Who decided these features should go in the WWDC keynote, with a promise they’d arrive in the coming year, when, at the time, they were in such an unfinished state they could not be demoed to the media even in a controlled environment? Three months later, who decided Apple should double down and advertise these features in a TV commercial, and promote them as a selling point of the iPhone 16 lineup — not just any products, but the very crown jewels of the company and the envy of the entire industry — when those features still remained in such an unfinished or perhaps even downright non-functional state that they still could not be demoed to the press? Not just couldn’t be shipped as beta software. Not just couldn’t be used by members of the press in a hands-on experience, but could not even be shown to work by Apple employees on Apple-controlled devices in an Apple-controlled environment? But yet they advertised them in a commercial for the iPhone 16, when it turns out they won’t ship, in the best case scenario, until months after the iPhone 17 lineup is unveiled?

“Can anyone tell me what MobileMe is supposed to do?” Having received a satisfactory answer, he continued, “So why the fuck doesn’t it do that?” For the next half-hour Jobs berated the group. “You’ve tarnished Apple’s reputation,” he told them. “You should hate each other for having let each other down.” The public humiliation particularly infuriated Jobs. Walt Mossberg, the influential Wall Street Journal gadget columnist, had panned MobileMe. “Mossberg, our friend, is no longer writing good things about us,” Jobs said. On the spot, Jobs named a new executive to run the group. Tim Cook should have already held a meeting like that to address and rectify this Siri and Apple Intelligence debacle. If such a meeting hasn’t yet occurred or doesn’t happen soon, then, I fear, that’s all she wrote. The ride is over. When mediocrity, excuses, and bullshit take root, they take over. A culture of excellence, accountability, and integrity cannot abide the acceptance of any of those things, and will quickly collapse upon itself with the acceptance of all three.

I floated a theory of mine to Atlantic writer Charlie Warzel on this week’s episode of Panic World that content moderation, as we’ve understood, it effectively ended on January 6th, 2021. You can listen to the whole episode here, but the way I look at it is that the Insurrection was the first time Americans could truly see the radicalizing effects of algorithmic platforms like Facebook and YouTube that other parts of the world, particularly the Global South, had dealt with for years. A moment of political violence Silicon Valley could no longer ignore or obfuscate the way it had with similar incidents in countries like Myanmar, India, Ethiopia, or Brazil. And once faced with the cold, hard truth of what their platforms had been facilitating, companies like Google and Meta, at least internally, accepted that they would never be able to moderate them at scale. And so they just stopped.

After 2021, the major tech platforms we’ve relied on since the 2010s could no longer pretend that they would ever be able to properly manage the amount of users, the amount of content, the amount of influence they “need” to exist at the size they “need” to exist at to make the amount of money they “need” to exist.

Under Zuckerberg’s new “censorship”-free plan, Meta’s social networks will immediately fill up with hatred and harassment. Which will make a fertile ground for terrorism and extremism. Scams and spam will clog comments and direct messages. And illicit content, like non-consensual sexual material, will proliferate in private corners of networks like group messages and private Groups. Algorithms will mindlessly spread this slop, boosted by the loudest, dumbest, most reactionary users on the platform, helping it evolve and metastasize into darker, stickier social movements. And the network will effectively break down. But Meta is betting that the average user won’t care or notice. AI profiles will like their posts, comment on them, and even make content for them. A feedback loop of nonsense and violence. Our worst, unmoderated impulses, shared by algorithm and reaffirmed by AI. Where nothing has to be true and everything is popular.

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.

Google is facing many of the same challenges after its decades long dominance of the open web: all of the products shown yesterday rely on a different business model than advertising, and to properly execute and deliver on them will require a cultural shift to supporting customers instead of tolerating them. What hasn’t changed — because it is the company’s nature, and thus cannot — is the reliance on scale and an overwhelming infrastructure advantage. That, more than anything, is what defines Google, and it was encouraging to see that so explicitly put forward as an advantage.

The left side of figure 5-1 indicates that when there is a performance gap — when product functionality and reliability are not yet good enough to address the needs of customers in a given tier of the market — companies must compete by making the best possible products. In the race to do this, firms that build their products around proprietary, interdependent architectures enjoy an important competitive advantage against competitors whose product architectures are modular, because the standardization inherent in modularity takes too many degrees of design freedom away from engineers, and they cannot not optimize performance.

The issue I have with this analysis of vertical integration — and this is exactly what I was taught at business school — is that the only considered costs are financial. But there are other, more difficult to quantify costs. Modularization incurs costs in the design and experience of using products that cannot be overcome, yet cannot be measured. Business buyers — and the analysts who study them — simply ignore them, but consumers don’t. Some consumers inherently know and value quality, look-and-feel, and attention to detail, and are willing to pay a premium that far exceeds the financial costs of being vertically integrated.

Google trains and runs its Gemini family of models on its own TPU processors, which are only available on Google’s cloud infrastructure. Developers can access Gemini through Vertex AI, Google’s fully-managed AI development platform; and, to the extent Vertex AI is similar to Google’s internal development environment, that is the platform on which Google is building its own consumer-facing AI apps. It’s all Google, from top-to-bottom, and there is evidence that this integration is paying off: Gemini 1.5’s industry leading 2 million token context window almost certainly required joint innovation between Google’s infrastructure team and its model-building team.

