Found 11 bookmarks
Newest
How Elon Musk Got Tangled Up in Blue
How Elon Musk Got Tangled Up in Blue
Mr. Musk had largely come to peace with a price of $100 a year for Blue. But during one meeting to discuss pricing, his top assistant, Jehn Balajadia, felt compelled to speak up. “There’s a lot of people who can’t even buy gas right now,” she said, according to two people in attendance. It was hard to see how any of those people would pony up $100 on the spot for a social media status symbol. Mr. Musk paused to think. “You know, like, what do people pay for Starbucks?” he asked. “Like $8?” Before anyone could raise objections, he whipped out his phone to set his word in stone. “Twitter’s current lords & peasants system for who has or doesn’t have a blue checkmark is bullshit,” he tweeted on Nov. 1. “Power to the people! Blue for $8/month.”
·nytimes.com·
How Elon Musk Got Tangled Up in Blue
What Apple's AI Tells Us: Experimental Models⁴
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.
·oneusefulthing.org·
What Apple's AI Tells Us: Experimental Models⁴
Muse retrospective by Adam Wiggins
Muse retrospective by Adam Wiggins
  • Wiggins focused on storytelling and brand-building for Muse, achieving early success with an email newsletter, which helped engage potential users and refine the product's value proposition.
  • Muse aspired to a "small giants" business model, emphasizing quality, autonomy, and a healthy work environment over rapid growth. They sought to avoid additional funding rounds by charging a prosumer price early on.
  • Short demo videos on Twitter showcasing the app in action proved to be the most effective method for attracting new users.
Muse as a brand and a product represented something aspirational. People want to be deeper thinkers, to be more strategic, and to use cool, status-quo challenging software made by small passionate teams. These kinds of aspirations are easier to indulge in times of plenty. But once you're getting laid off from your high-paying tech job, or struggling to raise your next financing round, or scrambling to protect your kids' college fund from runaway inflation and uncertain markets... I guess you don't have time to be excited about cool demos on Twitter and thoughtful podcasts on product design.
I’d speculate that another factor is the half-life of cool new productivity software. Evernote, Slack, Notion, Roam, Craft, and many others seem to get pretty far on community excitement for their first few years. After that, I think you have to be left with software that serves a deep and hard-to-replace purpose in people’s lives. Muse got there for a few thousand people, but the economics of prosumer software means that just isn’t enough. You need tens of thousands, hundreds of thousands, to make the cost of development sustainable.
We envisioned Muse as the perfect combination of the freeform elements of a whiteboard, the structured text-heavy style of Notion or Google Docs, and the sense of place you get from a “virtual office” ala group chat. As a way to asynchronously trade ideas and inspiration, sketch out project ideas, and explore possibilities, the multiplayer Muse experience is, in my honest opinion, unparalleled for small creative teams working remotely.
But friction began almost immediately. The team lead or organizer was usually the one bringing Muse to the team, and they were already a fan of its approach. But the other team members are generally a little annoyed to have to learn any new tool, and Muse’s steeper learning curve only made that worse. Those team members would push the problem back to the team lead, treating them as customer support (rather than contacting us directly for help). The team lead often felt like too much of the burden of pushing Muse adoption was on their shoulders. This was in addition to the obvious product gaps, like: no support for the web or Windows; minimal or no integration with other key tools like Notion and Google Docs; and no permissions or support for multiple workspaces. Had we raised $10M back during the cash party of 2020–2021, we could have hired the 15+ person team that would have been necessary to build all of that. But with only seven people (we had added two more people to the team in 2021–2022), it just wasn’t feasible.
We neither focused on a particular vertical (academics, designers, authors...) or a narrow use case (PDF reading/annotation, collaborative whiteboarding, design sketching...). That meant we were always spread pretty thin in terms of feature development, and marketing was difficult even over and above the problem of explaining canvas software and digital thinking tools.
being general-purpose was in its blood from birth. Part of it was maker's hubris: don't we always dream of general-purpose tools that will be everything to everyone? And part of it was that it's truly the case that Muse excels at the ability to combine together so many different related knowledge tasks and media types into a single, minimal, powerful canvas. Not sure what I would do differently here, even with the benefit of hindsight.
