Silicon Valley has forgotten what normal people want

One of the most mortifying things about knowing a lot of techies is listening to them tell me excitedly about some very important discovery that they believe they have made. Recently, I ran into an acquaintance of mine, who began talking my ear off about an amazing discovery he’d made with LLMs. Knowledge, it turns out, is structured into language! You could put one word into ChatGPT and it might understand what you wanted, or make up a word and see if it understood what you meant! These amazing new tools have revealed that the English corpus contains so much about its speakers!

Silicon Valley has forgotten what normal people want

What NFTs, AI and the metaverse tell us about “thought leadership”

He concluded that LLMs are a discovery on par with writing.

Regular humans hit on this idea about a century ago; my most generous interpretation of what he was telling me was that he’d hit on a kind of naive, confused version of Structuralism; Saussure via a game of telephone. (There has been recent work on a similar point, which argues that one needs to understand LLMs via literary theory, but it starts with Saussure.) I tried to get out of the conversation as quickly as I could, not least because he seemed frustrated that I didn’t see things exactly as he did — a new behavior and likely a symptom of LLM overuse.

There is a certain amount of hubris required to throw oneself at an unsolved problem. But elsewhere, that hubris is a liability.

Not every discovery that’s new to you is actually new. For instance, there’s Elon Musk marvelling at the complexity of hands; I could point to a variety of disciplines for which this is 101-level stuff: artists, who have to figure out how to draw them; surgeons, who have to figure out how to operate on them; musicians and magicians, who rely on extremely fine motor skill to produce their work; neuroscientists and psychologists, who doubtless encountered the cortical homunculus early in their careers. Or Palmer Luckey claiming that “no one has done a postmortem” on the One Laptop Per Child computing project — because he didn’t know there’s a whole book about it called* The Charisma Machine.*

At its most absurd nadir, one is reminded of Juicero, a company that sold a $400 juicer that did the same work as squeezing its proprietary juice packs with one’s bare hands.

Look, discovering something that’s new to you is exciting — ask anyone who listened to me yell about the joys of European (higher-fat) butter — but you can’t take for granted that something that’s new to you is new to *everyone. *These things have in common a certain incuriosity that I have found endemic among a certain kind of tech enthusiast, particularly the ones who are most interested in startups and entrepreneurship. Perhaps they have been so siloed that they did not realize their “discovery” was well -known elsewhere, or perhaps their self-conception is that they are the smartest, and if they don’t know something, no one knows it.

There is a certain amount of hubris required to throw oneself at an unsolved problem — you have to believe you can solve it. But elsewhere, that hubris is a liability. It leads you to do weird things, like announce that Freud invented introspection and that it is a bonus that you simply do not engage in it.

Within recent memory, people who made software and hardware understood their job was to serve their customer. It was to identify a need, and then fill it. But at some point following the financial crisis, would-be entrepreneurs got it into their heads that their job was to invent the future, and consumers’ job was to go along with that invented future. My guess is that they’re aping what they thought Steve Jobs was doing when he, for instance, got rid of the optical drives on the MacBook Air.

But Steve Jobs, famously, failed at inventing the future in the 1980s and got booted from Apple. We all know how things changed when he came back. But the iMac, the iPod, the iPhone were built with a need in mind. The iMac won because it was easy to use. The iPod was easier to take with you than a CD player and a stack of CDs. (It also was a way to play the MP3s you might have illegally downloaded.) The iPhone had the App Store, which expanded its utility well beyond any other mobile device.

At some point, our Silicon Valley overlords forgot that in order for their vision of the future to be adopted, people had to want it.

Some of this was luck — introducing the right product at the right time. But each product offered consumers a distinct value proposition. Sure, early adopters jumped on each of these things because they were cool, but the uncool masses don’t care about that. They’ll buy something if it improves their life in a distinct way.

In the place of problem-solving technology, companies have jumped on successive bandwagons like NFTs, the metaverse, and large language models. What these all have in common is that they are not built to really solve a market problem. They are built to make VCs and companies rich. NFTs, like crypto, let VCs quickly unload investments with abbreviated lockup periods. The metaverse promised to enrich companies like Facebook by having people move all their socializing online, where it could be surveilled and monetized. In addition, Facebook’s metaverse required the purchase of hardware, which would then need regular upgrades.

At some point, our Silicon Valley overlords forgot that in order for their vision of the future to be adopted, people had to want it. That’s why NFTs, the metaverse, and the Oculus and Vision Pro never really found their customer base. AI is, admittedly, more useful — it’s good for organizing large swaths of data, for instance. LLMs have had widespread consumer adoption, at least as long as they remain free. But there is only really one customer for LLMs that can justify the massive cash incineration process that was required to build them: the US government.

There can only be a few winners on government contracts, though. So we are now treated to the spectacle of watching AI companies scramble. OpenAI is perhaps the funniest, because it is attempting to position itself as a consumer product.

The people who tell us that AI will dominate our future and take our jobs are the people who are hoping that will be true.

Consider Sam Altman telling the world that he needed ChatGPT to tell him how to raise a baby. You exist. I exist. Our parents did not have LLMs, or even AI, and yet somehow we survived our childhoods, as did almost everyone else we knew growing up because childhood death rates in the US have been extraordinarily low — compared to most of the rest of human history — for decades.