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.

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.”

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.

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.

Meanwhile, whenever I talk to music people or book people, very quickly the conversation becomes a music industry conversation or a book industry conversation. What matters for music are artists and touring and labels and so on, and what matters for books are writers and publishers and rights and Amazon’s bargaining power in books and so on. These aren’t tech conversations.

Tech needed content to make their devices viable, but having got the content (by any means necessary), and with it of course completely resetting the dynamics of the industry, tech outgrew music and books and moved on to bigger opportunities.

All of this of course takes us to TV, the industry that’s next on the tech industry’s content journey. Just as new technology unlocked massive change in music and (rather less so) in books, it is now about to break apart the bundled, linear channel model of the TV industry (this is especially the case in the USA, which has a hugely over-served pay TV market). As this happens, there are all sorts of questions that follow on: what happens to channels that might be able to make more going direct to consumer (HBO, perhaps); what happens to channels that might benefit from being in a bundle and lose from having to go direct (ESPN, perhaps), where the syndication model goes, and so on, and so on.

Just as for music or books, though, these are all fundamentally TV industry questions. What viewing distribution, what rights structure, what exploitation chain, what relationship between creatives, financiers, aggregators and distributors - these are all southern California questions, not northern California questions. So, what are the northern California questions, and will this end up being any more strategic than books or music?

Amazon and Netflix have entered TV content creation and ownership in ways and on a scale that no-one from tech ever did for music or books. Amazon did try to get into book publishing and has a significant self-publishing arm, but it had little success recruiting existing mainstream authors; neither Apple nor Spotify created a record label.

Netflix, of course, is a TV company, in the context of this conversation - it isn’t using content for leverage for some other platform (Spotify is the same, without the commissioning). But Amazon clearly is using content for platform leverage - as something else to speed up the Prime flywheel. Prime has become a third pillar to Amazon’s business, next to logistics and the ecommerce platform, and Amazon is always looking for ways to add more perceived value to it, preferably with no marginal cost - TV content that it owns outright is exactly that.

You don't close your Facebook account - you just go there less. You might stop paying for the Youtube TV service, but that won’t cut off your access to any other part of Google - nor would anyone want it to - the purpose of these businesses is reach. Nor, really, will you fundamentally change your search behaviour if Google discovers the next Game of Thrones. That is, cancel Prime and you'd lose Amazon, but what do Google & FB have to cancel? Without some platform decision to lock you into, content is marketing, and revenue, but not a lever.

Apple has always preferred a very asset-light approach to things that are outside its core skills. It didn’t create a record label, or an MVNO, and it didn’t create a credit card for Apple Pay - it works with partners on the existing rails as much as possible (even the upcoming Apple Pay P2P service uses a partner bank).

Part of ‘content is king’ was the idea that (at least in theory) content companies can withhold access to their libraries entirely, and in the past one might have presumed that that meant they had the power to kill any new service at birth. In reality, rights-holders have always had too strong a need for short-term revenue to forgo broad distribution, and few of them individually had a strong enough brand to extract a fee that was high enough to justify exclusivity. They always have to take the cheques - individually to meet their bonus targets, and collectively to meet their earnings estimates.

This is a multi-sided market place with too many players on both sides for anyone to exert dominance: Apple dominated purchased music and Amazon dominates ebooks (thanks to the DoJ), but there is no such dominance on the buy or sell side for TV, for now.

The reason Apple TV, Chromecast, FireTV and everything else feel so anti-climactic is that getting onto the TV was a red herring - the device is the phone and the network is the internet. The smartphone is the sun and everything else orbits it. Internet advertising will be bigger than TV advertising this year, and Apple’s revenue is larger than the entire global pay TV industry. This is also why tech companies are even thinking about commissioning their own premium shows today - they are now so big that the budgets involved in buying or creating TV look a lot less daunting than they once did.