Otis Health

Today we launched our newest PSL spinout, Otis Health.

In its first iteration, Otis offers a free discount pharmacy card to the underserved 1099 worker market. A shocking percentage of contract workers have no insurance whatsoever; saving even a handful of dollars on medications can make a meaningful difference. Otis can often save much more than that.

Otis Health: as easy as 1-2-3

I’m excited about Otis on three fronts. First, it brings a modern design and user experience to a market that until today has sorely lacked it. Second, Otis’ discount card is free to use; all the economic magic happens behind the scenes, in the form of complex contracts between retail chains, benefits managers, distributors, and manufacturers. Finally, Otis has its eyes firmly fixed on several adjacent services that we think will also meaningfully improve the lives of 1099 workers in the future.

Oh, and one more (the most important!) reason to be excited: the team. It’s been a blast working with Aaron, Luke, Sanford, Sharon, and Steve to get this thing out the door.

Craig Hockenberry, writing on his long-lived personal blog:

Well, it happened.

We knew it was coming.

A prick pulled the plug.

Over the weekend, Tweetbot, Twitterrific, and every other popular third-party Twitter client was unceremoniously banned. It’s a stupid petty move on Twitter’s part, executed in an impressively stupid petty way. I imagine it’s the final nail in the coffin for several high-profile Twitter hangers-on.

Most of the people I follow, though? They’re long gone.

Ran across a software blog post that made me feel, well, old:

In traditional web applications, web pages are rendered on the client side. The browser receives a blob of JavaScript from the server, processes it, and paints the UI that the user sees.

This is not the “tradition” I grew up with!

(It’s also not a “tradition” I’ve ever particularly loved.)

Me, five weeks ago:

For me, it’s not really about Elon.

Musk, yesterday:

My pronouns are Prosecute/Fauci

Yeah, well, I take it back. It is about Elon. Once upon a time, Twitter was fun. It’s a shame a midwit troll had to come along and wreck the party.

I suppose all things must end. Onward.

Phase Transitions

:: musings

GPT-3 shipped two years ago. Its capabilities, and that of descendant language models like OpenAI Codex, astonished me on day one; two years later, I’m still just as astonished.

Earlier this week OpenAI announced ChatGPT, a new variant intended to be used in interactive dialogue. With ChatGPT I find myself astonished all over again.

One delightful discovery is that back-and-forth conversation is a good way to build code. It’s a form of literate programming that Knuth probably never imagined.

I paid for GitHub Copilot the moment I could. Copilot, which builds on top of Codex, is more than just astonishing: it’s useful. Yet, as impressive as Copilot is, playing with ChatGPT makes it clear that Copilot has the potential to do vastly more even today.

The Internet has done its work and there are too many fun ChatGPT code samples to choose from. The most compelling examples refine code just by talking it over. There are also countless short examples that might have been accomplished with the previous generation of Codex or GPT-3 but that seem to have renewed potency today, like explaining a bug or exploiting a buffer overflow. But if I were to highlight just one example that seems to capture the moment, it might be this complete absurdity from Riley Goodside:

Wise guys get wise to big-O

Computers pretending to be gangsters with a knack for complexity theory. That is where we’re at today.

We’re at one of those handful of moments when our industry undergoes a deep and lasting phase transition. It’s easy to draw parallels with previous transitions like the advent of the Web in 1991. Then, as now, a new technology was introduced that collected recent advances into a package that felt wholly new. Even in its first version, that new technology was instantly useful in spite of its obvious flaws. It was easy to imagine a long road of improvements ahead. Most of all: people couldn’t look away. The Web struck like lightning. Large language models? Much the same.

Having said this, there’s also something that feels entirely different to me about this moment. We’re playing with language. Language is primal. It is quintessentially human. It is fire. It’s no accident that GPT-3 was built by an organization whose stated ambition is to develop the world’s first artificial general intelligence.

What lies on the other side of this transition? I don’t know; until we get there, I’ll have to content myself with those fast-talkin’ wise guys. Hopefully they can teach me another thing or two about computer programming along the way.