On the other extreme is AWS, which doesn’t have any of its own models; instead its focus has been on its Bedrock managed development platform, which lets you use any model. Amazon’s other focus has been on developing its own chips, although the vast majority of its AI business runs on Nvidia GPUs.

Microsoft is in the middle, thanks to its close ties to OpenAI and its models. The company added Azure Models-as-a-Service last year, but its primary focus for both external customers and its own internal apps has been building on top of OpenAI’s GPT family of models; Microsoft has also launched its own chip for inference, but the vast majority of its workloads run on Nvidia.

Google is certainly building products for the consumer market, but those products are not devices; they are Internet services. And, as you might have noticed, the historical discussion didn’t really mention the Internet. Both Google and Meta, the two biggest winners of the Internet epoch, built their services on commodity hardware. Granted, those services scaled thanks to the deep infrastructure work undertaken by both companies, but even there Google’s more customized approach has been at least rivaled by Meta’s more open approach. What is notable is that both companies are integrating their models and their apps, as is OpenAI with ChatGPT.

It may be the case that selling hardware, which has to be perfect every year to justify a significant outlay of money by consumers, provides a much better incentive structure for maintaining excellence and execution than does being an Aggregator that users access for free.

Google’s collection of moonshots — from Waymo to Google Fiber to Nest to Project Wing to Verily to Project Loon (and the list goes on) — have mostly been science projects that have, for the most part, served to divert profits from Google Search away from shareholders. Waymo is probably the most interesting, but even if it succeeds, it is ultimately a car service rather far afield from Google’s mission statement “to organize the world’s information and make it universally accessible and useful.”

The only thing that drives meaningful shifts in platform marketshare are paradigm shifts, and while I doubt the v1 version of Pixie [Google’s rumored Pixel-only AI assistant] would be good enough to drive switching from iPhone users, there is at least a path to where it does exactly that.

the fact that Google is being mocked mercilessly for messed-up AI answers gets at why consumer-facing AI may be disruptive for the company: the reason why incumbents find it hard to respond to disruptive technologies is because they are, at least at the beginning, not good enough for the incumbent’s core offering. Time will tell if this gives more fuel to a shift in smartphone strategies, or makes the company more reticent.

while I was very impressed with Google’s enterprise pitch, which benefits from its integration with Google’s infrastructure without all of the overhead of potentially disrupting the company’s existing products, it’s going to be a heavy lift to overcome data gravity, i.e. the fact that many enterprise customers will simply find it easier to use AI services on the same clouds where they already store their data (Google does, of course, also support non-Gemini models and Nvidia GPUs for enterprise customers). To the extent Google wins in enterprise it may be by capturing the next generation of startups that are AI first and, by definition, data light; a new company has the freedom to base its decision on infrastructure and integration.

Amazon is certainly hoping that argument is correct: the company is operating as if everything in the AI value chain is modular and ultimately a commodity, which insinuates that it believes that data gravity will matter most. What is difficult to separate is to what extent this is the correct interpretation of the strategic landscape versus a convenient interpretation of the facts that happens to perfectly align with Amazon’s strengths and weaknesses, including infrastructure that is heavily optimized for commodity workloads.

Meta’s open source approach to Llama: the company is focused on products, which do benefit from integration, but there are also benefits that come from widespread usage, particularly in terms of optimization and complementary software. Open source accrues those benefits without imposing any incentives that detract from Meta’s product efforts (and don’t forget that Meta is receiving some portion of revenue from hyperscalers serving Llama models).

The iPhone maker, like Amazon, appears to be betting that AI will be a feature or an app; like Amazon, it’s not clear to what extent this is strategic foresight versus motivated reasoning.

achieving something approaching AGI, whatever that means, will require maximizing every efficiency and optimization, which rewards the integrated approach.

the most value will be derived from building platforms that treat models like processors, delivering performance improvements to developers who never need to know what is going on under the hood.

Once a company becomes an industry leader, its employees, from top to bottom, start thinking defensively. Suddenly, people feel they have more to lose from challenging the status quo than upending it. As a result, one-time revolutionaries turn into reactionaries. Proof of this about-face comes when senior executives troop off to Washington or Brussels to lobby against changes that would make life easier for the new up and comers.

Years of continuous improvement produce an ultra-efficient business system—one that’s highly optimized, and also highly inflexible. Successful businesses are usually good at doing one thing, and one thing only. Over-specialization kills adaptability—but this is a tough to trap to avoid, since the defenders of the status quo will always argue that eking out another increment of efficiency is a safer bet than striking out in a new direction.

Long-tenured executives develop a deep base of industry experience and find it hard to question cherished beliefs. In successful companies, managers usually have a fine-grained view of “how the industry works,” and tend to discount data that would challenge their assumptions. Over time, mental models become hard-wired—a fact that makes industry stalwarts vulnerable to new rules. This risk is magnified when senior executives dominate internal conversations about future strategy and direction.

With success comes bulk—more employees, more cash and more market power. Trouble is, a resource advantage tends to make executives intellectually lazy—they start believing that success comes from outspending one’s rivals rather than from outthinking them. In practice, superior resources seldom defeat a superior strategy. So when resources start substituting for creativity, it’s time to short the shares.

One quick suggestion: Treat every belief you have about your business as nothing more than a hypothesis, forever open to disconfirmation. Being paranoid is good, becoming skeptical about your own beliefs is better.

The “hard tech” in AI are the LLMs available for rent from OpenAI, Anthropic, Cohere, and others, or available as open source with Llama, Bloom, Mistral and others. The hard-tech is a level playing field; startups do not have an advantage over incumbents.

