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.

Companionship content is long-form content that can be consumed passively — allowing the consumer to be incompletely attentive, and providing a sense of relaxation, comfort, and community.

Interestingly, each individual “unit” of music is short-form (e.g. a 3-5 minute song), but how we consume it tends to be long-form and passive (i.e. via curated stations, lengthy playlists, or algorithms that adapt to our taste).

If you’re rewatching a show or movie, it’s likely to be companionship content. (Life-like conversational sitcoms can be consumed this way too.) As streaming matures, platforms are growing their passive-watch library.

content isn’t always prescriptively passive, rather it’s rooted in how consumers engage it.

That said, some content lends better to being companionship content: Long-form over short. Conversational over action. Simple plot versus complex.

Short-form video requires more attention & action in a few ways: Context switching, i.e. wrapping your head around a new piece of context every 30 seconds, especially if they’re on unrelated topics with different styles Judgment & decision-making, i.e. contemplating whether to keep watching or swipe to the next video effectively the entire time you’re watching a video Multi-sensory attention, i.e. default full-screen and requires visual and audio focus, especially since videos are so short that you can easily lose context Interactive components, e.g. liking, saving, bookmarking,

With how performative, edited, and algorithmically over-optimized it is, TikTok feels sub-human. TikTok has quickly become one of the most goal-seeking places on earth. I could easily describe TikTok as a global focus group for commercials. It’s the product personification of a means to an end, and the end is attention.

even TikTok creators are adapting the historically rigid format to appeal to more companionship-esque emotions and improve retention.

When we search for a YouTube video to watch, we often want the best companion for the next hour and not the most entertaining content.

While short-form content edits are meant to be spectacular and attention-grabbing, long-form content tends to be more subtle in its emotional journey Long-form engagement with any single character or narrative or genre lets you develop stronger understanding, affinity, and parasocial bonds Talk-based content (e.g. talk shows, podcasts, comedy, vlogs, life-like sitcoms) especially evokes a feeling of companionship and is less energy-draining The trends around loneliness and the acceleration of remote work has and will continue to make companionship content even more desirable As we move into new technology frontiers, we might unlock novel types of companionship content itself, but I’d expect this to take 5-10 years at least

TikTok is where you connect with an audience, YouTube is where you consolidate it.5 Long-form content also earns creators more, with YouTube a standout in revenue sharing.

YouTube paid out $16 billion to creators in 2022 (which is 55% of its annual $30 billion in revenue) and the other four social networks paid out about $1 billion each from their respective creator funds. In total, that yields $20 billion.”

Mr. Beast, YouTube’s top creator, says YouTube is now the final destination, not “traditional” hollywood stardom which is the dream of generations past. Creators also want to funnel audiences to apps & community platforms where they can own user relationships, rely less on algorithms, engage more directly and deeply with followers, and enable follower-to-follower engagement too

Interestingly of course, an increasing amount of short-form video, including formats like clips and edits, seems to be made from what originally was long-form content.8 And in return, these recycled short-form videos can drive tremendous traffic to long-form formats and platforms.

90% of people use a second screen while watching TV. We generally talk about “second screen” experiences in the context of multiple devices, but you can have complementary apps and content running on the same device — you can have the “second screen” on the same screen.

YouTube itself also cites a trend of people putting YouTube on their real TV screens: “There are more Americans gathering around the living room TV to watch YouTube than any other platform. Why? Put simply, people want choices and variety … It’s a one stop shop for video viewing. Think about something historically associated with linear TV: Sports. Now, with [our NFL partnership], people can not only watch the games, but watch post-game highlights and commentary in one place.”

If I were to build an on-demand streaming product or any kind of content product for that matter, I’d build for the companionship use case — not only because I think it has a higher ceiling of consumer attention, but also because it can support more authentic, natural, human engagement.

All the creators that are ‘made’ on TikTok are looking for a place to go to consolidate the attention they’ve amassed. TikTok is commercials. YouTube is TV. (Though yes, they’re both trying to become each other).

certainly AI and all the new creator tools enabled by it will help people mix and match and remix long and short formats all day, blurring the historically strict distinctions between them. It’ll take some time before we see a new physical product + content combo thrive, and meanwhile the iPhone and its comps will be competing hard to stay the default device.

The new default seems to be that we’re not lonely as long as we’re streaming. We can view this entirely in a negative light and talk about how much the internet and media is contributing to the loneliness epidemic. Or we could think about how to create media for good. Companionship content can be less the quick dopamine-hit-delivering clips and more of this, and perhaps even truly social.

Long-form wants to become the conversational third space for consumers too. The “comments” sections of TikTok, YouTube and all broadcast platforms are improving, but they still have a long way to go before they become even more community-oriented.

I’m not an “AI-head” but I am more curious about what it’s going to enable in long-form content than all the short-form clips it’s going to help generate and illustrate, etc.

The foreground tends to be utilities or low-cognitive / audio effort (text or silent video). Tiktok is a foreground app for now, YouTube is both (and I’d say trending towards being background).

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?”

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.