:: audio

It’s snowing outside. I decide to listen to A Charlie Brown Christmas. A bit early, but still: snow!

At the same time, I’m playing with GPT-3’s new text-davinci-003 model. It’s impressive.

A couple weeks ago, Adam and I tried to get GPT-3 to spit out chord progressions. Today’s updated GPT-3 seems pretty good: sure, some of my prompts result in sonic (or textual) mayhem, but many more result in ii-V-I and other legible changes.

I punch in an oddball prompt:

Give me the chords to a straight-ahead jazz reharmonization of Erik Satie's Gymnopedie No. 1. A simple list will do.

GPT-3 replies:

Ebmaj7 - Bbmaj7 - Ebmaj7 - Bbmaj7 - Cm7 - Fm7 - Gm7 - Bb7 - Eb7 - F7

Okay, those first repeating chords make some sense; I can tack a melody to that. The next are a bit mysterious, but I give it a go and eventually find a way to make them fit. I toy with chromatic approaches while Vince Guaraldi sinks in and somehow end up with… well, “Gymnopedie No. GPT-3” I suppose.

I’m taking a break from Twitter.

My usage tailed off a while ago when I realized that my old-school RSS reader was once again both more valuable and more joyful. Blogs have had quite the resurgence in the past three or four years; I want to be a part of that!

For me, it’s not really about Elon. The timing just feels right.

Fancy Tree Screenshot

My 7yo spends a lot of time making fun programs in Tynker. Most of them involve animated cats. She’s a true self-directed learner but every once in a while I get to share a new idea. This weekend it was recursion. We decided to make it “visible” by implementing a simple tree drawing toy. (Later, I went back and made a “fancy” variant.)

In case it’s not clear from my previous post, I’m an unrepentant crypto bear. At the same time, I’m fascinated by crypto’s culture and by its technical edifices: great walls of complex code all in service of… well, I’m not sure what, exactly.

One thing I haven’t done is backstop my bearishness with a financial position. Thankfully, I can live vicariously! Paul Butler’s rationale for and approach to shorting bitcoin by shorting publicly traded miners is a breath of fresh air.

Down the Crypto Rabbit Hole

:: musings

Crypto is a wild mix of culture, code, and capitalism. Its proponents speak of “going down the rabbit hole” in a positive way, as if a fundamental truth awaits on the other side. Crypto’s rabbit hole is deep, yes, but in my view it is full not of pleasant truths, but of distressing surprises that seem to animate the surrounding chaos.

At the surface, crypto’s “culture” feels both youthful and vibrant. I’m reminded of the early days of the web, when sites were weird and creators built without constraint. Then as now, nobody quite knew which way the industry’s winds blew; they built anyway. Crypto is the center of a new design trend that hearkens back to Space Jam, bringing its aesthetics into a technotronic future. It’s home to new writing and criticism that feels like the work of whip-smart semiotics majors. Like the early web, there’s lofty rhetoric about crypto’s utopian potential. New social clubs seem as enthusiastic about throwing underground raves in Paris as they are with the market value of their tokens.

This bizarre emerging culture arrives with what seems to me to be a giant asterisk. I think @pinboard said it best when he described crypto as “an unregulated casino with a hip bar scene”. He continued: “there’s nothing morally neutral about the criminality at the heart of the endeavor”. Every big-time speculator, punter, grifter, money launderer, and ransomware bandit in the world is hard at work in the casino. No matter how literate the bar scene, it’s the fruit of a poison tree.

Just inside the crypto rabbit hole, we find a genuinely new and expressive culture emerging from the grimy bits of unregulated capitalism run amok.

Code animates the crypto ecosystem; its more starry-eyed believers claim that code is all that matters. And, to be sure, there is very interesting code behind crypto. A dozen years ago, Bitcoin introduced the world to a new form of distributed consensus. Half a decade later, Ethereum proved the viability of smart contract programming. Since then, algorithmic advancements have led to low-cost high-throughput chains. Emerging financial protocols on top of blockchains — MakerDAO, which creates a dollar-stable asset through collateralization; Uniswap, an exchange without an order book; and Compound, a decentralized interest rate market — all have innovative technical and economic underpinnings. (Are they long-term valuable underpinnings? I admit my skepticism.)

