, are only a medium. Corporations today are working hard to exploit these new means of distribution.
Understanding that developing markets are fundamentally different beasts, and not just waiting for copies of what has already been done, is both challenging, and exciting. Makes me wonder what I could do if I went back home.
Yes, two posts by Evans today. It’s that good.
A glimpse into what money might become.
The application of these simple machine learning concepts keep impressing me more and more. Autoencoders are a very simple idea. If anything, click through to see the side-by-side video.
Few times does a post involving convoluted math and programming seem so clear. The diagrams help a lot, and the jump to 2D is mindblowing.
Orwell would be proud.
I learned this exists from my manager, who used to work at Netflix. Mind blown.
TLDR, no one noticed until the guy revealed it.
The “best” is not always enough.
Culture is fascinating, but also really subjective, making it hard to quantify, or analyze. To make it worse, it is turtles all the way down: culture matters at the company, division, group, team and individual basis, and the larger the company the more culture solidifies as a “thing” that makes that company what it is.
Speed is rarely the reason to pick a programming language these days. See below.
Mostly, its a matter of taste. See above.
It takes guts to describe your company as the “…most popular way to buy, sell, and use bitcoin” or, more humbly, a “bitcoin wallet and platform” and then come out and say that something else is better, and possibly more sustainable, than BTC. Smells like a soft pivot to cryptocurrencies in general could be coming.
If I am sharing an article by this guy, it must be good. Never thought I’d do that, but he does bring up good points.
The legal field is not very technologically enabled. As Casetext’s Jake Heller points out, “We’ve all seen this story. Whether it’s restaurants or encyclopedias, this is going to be replaced by an open knowledge solution.” The question is, which of all these services will win the market (full disclosure, my girlfriend works at Casetext, and I think they are doing great work at making legal data easily available).
While I enjoy reading about the breakthrough techniques in deep learning, applied machine learning, with weird and fun objectives and non-standard datasets is much more exciting.
The article talks about topics beyond management, but spends a good chunk of time discussing why projects with many moving pieces, many stakeholders, and many contributors are hard to do right. Mostly, because people are hard to understand. If you understand people, you’ll be a better engineer, better designer, and better manager.
As Marco says, “…the last thing we all need is for the ‘data’ economy to destroy another medium.” Implied, but not mentioned in the article, is the discoverability problem of podcasts. Finding 10 shows that you generally like is easy. Finding the best episode of those 10 shows is impossible.
Incentives…
It is weird when you can’t credit an author because their work doesn’t list their name. </br> As a side note, tweeting this got me into a strange twitter fight.
While I understand the point of regulation, Opternative delivers exactly what it advertises: refractive eye exams. The incumbents are just using regulation to push their interests and avoid getting pushed out of the market. But, obviously, I am biased. I used to work there.
Possibly my favorite opening paragraph in a TechCrunch article, ever.
Extreme clarity on the future of journalism, media, and strategies for companies in the space to respond to change. TL;DR: create better content or disappear. The arguments fit perfectly with Aggregation Theory, and while the article is a bit too focused on politics, the analysis could apply to any other news covered by the media, from the Tech Bubble, to ISIS, or Millenials. Long, but worthwhile.</br>I have been reading Baekdal for years. I can’t even remember how I ran into his blog, but it must have been 7 or 8 years ago, and I am glad I did.
While I have read (…skimmed 🙄) Mary Meeker’s report several years in a row by now, I had never consciously noticed the acceleration of adoption rates of new technologies.
Possibly more interesting than the opt-in model championed by Blendle.
Evans has a knack for finding great analogies from history. In most cases, path dependence, network effects, consumer lock in, and feedback loops matter more than any one decision. I wonder if we can systematically figure out the decisions that matter more…
Somehow, the dots connect in the future.
Was not expecting Uncle Bob to finish on that note. The history of programming languages is a big question mark for me. If you have a good book/blog post to recommend on it, please send it my way.
Ben sounds more bullish in this article than in the past few, especially Exponent.
Yet another bear case for Apple pinned on the cult of personality for Steve Jobs. While I disagree with the overall message, the writing is really good, and Lefsetz does have a point on the strategy of innovation, viz. Christensen’s disruptive innovation.
A good explanation of neural networks by example. It is amazing how quickly the toy problem of learning a couple of weights, basic high school math, becomes untractable.
Reminded me of Cesar Hidalgo’s book, Why Information Grows. At some point info HAS to be spread out across brains in the organization.
Most of modern economics is based on the idea that people make decisions with a clear understanding of the consequences. This couldn’t be further from the truth. Whether we’re talking of switching to a new job, moving to a different state, picking an insurance plan or making a donation, there are always economic consequences that people don’t understand. The complexity of our world, some of it designed, some of it emergent, makes rational decision-making almost impossible. These Uber employees were definitely not aware of how big of an issue this policy would be years after they joined the company. (For more on the topic, take a look at Zach Holman’s post.)
I don’t buy the bot craze. The technology is not there yet, and as the author well describes, the user experience feels just like calling a bank, or a telco, and being greeted by a distorted digital voice asking how one can be helped. Some day.
An oldie, but goodie. Someone should repeat this analysis and include 2015/2016 data. We’ve probably already crossed the 2x threshold.
One of those lists that invariably will be printed out, and pinned to a cube, by a grumpy coworker.
This reminded me of the Planet Money episode on CEO pay and how hard it is to actually measure how employees are compensanted.
I have been on the other side of the table of many interviews since I started working at Apple. It is unbelievably hard to gauge the skills of a front-end engineer, even more so when more than half the people involved in the interview process do back-end work day to day.
As is mentioned toward the end, “the most effective monopoly killer is the next monopoly.”
Sometimes, free is a problem.
To be honest, I haven’t finished reading this, but it was profusely recommended by randos on HN and coworkers alike. The preferred stack, and the JS framework du jour might have changed since then, but the basics are still the same. This essay tries to explain distributed systems fundamentals from “the log” up.
Even though I didn’t take a regex class, the similarities with my stochastic modeling class are stark. Now I want to learn more!
Building software is hard. Learn from others’ mistakes.
A little bit hyperbolic, I use Feedly and it works more than fine, but the internet definitely changed the day Google shut down Reader.
Long, but so worth it. As Paul Ford tweeted, this essay is “a great catalog of Silicon Valley self-deceptions.”
Everyone talks about “bots”, but “bots” are not new. Grover makes a great analogy between early iOS skeumorphism and the metaphors of “conversational UI” that have leaked into these new user experiences. He goes on to argue that the notification systems in modern operating systems are broken, which I fully agree with, and suggests the rise of meta-platforms like WeChat and Facebook Messenger as the path forward.
Everyone is talking about bots.
