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Dear Readers,
The AI economy is shifting from spectacle to substance. What once felt like sci-fi hype is now running through the arteries of real markets—interest rates, chip exports, and even music charts. The Federal Reserve’s Powell says this isn’t a bubble, Apple quietly leans on Google’s Gemini, and an AI artist just broke into Billboard. Each headline tells the same story in a different accent: intelligence is no longer virtual—it’s capital, culture, and competition all at once.
In today’s issue, we trace these threads where hype meets hard economics. You’ll find the Remote Labor Index redefining how we measure “AI work,” new numbers revealing a $73 billion venture flood into startups, and rare-earth diplomacy between China and the U.S. hinting at a fragile balance beneath the boom. The undercurrent is clear: the age of synthetic intelligence is no longer about potential—it’s about power. Dive in.
In Today’s Issue:
🤑 The Remote Labor Index (RLI) indicates AI's current job readiness is minimal
🤝 China and the US reach a short-term rare earths deal
💸 VC funding floods AI startups with $73.1B in Q1 2025
📈 AI valuations are splitting
✨ And more AI goodness…
All the best,
Powell Declares AI Boom Real
Federal Reserve Chair Jerome Powell said the AI surge isn’t a speculative bubble like the 1990s dot-com craze because the companies driving it already show strong profits and real productivity gains. He emphasized that AI spending, especially in chips, data centers, and automation, is rooted in measurable economic output, not hype.
Apple’s Siri taps Google Gemini engine
Siri is reportedly being revamped by Apple Inc. to roll out in early 2026, and it will “lean” on Google Gemini for its AI-powered capabilities instead of OpenAIs ChatGPT.
AI Artist Xania Monet Hits Billboard Milestone
An AI-generated artist named Xania Monet debuted on the Billboard Adult R&B Airplay chart (entering at No. 30)- the first time an AI act has broken into a Billboard radio airplay chart.
PewDiePie goes all in on local LLMs. What a goat!
Remote Labor Index (RLI)
The Takeaway
👉 AI’s “job readiness” remains minimal, 2.5% automation rate so far.
👉 RLI benchmarks real productivity, not academic puzzles.
👉 Businesses should temper automation timelines with these findings.
👉 Tracking RLI helps spot when AI truly crosses from clever to capable.
AI benchmarks often live in sterile lab settings, but the Remote Labor Index (RLI) from Scale AI flips the script. It measures how well AI agents can actually complete real freelance jobs drawn from real marketplaces - writing, coding, design, and data analysis. Each task mirrors an authentic client brief, testing whether an AI’s work would meet professional standards.
The results are humbling: even the best models automate only about 2.5% of human-level remote work. That gap between demo-ready and deployable shows how far current systems are from reliably handling economically valuable tasks end-to-end. For developers and policymakers, RLI is a reality check—a new metric for progress toward generalizable, trustworthy AI labor.
Why it matters: It cuts through the hype by measuring economic usefulness, not just technical prowess. RLI exposes where AI still fails to replace skilled human work—and how much innovation remains ahead.
Sources:
🔗 https://scale.com/leaderboard/rli
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China-US Rare Earths Deal: Short-Term Relief, Long-Term Tension
China has agreed to pause for one year new export controls on rare-earth materials after a summit with Donald Trump, while still keeping prior restrictions in place. Rare earths (17 elements vital for EVs, defense, chips) are evolving from a niche supply chain issue into a strategic geopolitical lever.
VC Flood Fuels AI Valuation Bubble Fears
AI startups raised $73.1 billion in venture capital during Q1 2025, a record 57.9% of all global VC funding. This surge marks a turning point: AI is now a core macro-investment theme, not a tech niche. Yet the imbalance between capital inflow and proven cashflow signals bubble-like dynamics. Central banks and regulators face growing pressure to monitor systemic risk as speculative valuations spill into broader markets.
AI Valuations Split into Two Economies
A new survey of 565 AI firms finds widening divergence in valuation multiples. Core model developers still command extreme premiums, while vertical-application players (Fintech, HRTech, etc.) are normalizing toward traditional SaaS metrics. The shift signals investor maturity: capital is moving from frontier bets to proven business adoption. It also suggests a bifurcated AI economy, speculative at the infrastructure layer, pragmatic at the application layer.
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