MC.87: The Current Bittersweet Symphony of AI

GPT-5 launch perfectly captured the current moment in AI: sky-high expectations crashing into underwhelming reality. Sam Altman hyped it as something he'd "never want to go back from," posting Death Star images on social media. The anticipation felt like Christmas Eve for tech enthusiasts.

Then came the letdown. Users found GPT-5 insisting there were three "b's" in "blueberry" and mislabeling U.S. states with fictional names like "New Jefst" and "Miroinia." The model that promised PhD-level intelligence couldn't count letters or identify basic geography.

The backlash was swift. Gary Marcus called it "overdue, overhyped and underwhelming." Reddit users branded it "hot garbage." Even OpenAI had to quickly restore the previous GPT-4o model after user complaints about the new version's cold, robotic tone.

Behind the Curtain: Altman's Candid Moment

In a rare extended dinner interview, Altman admitted: "I think we totally screwed up some things on the rollout." Yet he also revealed the contradictions at AI's heart—while critics panned GPT-5, OpenAI's API traffic doubled and they're "out of GPUs."

Altman also confirmed we're in an AI bubble, comparing it to the dot-com era: "Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes."

The Economics Don't Add Up

The numbers tell a sobering story. OpenAI raised $8.3 billion by August—suggesting a burn rate that dwarfs any startup in history. At a $300 billion valuation, who could possibly acquire them?

Meanwhile, the supposed AI success stories are crumbling:

• Cursor, the AI coding darling, had to degrade its service and introduce a $200/month tier after Anthropic raised prices

• Character.ai and Windsurf weren't really "acquired"—their founders got paid billions while employees got nothing

• No major AI company has gone public or found a real exit strategy

The pattern is clear: these companies can't make money at scale, can't be acquired at their inflated valuations, and can't go public without revealing their unsustainable economics.

But don’t worry, Anthropic new round is “too popular”.

The Infrastructure Mirage

Perhaps most concerning is how AI capex has become a pillar of U.S. economic growth. According to analyst Paul Kedrosky, AI infrastructure spending now represents 1.2% of GDP and accounts for more than half of recent economic growth.

But this "boom" is really just four companies—Microsoft, Google, Meta, and Amazon—spending hundreds of billions on data centers for products that don't generate meaningful revenue. It's a private stimulus program built on hope rather than returns.

When this CAPEX spending inevitably slows (you can't build data centers forever), what happens to the economy that's become dependent on it?

The Scaling Law's End

The technical reality is equally sobering. The 2020 "scaling laws" paper that launched the current AI frenzy suggested models would keep improving as they got bigger. But that's clearly breaking down.

OpenAI's internal "Orion" model disappointed, leading to GPT-5's focus on "post-training improvements", essentially souping up existing models rather than building fundamentally better ones. It's like the difference between building a sports car versus adding racing stripes to a sedan.

The Bittersweet Reality

We're witnessing AI's bittersweet symphony: genuine technological progress shadowed by unsustainable economics, revolutionary potential undermined by fundamental limitations, and transformative promises colliding with disappointing reality.

The technology isn't worthless, GPT-5 does show improvements in coding and reduced hallucinations. But it's not the paradigm shift that justifies the hundreds of billions invested or the economic disruption it's causing.

As one observer noted, we're building "short-lived, asset-intensive facilities riding declining-cost technology curves", not century-spanning infrastructure like railroads, but rapidly depreciating assets that require constant replacement.

The symphony plays on, but the crescendo may be behind us. The question isn't whether AI will matter, but whether the current bubble can find a sustainable rhythm before the music stops.

Cheers,
Olivier

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1  Since we wrote this piece, previous models are now back for plus users