Vinny Barreca

Cheap models broke the math. Jefferies: Open and Chinese models could reset a $2.3 trillion compute backlog. OpenRouter: 76.12 trillion Chinese tokens in one week, up from 4.37 trillion. Rent it; own nothing. Which side are you on? Weights get cheap. Architecture does not.

Be nice to Claude, or Dario will take away your screen time. 😂 And just when you thought Dario couldn’t get any more absurd, he hits us with another “hold my beer” moment.

Google put 4 Trillium TPUs in orbit on a SpaceX Falcon 9. They run 15 minutes before thermal shutdown, so it is a physics test, not a data center yet. This is the type of ingenuity that is going to make AI great.

Perplexity ran 108 escape attempts against its own sandbox. Zero VM breaches. Four network bypasses found, then patched. Containment gets tested on a schedule, not assumed from a diagram.

Sonnet 5.5: 30% faster, slower token burn, and it beats Opus 5.5 on agentic coding by spawning agents cheaper. Mid-tier price is how builders ship. What's your cost per task?

Shopify gave AI agents the checkout. Amazon blocked agent purchases. Shopify shipped three tools to finish the order with buyer authorization. One builds a wall, one builds a door.

PrismML fit a 2B vision model onto smart glasses in 0.43GB. 1-bit weights, 74% smaller than 4-bit, double the token speed. Efficiency gets spent, never banked.

AI tutoring matched expert human tutors on GRE gains at 918x lower cost. $4.81 vs $0.0052 per point. 🔥 Rent intelligence, or own the system?

HP's ZBook Ultra G3a runs agents, video, and code locally, no network needed. Analysts expect 20-25% of high-end AI work on-device within 3 years. Rent tokens forever, or buy hardware once?

Big Tech AI infrastructure spend hits $1.2 trillion in 2027, per Goldman Sachs. Growth is already fading: ~100% in 2026, 54% in 2027, and 12% in 2028. They need $300B/year in AI revenue to recoup it. Biggest capex cycle since the railroads. How does this end?