Language is primarily a tool for communication rather than thought
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I Will Fucking Piledrive You If You Mention AI Again — Ludicity
Fast Crimes at Lambda School
Arc Browser is a Fantastic Browser. I Can't Recommend It. Ever.
The human cost of an Apple update
Dating apps don’t work, and meeting people in person seems foreign, even impossible. But it was dating apps that drove IRL connections nearly extinct. In other words, dating apps did work, for almost a decade, by promising to cut out all the things about in-person dating that made us feel vulnerable or uncomfortable. Rejection now happens with a swipe, out of sight, with neither party the wiser. If you match and then change your mind, you can just unmatch without explanation.
This arc plays out across all kinds of apps, and all kinds of human relationships, as tech companies seek to find and solve every type of “friction” and discomfort. But those efforts are rooted in the mistaken idea that being a person shouldn’t come with difficult emotions—that we aren’t often, in fact, served by hard conversations or uncomfortable feelings.
Useful and Overlooked Skills
A diplomatic “no” is when you’re clear about your feelings but empathetic to how the person on the receiving end might interpret those feelings.
What Is Going On With Next-Generation Apple CarPlay?
I’d posit that a reason why people love CarPlay so much is because the media, communication, and navigation experiences have traditionally been pretty poor. CarPlay supplants those, and it does so with aplomb because people use those same media, communication, and navigation features that are personalized to them with their phones when they’re not in their cars.
No one is walking around with a speedometer and a tachometer on their iPhone that need to have a familiar look and feel, rendered exclusively in San Francisco.
As long as automakers supply the existing level of CarPlay support, which isn’t a given, then customers like us would be content with the status quo, or even a slight improvement.
In my humble opinion, Next-Gen CarPlay is dead on arrival. Too late, too complicated, and it doesn’t solve the needs of automakers or customers.
Instead of letting the vehicle’s interface peak through, Apple should consider letting CarPlay peak through for the non-critical systems people prefer to use with CarPlay.
Design a CarPlay that can output multiple display streams (which Apple already over-designed) and display that in the cluster. Integrate with the existing controls for managing the interfaces in the vehicle. When the phone isn’t there, the vehicle will still be the same vehicle. When the phone is there, it’s got Apple Maps right in the cluster how you like it without changing the gauges, or the climate controls, or where the seat massage button is.
The everyday irritations people have are mundane, practical, and are not related to how Apple-like their car displays can look.
ivanreese/visual-programming-codex: Waypoints to the past and future of visual programming.
Niche InternetThe best WWDC videos about interface design
We've spent billions to fix our medical records, and they're still a mess. Here's why.
Despite the U.S. government spending billions to digitize medical records through the HITECH Act, the system remains fragmented, with doctors unable to easily exchange patient information across different practices and hospitals. This is largely due to a lack of interoperability between the proprietary software of electronic health record (EHR) vendors like Epic Systems. Epic has grown into the leading EHR vendor, but its software doesn't readily connect with competing systems, hindering the original goals of digitization. Patients are hurt by this inability to ensure their complete records are accessible to all their doctors. While Epic says it supports data sharing, it has charged additional fees and allegedly engaged in information blocking. The government has started pushing back on Epic's practices, but with many hospitals deeply invested in Epic's system, the issues persist, and the promised cost savings and benefits of EHRs have yet to fully materialize.
A 2014 RAND report singled out Epic as a roadblock to interoperability. With the company’s rise, researchers wrote, came an increasingly walled-off system. “By subsidizing ‘where the industry is’ rather than where it needed to go,” the report said, the government propped up an EHR market “that did not have the level of connectivity envisioned by the authors of the HITECH Act.”
In terms of bringing digital records to practices across the country, the HITECH Act has unquestionably succeeded: The percentage of US hospitals using digital records skyrocketed from 9.4 to 75.5 percent between 2008 and 2014. But the HITECH Act didn’t prioritize “interoperability”—the ability to transfer a medical file from one hospital to another. Unless programmers ensure that their system properly integrates with another, a doctor’s computer might spit out something akin to emoticons when queried for key test results.
Epic does work with hospitals and practices to link its system with competing ones, but it usually charges top dollar to do so.
A recent study by the American Medical Association and the online network AmericanEHR Partners found that 43 percent of physicians thought their software actually made their jobs more difficult. Doctors are investing the time to input data, but their offices are still having to fax and mail records like they did a decade ago. Less than 10 percent of hospitals say they’ve been able to trade records entirely through their digital systems.