Muse built a lot of its reputation on being principled, but we were maybe too cautious to do the mercenary things that help you succeed. A good example here is asking users for ratings; I felt like this was not to user benefit and distracting when the user is trying to use your app. Our App Store rating was on the low side (~3.9 stars) for most of our existence. When we finally added the standard prompt-for-rating dialog, it instantly shot up to ~4.7 stars. This was a small example of being too principled about doing good for the user, and not thinking about what would benefit our business.
Growing the team slowly was a delight. At several previous ventures, I've onboard people in the hiring-is-job-one environment of a growth startup. At Muse, we started with three founders and then hired roughly one person per year. This was absolutely fantastic for being able to really take our time to find the perfect person for the role, and then for that person to have tons of time to onboard and find their footing on the team before anyone new showed up. The resulting team was the best I've ever worked on, with minimal deadweight or emotional baggage.
ultimately your product does have to have some web presence. My biggest regret is not building a simple share-to-web function early on, which could have created some virality and a great deal of utility for users as well.
In terms of development speed, quality of the resulting product, hardware integration, and a million other things: native app development wins.
After decades working in product development, being on the marketing/brand/growth/storytelling side was a huge personal challenge for me. But I feel like I managed to grow into the role and find my own approach (podcasting, demo videos, etc) to create a beacon to attract potential customers to our product.
when it comes time for an individual or a team to sit down and sketch out the beginnings of a new business, a new book, a new piece of art—this almost never happens at a computer. Or if it does, it’s a cobbled-together collection of tools like Google Docs and Zoom which aren’t really made for this critical part of the creative lifecycle.
any given business will find a small number of highly-effective channels, and the rest don't matter. For Heroku, that was attending developer conferences and getting blog posts on Hacker News. For another business it might be YouTube influencer sponsorships and print ads in a niche magazine. So I set about systematically testing many channels.
·adamwiggins.com·
Muse retrospective by Adam Wiggins
Generative AI’s Act Two
Generative AI’s Act Two
This page also has many infographics providing an overview of different aspects of the AI industry at time of writing.
We still believe that there will be a separation between the “application layer” companies and foundation model providers, with model companies specializing in scale and research and application layer companies specializing in product and UI. In reality, that separation hasn’t cleanly happened yet. In fact, the most successful user-facing applications out of the gate have been vertically integrated.
We predicted that the best generative AI companies could generate a sustainable competitive advantage through a data flywheel: more usage → more data → better model → more usage. While this is still somewhat true, especially in domains with very specialized and hard-to-get data, the “data moats” are on shaky ground: the data that application companies generate does not create an insurmountable moat, and the next generations of foundation models may very well obliterate any data moats that startups generate. Rather, workflows and user networks seem to be creating more durable sources of competitive advantage.
Some of the best consumer companies have 60-65% DAU/MAU; WhatsApp’s is 85%. By contrast, generative AI apps have a median of 14% (with the notable exception of Character and the “AI companionship” category). This means that users are not finding enough value in Generative AI products to use them every day yet.
generative AI’s biggest problem is not finding use cases or demand or distribution, it is proving value. As our colleague David Cahn writes, “the $200B question is: What are you going to use all this infrastructure to do? How is it going to change people’s lives?”
·sequoiacap.com·
Generative AI’s Act Two
Seven Rules For Internet CEOs To Avoid Enshittification
Seven Rules For Internet CEOs To Avoid Enshittification
People forget that when Bezos introduced Amazon Prime, Wall St. flipped out, because they insisted that it would cost way too much for too little benefit. But, through it all Amazon survived (and thrived) because Bezos just kept telling investors exactly what his plan was, and never backed down, no matter what Wall St. kept saying to him.
This is too easily forgotten, but your users are everything if you run an internet business. They’re not “the product.” They’re what makes your site useful and valuable, and often provide the best marketing you could never buy by convincing others to join and providing you with all of the best ideas on how to improve things and make your service even better for the users. The moment you’re undermining your own community, you’re beginning to spiral downward.
As you’re developing a business model, the best way to make sure that you’re serving your users best, and not enshittifying everything, is to constantly make sure that you’re only capturing some of the value you’re creating, and are instead putting much more out into the world, especially for your community.