The technical history of the Internet is, in part, the history of the birth, adoption, and stewardship of distributed protocols by its broader community. Blockchains follow in this tradition but also depart radically from it: they are the first protocols to arrive with an asset class attached. Protocols like SMTP and HTTP created immense value for the world but captured little for their inventors; blockchains and the protocols built on top of them upset this balance, allowing inventors to capture considerable value for themselves. Historically successful protocols typically see slow early adoption; crypto’s new protocols break this mold by nearly requiring substantial up-front speculation (or wise investment!) in order to achieve escape velocity. As a result, it’s alarmingly easy to launch systems that look indistinguishable from Ponzi schemes or multi-level marketing.

Midway down the crypto rabbit hole, we find a technically intriguing class of Internet protocols that upend the historical balance of value creation and capture, leading to surprising and problematic new dynamics.

Ultimately, healthy economies need productive ends. While speculation almost certainly drives crypto’s outsize market cap today, it’s hard to ignore the community’s rapid experimentation. Perhaps crypto will never uncover true sources of value creation; perhaps there are none to be found. (That’s certainly my instinct at the moment!) Or perhaps the essential ingredients are already in the kitchen. At the heart of every crypto experiment lies the simple abstraction of tokens: marks on ledgers maintained by the network. Anyone can wave a “magic wand” and declare the existence of a new token that the world will honor merely by collective agreement. Of course, waving wands alone isn’t enough to create value. Yesterday, we experimented by attaching goofy images of punks and apes to our tokens. Today, we’re starting to staple metadata with complex structure. Tomorrow, perhaps, we’ll wrap our tokens with increasingly sophisticated code: code that grants permissions and access rights, code that defines and enforces behavior, and code that describes how to interact with crypto’s new payment rails. There’s an immense design space to explore; it may be too bearish to entirely dismiss its potential.

The collective agreement that makes crypto’s “magic wand” possible at all is, to me, a puzzle. By nature, digital content can be reproduced at zero marginal cost. Why is it that we’ve decided to recreate scarcity in the digital world? Yes, we’ve grappled with digital scarcity in limited domains before. Video games sell digital items; the appeal is easy to understand. Software phones home to check its license. Intellectual property itself is a form of manufactured digital scarcity. Yet crypto seems to throw these doors wide open. Perhaps this was inevitable. Perhaps the centuries we’ve spent building societies and economic systems around the unavoidable problem of physical scarcity makes digital scarcity feel natural to us even though it’s unnatural to information itself. Whatever the case, the deluge of capital that floods the crypto markets today practically guarantees that we’ll experiment with manufactured digital scarcity for quite some time to come.

Deep down the crypto rabbit hole, we see that while crypto might portend a revolution, at its heart is a simple reassertion of scarcity in the digital realm — an assertion that is by no means a foregone conclusion.

Where does crypto go from here? With so many cards — cultural, technical, economic, and regulatory — in the air, it’s impossible to predict its future trajectory. But the technology industry is immensely path dependent. Particularly when buckets of money appear, feedback loops can form whose outcomes seem all but inevitable. Speculators and venture capitalists alike have inundated crypto with cash. Blockchains may become the future only because their story was told, speculated on, invested in, and told some more. Or they may disappear quickly, in the bursting of speculative and fraudulent excess. Whatever drives us, if society decides to wander further down this road, we should expect to see the same unequal outcomes we see today merely reproduced in the digital realm. Despite the utopian rhetoric, economic power always concentrates: crypto may mint new winners, but the tune will stay the same.

Twenty years. I thought I might have something to say. It took some time to realize that, for me, the day hadn’t taken on a greater or lesser meaning in the intervening decades. What I wrote just one year later still feels about right.

He’s gone. We won’t have to wake up in the morning and wonder what nonsense, malice, or criminality he got up to in the meantime. I’m sure much will be said about him in the years to come but, today, I’m content to simply join America’s collective sigh of relief.