All together, it’s like the Microsoft Office of health care software—more comprehensive than any of its competitors, even if its individual components are kind of meh.
“What you hear is that, if you were to buy the best of breed—the best cardiology system, or the best chemotherapy system—no one would ever choose Epic,” says Julia Adler-Milstein, a University of Michigan researcher who studies health care IT. As it stands, she says, using Epic is easier than trying to piece together better options from various software vendors. On top of that, Epic will tailor each installation on-site to a customer’s specific needs. What it doesn’t have—and ditto systems created by competitors Cerner and Meditech, the other bigwigs in EHR—is a framework to connect to other facilities using competing EHR systems.
Epic is probably here to stay, especially given the incredible investments hospitals have made to implement its system—Duke University, for example, reportedly spent $700 million on its Epic installation. That doesn’t mean Americans have to accept the status quo. According to Adler-Milstein, the University of Michigan researcher, “What we can do is force them to open up their system a little more, so that it plays better with others.” She hopes increased scrutiny pushes the company to publish its API—the code that lets others access information in its system—to allow other firms to build more user-friendly software.
Luma Dream Machine
text to video AI generator
What Is the Best Way to Cut an Onion?
As it turns out, cutting radially is, in fact, marginally worse than the traditional method. With all your knife strokes converging at a single central point, the thin wedges of onion that you create with your first strokes taper drastically as they get toward the center, resulting in large dice cut from the outer layers and much larger dice from the center. But even the classic method doesn’t produce particularly even dice, with a standard deviation of about 48 percent.
For the next set of simulations, I wondered what would happen if, instead of making radial cuts with the knife pointed directly at the circle’s center, we aimed our knife at an imaginary point somewhere below the surface of the cutting board, producing cuts somewhere between perfectly vertical and completely radial.
This proved to be key. By plotting the standard deviation of the onion pieces against the point below the cutting board surface at which your knife is aimed, Dr. Poulsen produced a chart that revealed the ideal point to be exactly .557 onion radiuses below the surface of the cutting board. Or, if it’s easier: Angle your knife toward a point roughly six-tenths of an onion’s height below the surface of the cutting board. If you want to be even more lax about it, making sure your knife isn’t quite oriented vertically or radially for those initial cuts is enough to make a measurable difference in dice evenness.
‘We cannot simply go, go, go.’ What is girl mossing, the wellness trend that rejects hustle culture?
Girl mossing recognises a need to step away from the pressures of modern, urban life, promoting spending time in nature as a restorative practice.
The fast pace and pressure of neoliberal capitalism take an enormous toll on wellbeing: not just personal, but social and planetary. These pressures are most acutely felt by women – whose labour remains, in large part, undervalued and underpaid – and by young people, who are often in precarious work, priced out of the housing market. Yet they’re still bombarded with images of unattainable success on social media. Not so the moss selfies.
Girl rotting is another subversive form of rest and retreat, focused on being intentionally “unproductive” at home.
In China, there’s a parallel rise in “tangping/lying flat” among Chinese young people who are “rejecting high-pressure jobs” in favour of a “low-pressure life”, and in “bai lan” (letting things rot), “a voluntary retreat” from pursuing goals that are now seen as “too difficult to achieve”.
We typically strive for material rewards through hard work and achieve success through doing.
We celebrate the “wins”: the promotion, the new house, marriage, the birth of children. By contrast, we really struggle “when things fall apart”, as they inevitably do, particularly when we are confronted with old age, sickness, and death – basically, with human decomposition.
Spreadsheet Assassins | Matthew King
Rhe real key to SaaS success is often less about innovative software and more about locking in customers and extracting maximum value. Many SaaS products simply digitize spreadsheet workflows into proprietary systems, making it difficult for customers to switch. As SaaS proliferates into every corner of the economy, it imposes a growing "software tax" on businesses and consumers alike. While spreadsheets remain a flexible, interoperable stalwart, the trajectory of SaaS points to an increasingly extractive model prioritizing rent-seeking over genuine productivity gains.
As a SaaS startup scales, sales and customer support staff pay for themselves, and the marginal cost to serve your one-thousandth versus one-millionth user is near-zero. The result? Some SaaS companies achieve gross profit margins of 75 to 90 percent, rivaling Windows in its monopolistic heyday.