Push the power to make your service better out from the service to the users themselves and watch what they do. Let them build. Let them improve your service. Let them make it work better for you. But, you have to have some trust here. If you’re focused on “Rule 3” you have to recognize that sometimes your users will create value that you don’t capture. Or even that someone else captures. But in the long run, it still flows back to you, as it makes your service that much more valuable.
If you’re charging for something that was once free, you’re taking away value from your community. You’re changing the nature of the bargain, and ripping away the trust that your community put in you. Instead, always look for something new that is worth paying for above and beyond what you already offered.
There are ways to monetize that don’t need to overwhelm, that don’t need to suck up every bit of data, that don’t need to rely on taking away features users relied on. Focus on adding more scarce value, and figuring out ways to charge for those new things which can’t be easily replicated.
You start learning acronyms like “ARPU” (average revenue per user) and such. And then you’re being measured on how much you’re increasing those metrics, which means you need to squeeze more out of each individual user, and you’re now deep within the enshittification stage, in which you’re trying to squeeze your users for more money each quarter (because now everything is judged in how well you did in the last 3 months to improve that number).
·techdirt.com·
Seven Rules For Internet CEOs To Avoid Enshittification
Leviathan Wakes: the case for Apple's Vision Pro - Redeem Tomorrow
Leviathan Wakes: the case for Apple's Vision Pro - Redeem Tomorrow
The existing VR hardware has not received sufficient investment to fully demonstrate the potential of this technology. It is unclear whether the issues lie with augmented reality (AR) itself or the technology used to deliver it. However, Apple has taken a different approach by investing significantly in creating a serious computer with an optical overlay as its primary interface. Unlike other expensive headsets, Apple has integrated the ecosystem to make it appealing right out of the box, allowing users to watch movies, view photos, and run various apps. This comprehensive solution aims to address the uncertainties surrounding AR. The display quality is top-notch, finger-based interaction replaces clunky joysticks, and performance is optimized to minimize motion sickness. Furthermore, a large and experienced developer community stands ready to create apps, supported by mature tools and extensive documentation. With these factors in place, there is anticipation for a new paradigm enabled by a virtually limitless monitor. The author expresses eagerness to witness how this technology unfolds.
What can you do with this thing? There’s a good chance that, whatever killer apps may emerge, they don’t need the entire complement of sensors and widgets to deliver a great experience. As that’s discovered, Apple will be able to open a second tier in this category and sell you a simplified model at a lower cost. Meanwhile, the more they manufacture the essentials—high density displays, for example—the higher their yields will become, the more their margins will increase. It takes time to perfect manufacturing processes and build up capacity. Vision Pro isn’t just about 2024’s model. It’s setting up the conditions for Apple to build the next five years of augmented reality wearable technology.
VR/AR doesn’t have to suck ass. It doesn’t have to give you motion sickness. It doesn’t have to use these awkward, stupid controllers you accidentally swap into the wrong hand. It doesn’t have to be fundamentally isolating. If this paradigm shift could have been kicked off by cheap shit, we’d be there already. May as well pursue the other end of the market.
what starts as clunky needn’t remain so. As the technology for augmented reality becomes more affordable, more lightweight, more energy efficient, more stylish, it will be more feasible for more people to use. In the bargain, we’ll get a display technology entirely unshackled from the constraints of a monitor stand. We’ll have much broader canvases subject to the flexibility of digital creativity, collaboration and expression. What this unlocks, we can’t say.
·redeem-tomorrow.com·
Leviathan Wakes: the case for Apple's Vision Pro - Redeem Tomorrow
Tiktok’s enshittification (21 Jan 2023) – Pluralistic: Daily links from Cory Doctorow
Tiktok’s enshittification (21 Jan 2023) – Pluralistic: Daily links from Cory Doctorow
it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a "two sided market," where a platform sits between buyers and sellers, holding each hostage to the other, raking off an ever-larger share of the value that passes between them.
Today, Marketplace sellers are handing 45%+ of the sale price to Amazon in junk fees. The company's $31b "advertising" program is really a payola scheme that pits sellers against each other, forcing them to bid on the chance to be at the top of your search.
Search Amazon for "cat beds" and the entire first screen is ads, including ads for products Amazon cloned from its own sellers, putting them out of business (third parties have to pay 45% in junk fees to Amazon, but Amazon doesn't charge itself these fees).
