t Picture winner and my current answer for favorite movie (it changes every week), was cut on Final Cut Pro.
The same concept extends to 3D creation. Minecraft and Roblox have broadened the definition of game developer. Overwolf makes it easy to build in-game apps and mods.
And we’re now seeing AI drive a Cambrian explosion in creativity. Jasper.ai, Copy.ai, and Lex give writers superpowers. Midjourney lets anyone with a Discord account create beautiful AI-generated images—and v4 is dramatically better than v3. As my colleague Cat shared last week, in these v3 (left) and v4 (right) outputs for the same prompt—“A penguin in Venice”—we get much better results in v4. We no longer have penguins with two beaks and three legs.
Ben Thompson had Midjourney’s David Holz on Stratechery recently for an interview. Holz shared that about 10% of cloud costs are going into training, while 90% are going into the inference to the users making images. Midjourney is using more than 10,000 GPUs, making it one of the largest GPU users in the world.
I found this excerpt particularly interesting:
Holz: Our inference usage is weird in that some users are willing to wait and some don’t have to wait and some won’t wait. And then there’s a large latency, but the usage pattern is really weird. So we did a lot of innovative logistics stuff early on to make the costs low. So right now, if you make an image, there are eight different regions of the world that the image might get made in, and you have no idea. It might get made in Korea or Japan or the Netherlands or something. It’s going to eight different regions that the GPUs are balancing between. Where it’s really cool is because we’ll use a lot of the GPUs in Korea while it’s nighttime and everyone’s sleeping there, no one’s using them. We can kind of load balance. You can basically race the darkness of the night across the earth.
We’re still in the early innings of AI applications, and every year leaps are being made. GPT-3 came out less than three years ago with ~200 billion parameters; the upcoming GPT-4 has ~1,000,000,000,000 (a trillion) parameters. AI will accelerate production by an order of magnitude, just as analog technologies like the linotype accelerated production a century ago.
At the same time, AI-powered production will converge with more immersive forms of content, like VR and AR. (One of my favorite quotes is Epic Games’s Tim Sweeney on VR: “I’ve never met a skeptic of VR who has tried it.”) The next decade will see a proliferation of information and content unleashed by new tools.
Organization of Content & Information
We already covered the creation of the filing cabinet, which was essential to organizing information. A related invention was that of the index card. Before index cards, information was stored in cumbersome bounded ledgers. Around the turn of the century, information management via cards of uniform size and weight took hold; cards were stored in drawers, each representing one unit of information, and could be arranged sequentially or alphabetically.
Founded in 1895, The New York Public Library became the city’s central nervous system of knowledge. The largest free public library system in the country, it housed eight million books and one million items of research by 1913, using recent innovations like the Dewey Decimal system to catalog everything. The card-based systems underpinning the library were the databases of the analog age.
An early version of a search engine, meanwhile, took place at The New York Times headquarters. Staff on the second floor fielded phone calls from a curious public, providing answers to their questions. One clip, for instance, shows a woman answering a call from a member of the public.
“Which player had the highest batting average this year?” the caller asks.
“That would be Bill Terry, at .401,” the woman replies.
The caller thanks her and hangs up. Seventy-odd years later, Google emerged. And now, as Google turns 24, many young people instead turn to TikTok and Instagram for search: 40% of Gen Zs prefer searching TikTok and Insta over