There can be differentiation in prompt engineering, problem break-down, use of vector databases, and more. However, this isn’t something where startups have an edge, such as being willing to take more risks or be more creative. At best, it is neutral; certainly not an advantage.

This doesn’t mean it’s impossible for a startup to succeed; surely many will. It means that you need a strategy that creates differentiation and distribution, even more quickly and dramatically than is normally required

Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial. Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune algorithms, so long as they maintain secrecy and privacy.

Intercom’s AI strategy is built on the foundation of hundreds of millions of customer interactions. This gives them an advantage over a newcomer developing a chatbot from scratch. Similarly, Google has an advantage in AI video because they own the entire YouTube library. GitHub has an advantage with Copilot because they trained their AI on their vast code repository (including changes, with human-written explanations of the changes).

While there will always be individuals preferring the startup environment, the allure of working on AI at an incumbent is equally strong for many, especially pure computer and data scientsts who, more than anything else, want to work on interesting AI projects. They get to work in the code, with a large budget, with all the data, with above-market compensation, and a built-in large customer base that will enjoy the fruits of their labor, all without having to do sales, marketing, tech support, accounting, raising money, or anything else that isn’t the pure joy of writing interesting code. This is heaven for many.

A chatbot is in the chatbot market, and an SEO tool is in the SEO market. Adding AI to those tools is obviously a good idea; indeed companies who fail to add AI will likely become irrelevant in the long run. Thus we see that “AI” is a new tool for developing within existing markets, not itself a new market (except for actual hard-tech AI companies).

AI is in the solution-space, not the problem-space, as we say in product management. The customer problem you’re solving is still the same as ever. The problem a chatbot is solving is the same as ever: Talk to customers 24/7 in any language. AI enables completely new solutions that none of us were imagining a few years ago; that’s what’s so exciting and truly transformative. However, the customer problems remain the same, even though the solutions are different

Companies will pay more for chatbots where the AI is excellent, more support contacts are deferred from reaching a human, more languages are supported, and more kinds of questions can be answered, so existing chatbot customers might pay more, which grows the market. Furthermore, some companies who previously (rightly) saw chatbots as a terrible customer experience, will change their mind with sufficiently good AI, and will enter the chatbot market, which again grows that market.

the right way to analyze this is not to say “the AI market is big and growing” but rather: “Here is how AI will transform this existing market.” And then: “Here’s how we fit into that growth.”

That other people tried your idea without success could imply it’s a bad idea or simply that the timing or execution was wrong. Distinguishing between these cases is hard and where you should apply serious thought. If you think your competitors executed poorly, you should develop a theory of what they did wrong and how you’ll do better.

If you think your competitor’s timing was off, you should have a thesis about what’s changed to make now the right time. These changes could come in a variety of forms: for example, it could be that users have become more sophisticated, the prices of key inputs have dropped, or that prerequisite technologies have become widely adopted.

Startups are primarly competing against indifference, lack of awareness, and lack of understanding — not other startups.

There were probably 50 companies that tried to do viral video sharing before YouTube. Before 2005, when YouTube was founded, relatively few users had broadband and video cameras. YouTube also took advantage of the latest version of Flash that could play videos seamlessly.

Google and Facebook launched long after their competitors, but executed incredibly well and focused on the right things. When Google launched, other search engines like Yahoo, Excite, and Lycos were focused on becoming multipurpose “portals” and had de-prioritized search (Yahoo even outsourced their search technology).

in their efforts to provide better products than their competitors and earn higher prices and margins, suppliers often “overshoot” their market: They give customers more than they need or ultimately are willing to pay for. And more importantly, it means that disruptive technologies that may underperform today, relative to what users in the market demand, may be fully performance-competitive in that same market tomorrow. This was the basis for insisting that the iPhone must have a low-price model: surely Apple would soon run out of new technology to justify the prices it charged for high-end iPhones, and consumers would start buying much cheaper Android phones instead! In fact, as I discussed in after January’s earnings results, the company has gone in the other direction: more devices per customer, higher prices per device, and an increased focus on ongoing revenue from those same customers.

Apple seems to have mostly saturated the high end, slowly adding switchers even as existing iPhone users hold on to their phones longer; what is not happening, though, is what disruption predicts: Apple isn’t losing customers to low-cost competitors for having “overshot” and overpriced its phones. It seems my thesis was right: a superior experience can never be too good — or perhaps I didn’t go far enough.

Jeff Bezos has been writing an annual letter to shareholders since 1997, and he attaches that original letter to one he pens every year. It included this section entitled Obsess Over Customers: From the beginning, our focus has been on offering our customers compelling value. We realized that the Web was, and still is, the World Wide Wait. Therefore, we set out to offer customers something they simply could not get any other way, and began serving them with books. We brought them much more selection than was possible in a physical store (our store would now occupy 6 football fields), and presented it in a useful, easy-to-search, and easy-to-browse format in a store open 365 days a year, 24 hours a day. We maintained a dogged focus on improving the shopping experience, and in 1997 substantially enhanced our store. We now offer customers gift certificates, 1-Click shopping, and vastly more reviews, content, browsing options, and recommendation features. We dramatically lowered prices, further increasing customer value. Word of mouth remains the most powerful customer acquisition tool we have, and we are grateful for the trust our customers have placed in us. Repeat purchases and word of mouth have combined to make Amazon.com the market leader in online bookselling.