This is enshittification: surpluses are first directed to users; then, once they're locked in, surpluses go to suppliers; then once they're locked in, the surplus is handed to shareholders and the platform becomes a useless pile of shit.
This made publications truly dependent on Facebook – their readers no longer visited the publications' websites, they just tuned into them on Facebook. The publications were hostage to those readers, who were hostage to each other. Facebook stopped showing readers the articles publications ran, tuning The Algorithm to suppress posts from publications unless they paid to "boost" their articles to the readers who had explicitly subscribed to them and asked Facebook to put them in their feeds.
Today, Facebook is terminally enshittified, a terrible place to be whether you're a user, a media company, or an advertiser. It's a company that deliberately demolished a huge fraction of the publishers it relied on, defrauding them into a "pivot to video" based on false claims of the popularity of video among Facebook users. Companies threw billions into the pivot, but the viewers never materialized, and media outlets folded in droves:
These videos go into Tiktok users' ForYou feeds, which Tiktok misleadingly describes as being populated by videos "ranked by an algorithm that predicts your interests based on your behavior in the app." In reality, For You is only sometimes composed of videos that Tiktok thinks will add value to your experience – the rest of the time, it's full of videos that Tiktok has inserted in order to make creators think that Tiktok is a great place to reach an audience.
"Sources told Forbes that TikTok has often used heating to court influencers and brands, enticing them into partnerships by inflating their videos’ view count.
"Monetize" is a terrible word that tacitly admits that there is no such thing as an "Attention Economy." You can't use attention as a medium of exchange. You can't use it as a store of value. You can't use it as a unit of account. Attention is like cryptocurrency: a worthless token that is only valuable to the extent that you can trick or coerce someone into parting with "fiat" currency in exchange for it.
The algorithm creates conditions for which the necessity of ads exists
For Tiktok, handing out free teddy-bears by "heating" the videos posted by skeptical performers and media companies is a way to convert them to true believers, getting them to push all their chips into the middle of the table, abandoning their efforts to build audiences on other platforms (it helps that Tiktok's format is distinctive, making it hard to repurpose videos for Tiktok to circulate on rival platforms).
every time Tiktok shows you a video you asked to see, it loses a chance to show you a video it wants you to se
I just handed Twitter $8 for Twitter Blue, because the company has strongly implied that it will only show the things I post to the people who asked to see them if I pay ransom money.
Compuserve could have "monetized" its own version of Caller ID by making you pay $2.99 extra to see the "From:" line on email before you opened the message – charging you to know who was speaking before you started listening – but they didn't.
Useful idiots on the right were tricked into thinking that the risk of Twitter mismanagement was "woke shadowbanning," whereby the things you said wouldn't reach the people who asked to hear them because Twitter's deep state didn't like your opinions. The real risk, of course, is that the things you say won't reach the people who asked to hear them because Twitter can make more money by enshittifying their feeds and charging you ransom for the privilege to be included in them.
Individual product managers, executives, and activist shareholders all give preference to quick returns at the cost of sustainability, and are in a race to see who can eat their seed-corn first. Enshittification has only lasted for as long as it has because the internet has devolved into "five giant websites, each filled with screenshots of the other four"
policymakers should focus on freedom of exit – the right to leave a sinking platform while continuing to stay connected to the communities that you left behind, enjoying the media and apps you bought, and preserving the data you created
technological self-determination is at odds with the natural imperatives of tech businesses. They make more money when they take away our freedom – our freedom to speak, to leave, to connect.
even Tiktok's critics grudgingly admitted that no matter how surveillant and creepy it was, it was really good at guessing what you wanted to see. But Tiktok couldn't resist the temptation to show you the things it wants you to see, rather than what you want to see.
·pluralistic.net·
Tiktok’s enshittification (21 Jan 2023) – Pluralistic: Daily links from Cory Doctorow
Social media is doomed to die
Social media is doomed to die
“We want the chronological feed back!” Instagram users scream into the void. “Here, have Reels and Shopping,” said Instagram’s CEO, on the hunt for new revenue streams.“We want freedom of speech!” tweet the denizens of Twitter. “But then our sponsored hashtags won’t be brand safe,” said Twitter’s CEO (whoever that is this week).
·theverge.com·
Social media is doomed to die