Rent-seeking has become an explicit playbook for many shameless SaaS investors. Private equity shop Thoma Bravo has acquired over four hundred software companies, repeatedly mashing products together to amplify lock-in effects so it can slash costs and boost prices—before selling the ravaged Franken-platform to the highest bidder.
In the Kafkaesque realm of health care, software giant Epic’s 1990s-era UI is still widely used for electronic medical records, a nuisance that arguably puts millions of lives at risk, even as it accrues billions in annual revenue and actively resists system interoperability. SAP, the antiquated granddaddy of enterprise resource planning software, has endured for decades within frustrated finance and supply chain teams, even as thousands of SaaS startups try to chip away at its dominance. Salesforce continues to grow at a rapid clip, despite a clunky UI that users say is “absolutely terrible” and “stuck in the 80s”—hence, the hundreds of “SalesTech” startups that simplify a single platform workflow (and pray for a billion-dollar acquihire to Benioff’s mothership). What these SaaS overlords might laud as an ecosystem of startup innovation is actually a reflection of their own technical shortcomings and bloated inertia.
Over 1,500 software startups are focused on billing and invoicing alone. The glut of tools extends to sectors without any clear need for complex software: no fewer than 378 hair salon platforms, 166 parking management solutions, and 70 operating systems for funeral homes and cemeteries are currently on the market. Billions of public pension and university endowment dollars are being burned on what amounts to hackathon curiosities, driven by the machinations of venture capital and private equity. To visit a much-hyped “demo day” at a startup incubator like Y Combinator or Techstars is to enter a realm akin to a high-end art fair—except the objects being admired are not texts or sculptures or paintings but slightly nicer faces for the drudgery of corporate productivity.
As popular as SaaS has become, much of the modern economy still runs on the humble, unfashionable spreadsheet. For all its downsides, there are virtues. Spreadsheets are highly interoperable between firms, partly because of another monopoly (Excel) but also because the generic .csv format is recognized by countless applications. They offer greater autonomy and flexibility, with tabular cells and formulas that can be shaped into workflows, processes, calculators, databases, dashboards, calendars, to-do lists, bug trackers, accounting workbooks—the list goes on. Spreadsheets are arguably the most popular programming language on Earth.
On the necessity of a sin
AI excels at tasks that are intensely human: writing, ideation, faking empathy. However, it struggles with tasks that machines typically excel at, such as repeating a process consistently or performing complex calculations without assistance. In fact, it tends to solve problems that machines are good at in a very human way. When you get GPT-4 to do data analysis of a spreadsheet for you, it doesn’t innately read and understand the numbers. Instead, it uses tools the way we might, glancing at a bit of the data to see what is in it, and then writing Python programs to try to actually do the analysis. And its flaws — making up information, false confidence in wrong answers, and occasional laziness — also seem very much more like human than machine errors.
This quasi-human weirdness is why the best users of AI are often managers and teachers, people who can understand the perspective of others and correct it when it is going wrong.
Rather than focusing purely on teaching people to write good prompts, we might want to spend more time teaching them to manage the AI.
Telling the system “who” it is helps shape the outputs of the system. Telling it to act as a teacher of MBA students will result in a different output than if you ask it to act as a circus clown. This isn’t magical—you can’t say Act as Bill Gates and get better business advice or write like Hemingway and get amazing prose —but it can help make the tone and direction appropriate for your purpose.
What Apple's AI Tells Us: Experimental Models⁴
Companies are exploring various approaches, from large, less constrained frontier models to smaller, more focused models that run on devices. Apple's AI focuses on narrow, practical use cases and strong privacy measures, while companies like OpenAI and Anthropic pursue the goal of AGI.
the most advanced generalist AI models often outperform specialized models, even in the specific domains those specialized models were designed for. That means that if you want a model that can do a lot - reason over massive amounts of text, help you generate ideas, write in a non-robotic way — you want to use one of the three frontier models: GPT-4o, Gemini 1.5, or Claude 3 Opus.
Working with advanced models is more like working with a human being, a smart one that makes mistakes and has weird moods sometimes. Frontier models are more likely to do extraordinary things but are also more frustrating and often unnerving to use. Contrast this with Apple’s narrow focus on making AI get stuff done for you.