This year, after highlighting just how much customers love Amazon (answer: a lot), Bezos wrote: One thing I love about customers is that they are divinely discontent. Their expectations are never static — they go up. It’s human nature. We didn’t ascend from our hunter-gatherer days by being satisfied. People have a voracious appetite for a better way, and yesterday’s ‘wow’ quickly becomes today’s ‘ordinary’. I see that cycle of improvement happening at a faster rate than ever before. It may be because customers have such easy access to more information than ever before — in only a few seconds and with a couple taps on their phones, customers can read reviews, compare prices from multiple retailers, see whether something’s in stock, find out how fast it will ship or be available for pick-up, and more. These examples are from retail, but I sense that the same customer empowerment phenomenon is happening broadly across everything we do at Amazon and most other industries as well. You cannot rest on your laurels in this world. Customers won’t have it.

when it comes to Internet-based services, this customer focus does not come at the expense of a focus on infrastructure or distribution or suppliers: while those were the means to customers in the analog world, in the online world controlling the customer relationship gives a company power over its suppliers, the capital to build out infrastructure, and control over distribution. Bezos is not so much choosing to prioritize customers insomuch as he has unlocked the key to controlling value chains in an era of aggregation.

consumer expectations are not static: they are, as Bezos’ memorably states, “divinely discontent”. What is amazing today is table stakes tomorrow, and, perhaps surprisingly, that makes for a tremendous business opportunity: if your company is predicated on delivering the best possible experience for consumers, then your company will never achieve its goal.

In the case of Amazon, that this unattainable and ever-changing objective is embedded in the company’s culture is, in conjunction with the company’s demonstrated ability to spin up new businesses on the profits of established ones, a sort of perpetual motion machine

Owning the customer relationship by means of delivering a superior experience is how these companies became dominant, and, when they fall, it will be because consumers deserted them, either because the companies lost control of the user experience (a danger for Facebook and Google), or because a paradigm shift made new experiences matter more (a danger for Google and Apple).

Quality software from independent makers is like quality food from the farmer’s market. A jar of handmade organic jam is not the same as mass-produced corn syrup-laden jam from the supermarket. Industrial fruit jam is filled with cheap ingredients and shelf stabilizers. Industrial software is filled with privacy-invasive trackers and proprietary formats. Google, Apple, and Microsoft make industrial software. Like industrial jam, industrial software has its benefits — it’s cheap, fairly reliable, widely available, and often gets the job done.

Big tech companies have the ability to make their software cheap by subsidizing costs in a variety of ways:

Google sells highly profitable advertising and makes its apps free, but you are subjected to ads and privacy-invasive tracking. Apple sells highly profitable devices and makes its apps free, but locks you into a proprietary ecosystem. Microsoft sells highly profitable enterprise contracts using a bundling strategy, and makes its apps cheap, also locking you into a proprietary ecosystem.

I’m not saying these companies are evil. But their subsidies create the illusion that all software should be cheap or free.

Independent makers of quality software go out of their way to make apps that are better for you. They take a principled approach to making tools that don’t compromise your privacy, and don’t lock you in. Independent software makers are people you can talk to. Like quality jam from the farmer’s market, you might become friends with the person who made it — they’ll listen to your suggestions and your complaints.

Big tech companies earn hundreds of billions of dollars and employ hundreds of thousands of people. When they make a new app, they can market it to their billions of customers easily. They have unbeatable leverage over the cost of developing and maintaining their apps.

But more than anything, they were able to merge with major competitors and buy out small ones. Google made one good product, search, a quarter of a century ago. That opened conduit to the capital markets that gave Google an effectively limitless budget to buy competitors.So it didn’t matter that everything Google made in-house failed — videos, social media, wifi balloons, smart cities, they couldn’t even keep an RSS Reader alive!Because they were able to buy other peoples’ companies — mobile, ad tech, videos, maps, documents, satellites, server management. Google isn’t Willy Wonka’s magic idea factory, they’re Rich Uncle Pennybags, spending other peoples’ money to buy the products they themselves are too ossified and lumbering to create.

They were able to sell goods below cost, which let the deepest-pocketed companies bankrupt their competitors, and prevent new companies from entering the market. Think of Amazon, which tried to buy diapers.com, got rejected, and then lit $100m on fire selling diapers below cost, until diapers.com went bankrupt.

When Apple reversed Office and built iWork, Microsoft just had to suck it up. In the ensuing decades, Apple — and Microsoft, Facebook, Google and other tech giants — have secured changes to law, regulation and their interpretations that make doing unto them as they did unto others radioactivelyillegal.

Tech companies can twiddle the knobs whenever they want, without explanation or transparency, and we can’t get a law passed to make them stop compulsively touching their knobs, because in the world of five giants websites each filled with screenshots of the other four, they can easily agree that these rules are bad, and they can mobilize their monopoly casino winnings to make sure they never pass.

Step one: consolidated industries eliminate competition through predatory pricing and acquisitions. Step two: tech companies play a high-speed shell-game on the back end, and use their consolidation to bigfoot any attempt to constrain their twiddling (like privacy, labor, or fair trading laws). Now we come to step thre: where tech companies embrace tech laws, laws that make it illegal to twiddle back at them, the IP laws that create felony contempt of business-model, criminalizing the adversarial interoperability, that once acted as garbage collection for enshittified, bloated, top-heavy companies, letting nimble, innovative players drain off their users, eat their lunch and dance on their graves.Put these three factors together — consolidation, unrestricted twiddling for them, a total ban on twiddling for us — and enshittification becomes inevitable.