Four years ago, I wrote:

Trust strikes me as the far more insidious concern. Trust may have been eroding before Trump, but he willfully accelerated the process. I have no doubt that he will continue to sow distrust in our government and media institutions throughout his tenure. This is a poison that will linger, harming our country long after Trump is gone: depending on how far one travels, one may never quite return from the dangerous road of distrust.

Yesterday’s violent insurrection, or something like it, was written in the stars. What the road looks like from here, I can only guess.

Happy new year? I think so. It’s hard to imagine 2021 faring worse than 2020. But between the United States’ political instability and the arrival of the new more contagious coronavirus variant, I won’t be shocked if the first half of 2021 has some twists and turns in store.

Notes on the Apple + Google Contact Tracing Partnership

On Friday April 10, 2020, Apple and Google announced a partnership to provide new tools on top of which comprehensive at-scale digital contact tracing solutions can be built.

The primary contributions are a bluetooth and a cryptographic specification, plus the promise that these specifications will be implemented on tens of millions of mobile devices by very early May, 2020. I expect the number of supporting devices to reach the billions in the months following. Scale is essential in any successful tracing solution; as a result, any viable solution going forward will probably need to utilize these specifications. I’ll be surprised if any competing proposal achieves the necessary scale.

While their specifications are an important piece of the puzzle, Apple and Google have not built (and do not seem to want to build) a complete solution for digital contact tracing. Instead, they’ve focused on the low-level question of how mobile devices will interact with one another to exchange anonymized data that can — in tandem with both apps and data services presumably built by others — be tied back to an infection and scored based on time and distance of exposure. The details of the underlying protocols are not specific to COVID-19 and should provide a foundation for future epidemics.

The current specifications appear to strike a balance between privacy and anonymity and the need to share diagnostic information with arbitrary third parties. In the assumed common case where the mobile device’s owner remains healthy, no identifiable information of any kind is obtainable by any third party, including the operators of back-end data services and the developers of contact tracing applications. (Contact tracing applications can of course explicitly ask for PII and can share this information with data services, but the Apple + Google protocols themselves stay silent on this point.) On the other hand, in the assumed rare case where a mobile device’s owner gets sick, that owner voluntarily shares cryptographic identifiers associated with the specific days when they might have been contagious. With access to these identifiers, owners of mobile devices that were within Bluetooth range of the symptomatic individual can rank the severity of their exposure without the ability to determine the infected individual’s identity. In addition, it is not possible for data service providers to determine which set of users may be at risk; the information necessary to make this determination lives on, and never leaves, the at-risk mobile devices.

Because the Apple + Google partnership does not provide a contact tracing app or a contact tracing data service — and because these are necessary components of an at-scale solution — there are many open questions about how digital contact tracing will work in practice.

For instance: it is unclear who will be allowed to ship applications that use these new protocols. Will Apple and Google limit access to public entities, select private partners, or will they open the floodgates wide?

It’s also unclear who is likely to operate back-end data services in practice. The Apple + Google design naturally lends itself to the creation of federated rather than centralized data services. We might expect multiple or even competing services to emerge. To achieve scale, these services will need to speak with one another; with what schema and semantics will this conversation take place?

Griefing is also an important consideration in the development of apps and data services. If anybody can press a button that says “I have COVID-19” then anybody will, including the uninfected. Apps and services may need to place hard restrictions on who can share what the protocol calls “diagnostic keys”. As a simple example, an app may allow an individual to share their diagnostic keys with their doctor but only allow authorized medical professionals to share the diagnostic keys with participating data services.

There are many other important factors to consider. On the technical front, well-known cryptographers have begun to ask pointed questions about the chosen cryptographic scheme and its real-world privacy considerations. On the privacy and policy front, there are many deep and complex issues to tackle. Perhaps the best discussion I’ve run across in the context of the United States comes from a recent Lawfare Podcast episode that dives deep on the question of whether contact tracing is a privacy threat.