Every major AI company argues the technology will evolve further and has teased mysterious future additions to their systems. In contrast, what we are seeing from Apple is a clear and practical vision of how AI can help most users, without a lot of effort, today. In doing so, they are hiding much of the power, and quirks, of LLMs from their users. Having companies take many approaches to AI is likely to lead to faster adoption in the long term. And, as companies experiment, we will learn more about which sets of models are correct.
Carabiner Collection
a celebration of carabiners
BookFinder.com: New & Used Books, Rare Books, Textbooks
A really useful search engine for finding physical copies of hard-to-find books from lesser known retailers.
Math Encrypt: Convert Any Number to a Hard Math Equation
A site that generates complex equations equaling any input number, loved by the author for its creative potential uses.
SmallStack | Robin Taylor (he/him) | Substack
Bloggers on Blogging
A quaint, nostalgic blog collecting blogposts about blogging.
The Climate Reality Check
A "Bechdel test for the environment" tracking climate change depiction in media
Blog - Private Cloud Compute: A new frontier for AI privacy in the cloud - Apple Security Research
Explanation of how Apple guards user data and prevents their own access to it when processing for AI on their custom-built servers
Apple Intelligence is Right On Time
Summary
- Apple remains primarily a hardware company, and an AI-mediated future will still require devices, playing to Apple's strengths in design and integration.
- AI is a complement to Apple's business, not disruptive, as it makes high-performance hardware more relevant and could drive meaningful iPhone upgrade cycles.
- The smartphone is the ideal device for most computing tasks and the platform on which the future happens, solidifying the relevance of Apple's App Store ecosystem.
- Apple's partnership with OpenAI for chatbot functionality allows it to offer best-in-class capabilities without massive investments, while reducing the threat of OpenAI building a competing device.
- Building out the infrastructure for API-level AI features is a challenge for Apple, but one that is solvable given its control over the interface and integration of on-device and cloud processing.
- The only significant threat to Apple is Google, which could potentially develop differentiated AI capabilities for Android that drive switching from iPhone users, though this is uncertain.
- Microsoft's missteps with its Recall feature demonstrate the risks of pushing AI features too aggressively, validating Apple's more cautious approach.
- Apple's user-centric orientation and brand promise of privacy and security align well with the need to deliver AI features in an integrated, trustworthy manner.
When America was ‘great,’ according to data - The Washington Post
we looked at the data another way, measuring the gap between each person’s birth year and their ideal decade. The consistency of the resulting pattern delighted us: It shows that Americans feel nostalgia not for a specific era, but for a specific age.
The good old days when America was “great” aren’t the 1950s. They’re whatever decade you were 11, your parents knew the correct answer to any question, and you’d never heard of war crimes tribunals, microplastics or improvised explosive devices.
The closest-knit communities were those in our childhood, ages 4 to 7. The happiest families, most moral society and most reliable news reporting came in our early formative years — ages 8 through 11. The best economy, as well as the best radio, television and movies, happened in our early teens — ages 12 through 15.
almost without exception, if you ask an American when times were worst, the most common response will be “right now!”
This holds true even when “now” is clearly not the right answer. For example, when we ask which decade had the worst economy, the most common answer is today. The Great Depression — when, for much of a decade, unemployment exceeded the what we saw in the worst month of pandemic shutdowns — comes in a grudging second.
measure after measure, Republicans were more negative about the current decade than any other group — even low-income folks in objectively difficult situations.
Hsu and her friends spent the first part of 2024 asking 2,400 Americans where they get their information about the economy. In a new analysis, she found Republicans who listen to partisan outlets are more likely to be negative, and Democrats who listen to their own version of such news are more positive — and that Republicans are a bit more likely to follow partisan news.
Review of ‘The New Mutants’ (2020) ★★½
Alex Jones Seeks to Liquidate His Assets to Pay Damages to Sandy Hook Families
Culture Needs More Jerks | Defector
The function of criticism is and has always been to complicate our sense of beauty. Good criticism of music we love—or, occasionally, really hate—increases the dimensions and therefore the volume of feeling. It exercises that part of ourselves which responds to art, making it stronger.