We don’t want to wait that long for a new good internet, and we don’t have to. Because tech is different: it is universal. It is interoperable, and that means we have options we’ve never had before.Interoperability options: options that devolve control over technology from giant companies to small companies, co-ops, nonprofits, and communities of users themselves.Interop is how we seize the means of computation.

First things first: we need to limit twiddling.Pass comprehensive federal privacy laws with private right of action, meaning that you can sue if your privacy is violated, even if the local public prosecutor doesn’t think you deserve justice.End worker misclassification through the so-called gig economy, meaning that every worker is entitled to minimum wages, a safe workplace, and fair scheduling.Apply normal consumer protection standards to ecommerce platforms and search engines, banning deceptive advertising, fake reviews, and misleading search results that put fake businesses and products ahead of the best matches.

Then we need to open the walled gardens. Laws like the EU’s Digital Markets Act will force tech platforms to stand up APIs that allow new platforms to connect to them. This interop will make switching costs low. So you can leave Facebook or Twitter and go to Mastodon, Diaspora — or Bluesky or some new platform — and still exchange messages with the people you left behind, and participate in the communities that matter to you, and connect with the customers you rely on.

To make mandatory APIs work, we need to make robust interoperability preferable to behind-the-scenes fuckery, we need to align tech giants’ incentives so they encourage competition, rather than sabotaging it.

in addition to the mandatory interop that’s already coming down the pike, we need to restore the right to mod, tinker, reverse and hack these services.

If we have the right to mod existing service to restore busted API functionality, then any company that’s tempted to nerf its API has to consider the possibility that you are going to come along and scrape its site or reverse its apps to make the API work again.That means that the choice for tech giants isn’t “Keep the API and lose my discontented users or nerf the API and screw my competitors.” It’s: “Keep the API and lose my discontented users or, nerf the API and get embroiled in unquantifiable guerilla warfare against engineers who have the attackers’ advantage, meaning I have to be perfect, and they only have to find and exploit a single error I make.”

Governments should require that every tech company that sells them a product or service has to promise not to interfere with interop.That’s just prudent public administration. Lincoln insisted that every rifle-supplier for the Union army used interoperable tooling and ammo. Of course he did! “Sorry boys, war’s cancelled, our sole supplier decided not to make any more bullets.”

Every digital system procured by every level of government should come with a binding covenant not to impede interop — from the cars in government motor-pools to Google Classroom in public schools to iPhones in public agencies.

Your shareholders’ priorities are your problem. Public agencies are charged with doing the people’s business.

It’s frankly surreal that the way we keep Facebook’s partners from abusing your info is by asking Facebook to decide what is and isn’t acceptable.Remember: Cambridge Analytica was a Facebook partner. So whether you’re using an API or you’re fielding an interoperable app that relies on scraping and reversing, you will be bound by those same laws, passed by democratically accountable lawmakers in public proceedings, not by shareholder accountable corporate executives in closed-door meetings.

They’re just able to buy their way to dominance, merging with competitors, until they have the money and the unity of purpose to capture our laws, to give them the freedom to abuse us without limit, and to criminalize anything we do to defend ourselves.To stop them we need to block new merger, and unwind existing ones, limit their ability to twiddle the back end to keep their users and business customers in a constant state of confusion, and restore our ability to twiddle back, to give ourselves an internet operated by and for the people who use it: the new, good internet that is the worthy successor to the old, good internet.

Remember when tech workers dreamed of working for a big company for a few years, before striking out on their own to start their own company that would knock that tech giant over?Then that dream shrank to: work for a giant for a few years, quit, do a fake startup, get acqui-hired by your old employer, as a complicated way of getting a bonus and a promotion.Then the dream shrank further: work for a tech giant for your whole life, get free kombucha and massages on Wednesdays.And now, the dream is over. All that’s left is: work for a tech giant until they fire your ass, like those 12,000 Googlers who got fired six months after a stock buyback that would have paid their salaries for the next 27 years.

“Some day, there will be a crisis, and when crisis comes, ideas that are lying around can move from the fringe to the center in an instant.”

For Google Search to increase its profits, it must shift value from web publishers, advertisers and/or users to itself. The only way for Google Search to grow is to make itself worse.

Google’s product managers are each charged with finding ways to increase the profitability of their little corner of the googleverse. That increased profitability can only come from enshittification. Every product manager on Google Search spends their workdays figuring out how to remove a Jenga block. What’s worse, these princelings compete with one another. Their individual progression through the upper echelons of Google’s aristocracy depends as much on others failing as it does on their success. The org chart only has so many VP, SVP and EVP boxes on it, and each layer is much smaller than the previous one. If you’re a VP, every one of your colleagues who makes it to SVP takes a spot that you can no longer get. Those spots are wildly lucrative. Each tier of the hierarchy is worth an order of magnitude more than the tier beneath it. The stakes are so high that they are barely comprehensible. That means that every one of these Jenga-block-pulling execs is playing blind: they don’t — and can’t — coordinate on the ways they’re planning to lower quality in order to improve profits. The exec who decided to save money by reducing the stringency of phone number checking for business accounts didn’t announce this in a company-wide memo. When you’re eating your seed-corn, it’s imperative that you do so behind closed doors, and tell no one what you’ve done. Like any sleight-of-hand artist, you want the audience to see the outcome of the trick (the cost savings), not how it’s done (exposing every searcher in the world to fraud risk to save a buck).

