While it’s interesting to see renderings in past styles graphic design, ultimately it’s going to ring false. Even if it’s executed well it’s just a costume or pastiche, with no real connection to the style.
What made these historical design movements actually memorable was usually a set of newly-possible techniques joined with young people with a set of shared community values.
So if you want to make something that will read as authentically “2026” to future generations, you should make brainrot. :-)
That fairly insular community pretty much gave up on commercial success in order to be insular. But the commercial forces were not happy being commercially successful, so they decided to disturb even their insular and commercially-unviable activities.
(academic.) Unfortunately the overwhelming majority of outsiders are missing core knowledge (or are cranks), so the optimal prior from a time management perspective is to ignore them. AI just makes engaging more costly because there’s more volume and it’s harder to get signal on whether they know what they are talking about.
It was donated without CCDs or electronics, which is what makes the difference between earth and space observation satellites. NASA only got the body and optics (mirrors), they had to provide their own sensors.
Yes. But there is also no other choice for people in these professions. The underlying job has been automated already. What's left is automating the last leg.
If you consider a 5-year outlook, it is also a very temporary job unless you're like a specialist neurosurgeon or something, as one of the examples in that article shows:
> The on-again, off-again nature of the work is not just the result of company culture; it stems from the cadence of AI development itself. People across the industry described the pattern. A model builder, like OpenAI or Anthropic, discovers that its model is weak on chemistry, so it pays a data vendor like Mercor or Scale AI to find chemists to make data. The chemists do tasks until there is a sufficient quantity for a batch to go back to the lab, and the job is paused until the lab sees how the data affects the model. Maybe the lab moves forward, but this time, it’s asking for a slightly different type of data. When the job resumes, the vendor discovers the new instructions make the tasks take longer, which means the cost estimate the vendor gave the lab is now wrong, which means the vendor cuts pay or tries to get workers to move faster. The new batch of data is delivered, and the job is paused once more. Maybe the lab changes its data requirements again, discovers it has enough data, and ends the project or decides to go with another vendor entirely. Maybe now the lab wants only organic chemists and everyone without the relevant background gets taken off the project. Next, it’s biology data that’s in demand, or architectural sketches, or K–12 syllabus design.
As a young Midwestern nerd in the 90s, getting one of those cow boxes delivered to our home was better than Christmas. (Christmas happens every year!). Somehow I can still remember the new computer smell…
I went from an unknown intel processor (pre-celeron) I think doing like ~75mhz and 2gb hard drive w/ 8mb ram to a gateway computer P4 w/ 1.3 or 1.4 GHZ, 40gb HD, and 128mb of ram - it was insane the jump. I do give credit to that old machine as I learned so much trying to optimize that processor to do things my friends were doing on their faster machines. Crazy times.
What made these historical design movements actually memorable was usually a set of newly-possible techniques joined with young people with a set of shared community values.
So if you want to make something that will read as authentically “2026” to future generations, you should make brainrot. :-)
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