The correction to critics’ failure to take pop music seriously is known as poptimism: the belief that pop music is just as worthy of critical consideration as genres like rock, rap or, god forbid, jazz. In my opinion, this correction was basically good. It’s fun and interesting to think seriously about music that is meant to be heard on the radio or danced to in clubs, the same way it is fun and interesting to think about crime novels or graphic design. For the critic, maybe more than for anyone else, it is important to remember that while a lot of great stuff is not popular, popular stuff can be great, too.
every good idea has a dumber version of itself on the internet. The dumb version of poptimism is the belief that anything sufficiently popular must be good. This idea is supported by certain structural forces, particularly the ability, through digitization, to count streams, pageviews, clicks, and other metrics so exactly that every artist and the music they release can be assigned a numerical value representing their popularity relative to everything else. The answer to the question “What do people like?” is right there on a chart, down to the ones digit, conclusively proving that, for example, Drake (74,706,786,894 lead streams) is more popular than The Weeknd (56,220,309,818 lead streams) on Spotify.
The question “What is good?” remains a matter of disagreement, but in the face of such precise numbers, how could you argue that the Weeknd was better? You would have to appeal to subjective aesthetic assessments (e.g. Drake’s combination of brand-checking and self-pity recreates neurasthenic consumer culture without transcending it) or socioeconomic context (e.g. Drake is a former child actor who raps about street life for listeners who want to romanticize black poverty without hearing from anyone actually affected by it, plus he’s Canadian) in a way that would ultimately just be your opinion. And who needs one jerk’s opinion when democracy is right there in the numbers?
This attitude is how you get criticism like “Why Normal Music Reviews No Longer Make Sense for Taylor Swift,” which cites streaming data (The Tortured Poets Department’s 314.5 million release-day streams versus Cowboy Carter’s 76.6 million) to argue that Swift is better understood not as a singer-songwriter but as an area of brand activity, along the lines of the Marvel Cinematic Universe or Star Wars. “The tepid music reviews often miss the fact that ‘music’ is something that Swift stopped selling long ago,” New Yorker contributor Sinéad O’Sullivan writes. “Instead, she has spent two decades building the foundation of a fan universe, filled with complex, in-sequence narratives that have been contextualized through multiple perspectives across eleven blockbuster installments. She is not creating standalone albums but, rather, a musical franchise.”
The fact that most cognitively normal adults regard these bands as children’s music is what makes their fan bases not just ticket-buyers but subcultures.
The power of the antagonist-subculture dynamic was realized by major record labels in the early 1990s, when the most popular music in America was called “alternative.”
For the person who is not into music—the person who just happens to be rapturously committed to the artists whose music you hear everywhere whether you want to or not, whose new albums are like iPhone releases and whose shows are like Disneyland—the critic is a foil.
Rank Apple
Make no mistake: this is a promotional exercise for Apple Music more than it is criticism. Sure, most lists of this type are also marketing for publications like Rolling Stone and Pitchfork and NME. Yet, for how tepid the opinions of each outlet often are, they have each given out bad reviews. We can therefore infer they have specific tastes and ideas about what separates great art from terrible art.
After Steve Jobs’ death came a river of articles questioning the internal culture he fostered, with several calling him an “asshole”. But that is mixing up a mean streak and a critical eye — Jobs, apparently, had both
It does not interrogate which albums are boring, expressionless, uncreative, derivative, inconsequential, inept, or artistically bankrupt. So why should we trust it to explain what is good? Apple’s ranking of albums lacks substance because it cannot say any of these things. Doing so would be a terrible idea for the company and for artists.
It is beyond my understanding why anyone seems to be under the impression this list is anything more than a business reminding you it operates a music streaming platform to which you can subscribe for eleven dollars per month.
Anti Trust in Tech
For years, poll after poll from around the world has found high levels of distrust in their influence, handling of private data, and new developments.
If these corporations were at all worried about this, they are not much showing it in their products — particularly the A.I. stuff they have been shipping. There has been little attempt at abating last year’s trust crisis. Google decided to launch overconfident summaries for a variety of search queries. Far from helping to sift through all that has ever been published on the web to mash together a representative summary, it was instead an embarrassing mess that made the company look ill prepared for the concept of satire. Microsoft announced a product which will record and interpret everything you do and see on your computer, but as a good thing.
why should we turn to them to fill gaps and needs in society? I certainly would not wish to indulge businesses which see themselves as entirely separate from the world.
These product introductions all look like hubris. Arrogance, really — recognition of the significant power these corporations wield and the lack of competition they face. Google can poison its search engine because where else are most people going to go? How many people would turn off Recall, something which requires foreknowledge of its existence, under Microsoft’s original rollout strategy?
There seems to be little attempt at persuasion. Instead, we are told to get on board because this rocket ship is taking off with or without us.