Google/Apple’s mobile duopoly is more cozy than competitive. Google pays Apple $15–20 billion, every single year, to be the default search in Safari and iOS. If Google and Apple were competing over mobile, you’d expect that one of them would drop the sky-high 30 percent rake they charge on in-app payments, but that would mess up their mutual good thing. Instead, these “competitors” charge exactly the same price for a service with minimal operating costs.

your bank, your insurer, your beer company, the companies that make your eyeglasses and your athletic shoes — they’ve all run out of lands to conquer, but instead of weeping, they’re taking it out on you, with worse products that cost more.

The criticisms I have been seeing about the features of the Pixel 8, however, feel like we are only repeating the kinds of fears of nearly two hundred years. We have not been able to wholly trust photographs pretty much since they were invented. The only things which have changed in that time are the ease with which the manipulations can happen, and their availability.

We all live with a growing sense that everything around us is fraudulent. It is striking to me how these tools have been introduced as confidence in institutions has declined. It feels like a death spiral of trust — not only are we expected to separate facts from their potentially misleading context, we increasingly feel doubtful that any experts are able to help us, yet we keep inventing new ways to distort reality.

The questions that are being asked of the Pixel 8’s image manipulation capabilities are good and necessary because there are real ethical implications. But I think they need to be more fully contextualized. There is a long trail of exactly the same concerns and, to avoid repeating ourselves yet again, we should be asking these questions with that history in mind. This era feels different. I think we should be asking more precisely why that is.

The questions we ask about generative technologies should acknowledge that we already have plenty of ways to lie, and that lots of the information we see is suspect. That does not mean we should not believe anything, but it does mean we ought to be asking questions about what is changed when tools like these become more widespread and easier to use.

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?”

The idea that the future is created by flawed geniuses who happen to accumulate great wealth is outmoded and simplistic, and it encourages a flattened view of how technology is developed and whom it impacts. Just scan the list of sources Isaacson includes in the book: executives, venture capitalists, founders and high-ranking engineers. Yes, Isaacson spoke to “adversaries” like Jeff Bezos and Bill Gates, but not (at least per the list) to line workers, not to Jenna, not to anyone whose family member died in an Autopilot crash, nor anyone who tried to organize a Tesla plant.

There is little precedent for a civilian’s becoming the arbiter of a war between nations in such a granular way, or for the degree of dependency that the U.S. now has on Musk in a variety of fields, from the future of energy and transportation to the exploration of space. SpaceX is currently the sole means by which NASA transports crew from U.S. soil into space, a situation that will persist for at least another year. The government’s plan to move the auto industry toward electric cars requires increasing access to charging stations along America’s highways. But this rests on the actions of another Musk enterprise, Tesla. The automaker has seeded so much of the country with its proprietary charging stations that the Biden Administration relaxed an early push for a universal charging standard disliked by Musk. His stations are eligible for billions of dollars in subsidies, so long as Tesla makes them compatible with the other charging standard.

In the past twenty years, against a backdrop of crumbling infrastructure and declining trust in institutions, Musk has sought out business opportunities in crucial areas where, after decades of privatization, the state has receded. The government is now reliant on him, but struggles to respond to his risk-taking, brinkmanship, and caprice

Current and former officials from NASA, the Department of Defense, the Department of Transportation, the Federal Aviation Administration, and the Occupational Safety and Health Administration told me that Musk’s influence had become inescapable in their work, and several of them said that they now treat him like a sort of unelected official

Sam Altman, the C.E.O. of OpenAI, with whom Musk has both worked and sparred, told me, “Elon desperately wants the world to be saved. But only if he can be the one to save it.

later. “He had grown up in the male-dominated culture of South Africa,” Justine wrote. “The will to compete and dominate that made him so successful in business did not magically shut off when he came home.”

There are competitors in the field, including Jeff Bezos’s Blue Origin and Richard Branson’s Virgin Galactic, but none yet rival SpaceX. The new space race has the potential to shape the global balance of power. Satellites enable the navigation of drones and missiles and generate imagery used for intelligence, and they are mostly under the control of private companies.

A number of officials suggested to me that, despite the tensions related to the company, it has made government bureaucracies nimbler. “When SpaceX and NASA work together, we work closer to optimal speed,” Kenneth Bowersox, NASA’s associate administrator for space operations, told me. Still, some figures in the aerospace world, even ones who think that Musk’s rockets are basically safe, fear that concentrating so much power in private companies, with so few restraints, invites tragedy.

Tesla for a time included in its vehicles the ability to replace the humming noises that electric cars must emit—since their engines make little sound—with goat bleats, farting, or a sound of the owner’s choice. “We’re, like, ‘No, that’s not compliant with the regulations, don’t be stupid,’ ” Cliff told me. Tesla argued with regulators for more than a year, according to an N.H.T.S.A. safety report

Musk’s personal wealth dwarfs the entire budget of OSHA, which is tasked with monitoring the conditions in his workplaces. “You add on the fact that he considers himself to be a master of the universe and these rules just don’t apply to people like him,” Jordan Barab, a former Deputy Assistant Secretary of Labor at OSHA, told me. “There’s a lot of underreporting in industry in general. And Elon Musk kind of seems to raise that to an art form.”

