Muskism; A Guide for the Perplexed, Quinn Slobodian & Ben Tarnoff, 2026
His (Musk’s) communication style had always been proleptic (refers to something that is anticipatory, happens before its expected time, or treats a future event as if it has already occurred. ) The logic of financial fabulism (a contemporary literary genre that weaves fantastical, mythic, or surreal elements into otherwise realistic everyday settings. It blurs the line between reality and the impossible, treating magical occurrences as mundane to explore profound human themes) treated imagined futures as already underway, allowing speculative claims to generate market effects before the underlying technology had matured. “Musk’s success is sustained by predictions of a technological sublime that’s only ever another decade away.”
On twitter, however, such predictions could produce financial effects instantaneously. In 2018, Must tweeted, “Am considering taking Tesla private at $420. Funding secured.” The number was a weed joke, but investors took him seriously: Tesla stock jumped 11 percent…In 2020, he posted “stock price too high imo” and Tesla dropped as much as 12 percent. In January 2021, he added “#bitcoin” to his Twitter bio and the cryptocurrency jumped 20 percent within an hour. This was attention alchemy at work. As journalist Marco D’Eramo observed, Musk’s followers were his “real capital”.
The most important site of cyborg symbiosis (concept heralds a future where biological intelligence and artificial intelligence converge, potentially mirroring the cooperative success stories found in nature.) was social media. “Facebook and Twitter and Instagram and all these social networks — they’re giant cybernetic collectives,” Musk told the podcaster Joe Rogan ins 2018. They didn’t just let people collectivize their thoughts but, more importantly, their feelings. The “success of these online systems,” Musk argued, is a function of how much limbic resonance (a neurobiological concept describing the capacity for deep emotional and physiological attunement between two or more people) they’re able to achieve with people.” Virality was driven by emotion. “The more limbic resonance, the more engagement.”
What made these collectives cybernetic was the fact they included computers as well as humans. And these computers were, in fact, learning from the humans. AI systems based on neural networks are trained to perform a particular task by finding patterns in large quantities of data. On the platforms, users supplied this data through their activity. “We’re all collectively programming the AI,” Musk explained.
Gradually, this process would result in smarter and smarter AI. “The percentage of intelligence that is not human is increasing, and eventually we will represent a very small percentage of intelligence,” said Musk. The ultimate legacy of the cybernetic collectives of social media would be humanity training its replacement. In a computer, a bootloader is a special program that helps initialize the system. Humanity, Musk told Rogan, was becoming “the biological bootloader of AI.”
But there was an interesting wrinkle to this theory. If our online interactions were fueled more by emotion than reason, then the AI systems that we were collectively programming would reflect that. The AI that learned from observing our behavior in the cybernetic collective would become “our id writ large,” Musk said. This was a view of advanced AI not merely as “superintelligence” but as an algorithmic embodiment of combined impulses and instincts.
One implication was that social media had immense importance for the future of the human race. If social media were the primary site of cyborg symbiosis, then a platform like Twitter was more than a place to crack jokes, troll rivals, or pump crypto and stocks. It was a place where the perils of superintelligence could be neutralized by dissolving ourselves into data. If we didn’t become AI, AI would eliminate us.
Is Big Tech a Bubble? Goldman Sachs;
- The AI Capex Loophole: Critics argue that Big Tech is funding their own “circular revenue”. Giant tech firms invest billions into AI startups, which then use that exact funding to rent cloud infrastructure from those same tech giants.
- Unsustainable Spending: Companies are heavily sacrificing cash flows and taking on massive debt to fund data centers and AI hardware. Some analysts from major banks warn that this mirrors the telecom overspending of the dot-com era.
- Historical Concentration: A handful of mega-cap tech stocks now make up an unprecedented share of indices like the S&P 500, leaving the broader market vulnerable to any industry pullback.