Some people who know Musk well still struggle to make sense of his political shift. “There was nothing political about him ever,” a close associate told me. “I’ve been around him for a long time, and had lots of deep conversations with the man, at all hours of the day—never heard a fucking word about this.”

the cuts that Musk had instituted quickly took a toll on the company. Employees had been informed of their termination via brusque, impersonal e-mails—Musk is now being sued for hundreds of millions of dollars by employees who say that they are owed additional severance pay—and the remaining staffers were abruptly ordered to return to work in person. Twitter’s business model was also in question, since Musk had alienated advertisers and invited a flood of fake accounts by reinventing the platform’s verification process

Musk’s trolling has increasingly taken on the vernacular of hard-right social media, in which grooming, pedophilia, and human trafficking are associated with liberalism

It is difficult to say whether Musk’s interest in A.I. is driven by scientific wonder and altruism or by a desire to dominate a new and potentially powerful industry.

Netflix could buy 10 top quality screenplays per year with the cash they’ll spend on that one job.  They must have big plans for AI.There are also a half dozen AI job openings at Disney. And the tech-based streamers (Apple, Amazon) already have made big investments in AI. Sony launched an AI business unit in April 2020—in order to “enhance human imagination and creativity, particularly in the realm of entertainment.”

When Spotify launched on the stock exchange in 2018, it was losing around $30 million per month. Now it’s much larger, and is losing money at the pace of more than $100 million per month.

But the real problem at Spotify isn’t just convincing people to pay more. It runs much deeper. Spotify finds itself in the awkward position of asking people to pay more for a lousy interface that degrades the entire user experience.

Boredom is built into the platform, because they lose money if you get too excited about music—you’re like the person at the all-you-can-eat buffet who goes back for a third helping. They make the most money from indifferent, lukewarm fans, and they created their interface with them in mind. In other words, Spotify’s highest aspiration is to be the Applebee’s of music.

They need to prepare for a possible royalty war against record labels and musicians—yes, that could actually happen—and they do that by creating a zombie world of brain dead listeners who don’t even know what artist they’re hearing. I know that sounds extreme, but spend some time on the platform and draw your own conclusions.

The broader issue is that the video industry finally seems to be facing what happened to the print and music industry before them: the Internet comes bearing gifts like infinite capacity and free distribution, but those gifts are a poisoned chalice for industries predicated on scarcity. When anyone could publish text, most text-based businesses went from massive profitability to terminal decline; when anyone could distribute music the music industry could only be saved by tech companies like Spotify helping them sell convenience in place of plastic discs.

thanks to COVID a lot of people fell out of the habit of going to the movie theater, and it appears around 25% of the audience permanently found something better to do with their time; that same reality applies to TV. Just as newspapers once thought the Internet was a boon because it increased their addressable market, only to find out that it also drastically increased competition for readers’ attention, Hollywood has to face the reality that the ability to make far more shows extends not only to studios but also to literally anyone.

Maybe we’ll get to a point where the novelty will be that a human being wrote something: This person proved that they were in a box away from any A.I. when they wrote this thing

as writers and creators, you want people to watch your show, so if you can make something look and sound like something else that people already want to watch, then you might be able to convince a producer that it will have legs. But I discovered through doing “Fleabag” that you have to write something that is more dangerous, more honest, more unusual and more provocative — especially if it’s going to go into a pool with a million other things. Honing the uniqueness of whatever you do is your best chance. I know I’m saying that having just signed up to do “Tomb Raider,” which has an audience already, and I know that’s what Amazon wants, and Amazon made this unbelievable deal8 8 In 2019, Variety reported about Waller-Bridge’s development deal with Amazon Studios, that “sources say the deal is worth around $20 million a year.” with me. I care so much about delivering for them. Being able to do that dangerous, naughty, transgressive stuff in the heart of something that is very valuable to them in terms of I.P. satisfies both of those things, but the discipline for me is to not just give them the “Tomb Raider” they think they want, but to give them something else.

People are going to interpret everything I do as my feelings on contemporary womanhood because I’m a contemporary woman. I don’t want to escape that part of me. I can see how I’ve gone into masculine roles with Bond and “Indiana Jones,” but those worlds are the ones that always intrigued me. The high-stakes action world appeals to me, whether it’s masculine or feminine. I like the urgency of it and the idea of being able to write a female character in a world like that.

It’s a window into your psychology: You want to be a pleaser and do the assignment well, but what you actually want to do is something riskier. Oh, my gosh. That’s exactly what it is. But the best thing is when you satisfy both. The journey there can be quite [laughs] — I love the feeling of having done what’s been asked, but I hate the feeling of pleasing.

I think that with Bond there is something dangerous, transgressive and incendiary about that character, and it’s the same with Indy. He completely revolutionized the action hero, which Harrison1 1 Harrison Ford, of course, who has said “Indiana Jones and the Dial of Destiny” will be his last go-round with Indy’s famous whip and fedora. is dead set against him being described as, but there was something that broke the form. We accept them now as the biggest franchises, but in the kernel of these characters is something naughty and dangerous. They were the rascals of their time, and I feel like Villanelle and Fleabag are rascals.2 2 Villanelle is the name of the assassin character, played by Jodie Comer, in “Killing Eve.” “Fleabag,” for those who haven’t seen it, is that show’s title character, played by Waller-Bridge. The show earned six Emmy Awards and 11 nominations for its second season. So it was less like, “I want to go do this big movie,” and more, “I want to play in the sand pit with these rascals.” That’s one way of looking at it.

I couldn’t write anything that I felt didn’t have that deeper element sincerely at the heart of it, and that writer is with me everywhere I go. It’s ever-present: What does this mean? Because I’m obsessed with having an audience be moved.6 6 Waller-Bridge said the most recent things that moved her were the TV series “Dead Ringers,” a concert by the singer Christine Bovill in which she performed Edith Piaf songs and a revival of “Guys and Dolls” at the Bridge Theater in London. I was moved when I read the script, and I was moved when I heard Jim7 7 James Mangold, the director of “Dial of Destiny.” He is the first director other than Steven Spielberg to direct an “Indiana Jones” movie. and Harrison and Kathy talk about it. I mean, I wasn’t in tears on the floor, but I felt that tingle of, this has got some human stuff going on. But the day-to-day? Some of the days were superfun, and we did look really cool. But the proper actors don’t want to just look cool. They want to make you cry while looking cool.

In the coming weeks, when you search for something that might benefit from the experiences of others, you may see a Perspectives filter appear at the top of search results. Tap the filter, and you’ll exclusively see long- and short-form videos, images and written posts that people have shared on discussion boards, Q&A sites and social media platforms. We’ll also show more details about the creators of this content, such as their name, profile photo or information about the popularity of their content.

Helpful information can often live in unexpected or hard-to-find places: a comment in a forum thread, a post on a little-known blog, or an article with unique expertise on a topic. Our helpful content ranking system will soon show more of these “hidden gems” on Search, particularly when we think they’ll improve the results.We’ve also worked to improve how we rank review content on Search – for example, web pages that review businesses or destinations – to place greater emphasis on the quality and originality of the information. You’ll now see more pages that are based on first-hand experience, or are created by someone with deep knowledge in a given subject. And as we underscore the importance of “experience” as an element of helpful content, we continue our focus on information quality and critical attributes like authoritativeness, expertise and trustworthiness, so you can rely on the information you find.

I think hardcore Twitter users have rose-colored glasses about the site’s coolness. The reason for its success, if you can argue that it was ever really successful, wasn’t that it was cooler than Facebook. It was because of its proximity to power. The reason it was so popular with activists, extremists, journalists, and shitposters was because what you posted there could actually affect culture.

The thing that ties together pretty much everything that’s happened on Twitter since it launched in 2006 was the possibility that those who were not in power (or wanted more) could influence those who were.

I subscribe to the belief that internet trends are defined by a ratio of laziness to social reward. Users will always do the laziest possible thing to achieve the maximum amount clout. So, if every platform becomes either a Twitter alternative or a short-form video feed, but all with their own unique requirements for virality, users won’t make individual posts for each. They will instead shotgun blast all of them with the same posts and bet on the odds that something will breakthrough eventually. Which means everything eventually just becomes a reuploaded video or a screenshot from somewhere else.

While trying to track down the actual hyperlink to a post I found a screenshot of on a closed social network I was struck by how on an internet full of closed platforms, broken embeds, and crumbling indexes, the last reliable way to share anything is a screenshot.

the camera roll is, at this point, the real content management system of the social web. This is something that TikTok realized faster than other platforms, with their downloadable watermarked videos that have now become ubiquitous on every platform that allows video.

My theory as to why New Yorkers were so allergic to independent content creators is because for all the tedious guffawing about being a city of hustlers, most of the people who live there crave, on some level, institutional legitimacy and influencers, by definition, don’t get it or really need it. It could also just be that New Yorkers hate tourists and content creators are, in some form, permanent tourists of their own lives.

I actually think the post-COVID New York TikTok boom is already cresting. I think once these trends become calcified enough to report on, they’re already on their way out. I also don’t think Gen Z TikTokers are driving rents up, but rather documenting its rise due to other factors, like landlords being able to blame TikTok hype to jack up their rents.

Oh ElonWell, look, if I were the newly hired chief executive officer of a social media company, and if the directors and shareholders who brought me in as CEO had told me that my main mission was to turn around the company’s precarious financial situation by improving our position with advertisers, and if I spent my first few weeks reassuring advertisers and rebuilding relationships and talking up our site’s unique audience and powerful engagement, and then one day my head of software engineering came to me and said “hey boss, too many people were too engaged with too many posts, so I had to limit everyone’s ability to view posts on our site, just FYI,” I would … probably … fire ... him?

I mean I suppose I might ask questions like “Is this because of some technological limitation on our system? Is it because you were monkeying with the code without understanding it? Is it because you tried to stop people from reading the site without logging in, 3 and messed up and stopped them from reading the site even when they logged in? Is it because you fired and demoralized too many engineers so no one was left to keep the systems running normally? Is it because you forgot to pay the cloud bills? Is it because deep down you don’t like it when people read posts on our site and you want to stop them, or you don’t like relying on ad revenue and want to sabotage my ability to sell ads?”

no matter what the answers are, this guy’s gotta go. If you are in charge of the software engineers at a social media site, and you make it so that people can’t read the site, that’s bad.

Over the past 10 days, [Ultimate Fighting Championship President Dana] White said he, Mr. Musk and [Mark] Zuckerberg — aided by advisers — have negotiated behind the scenes and are inching toward physical combat. While there are no guarantees a match will happen, the broad contours of an event are taking shape, said Mr. White and three people with knowledge of the discussions.People keep emailing to ask about, like, the fiduciary duties and securities-law disclosure issues here, but I’m gonna wait until they’re in the octagon before I worry about that stuff