My AI bags need the Cerebras IPO to pop. I went to @HyperliquidX to figure out grey market on where it might open in a few hours. IPO price $185, so indicating a ~50% pop. Long live perp DEXs!!!

Stocks I’m watching $dgxx - cerebras ipo sentiment play $wolf - hold 65 and might see continuation for a parabolic short squeeze. $oust - robotics sector heating up ? $almu - possible death spiral

Altimeter CEO Brad Gerstner said on CNBC during the $CBRS Cerebras IPO that “we’re in the age of inference,” arguing AI is rapidly shifting from training models to generating tokens efficiently at scale. He tied this directly to Jensen Huang’s comments about inference demand potentially scaling “1 billion x,” reinforcing the bull case for inference infrastructure across $AMZN, $MSFT, $GOOGL, memory, networking, and AI cloud platforms. Gerstner also said the successful Cerebras IPO could pave the way for more AI infrastructure IPOs in coming years, including potential offerings tied to SpaceX, OpenAI, and Anthropic.

The next AI war won’t be about training models. It’ll be about: ➡️ Inference costs ➡️ Compute shortages ➡️ Scaling AI profitably Following Cerebras’ IPO, @RodrigoLiang joined @Bloomberg with @mattmiller1973 and @daniburgz to explain why inference could become the biggest business in tech. Enterprise AI demand is exploding. The infra race is just getting started. Watch here ⤵️

Jensen called this “probably the single most important chart for the future of AI factories”. Y-axis is “Throughput” (total volume) while X-axis is “Token Speed” (more tokens per second = more interactivity for a user + more context + more reasoning). Cerebras IPO very much about the chart. Firms market and price token offerings on those two variables, which are in tension. A free tier typically is high throughput but lower token speed. Meanwhile, the priciest tier would have lower througput but high-value tokens (eg. research, coding) SemiAnalysis makes the analogy of a “bus vs a Ferrari: you can choose to serve lots of users slowly, a single user quickly, or anything in between.” Nvidia’s challenge is to build systems that lift the entire line up and to the right. Jensen says Vera Rubin architecture improves revenue opportunity 5x vs. Blackwell. Then, if you add Groq to Vera Rubin, that revenue opportunity is up 10x vs. Blackwell. Groq is Nvidia’s option for delivering the higher value tokens at speed, which is the same market that Cerebras is targeting. Cerebras is attacking the problem with a massive, single-wafer design. Meanwhile, Groq uses multiple, smaller, connected chips and a specialized processor architecture design (Language Processing Unit aka LPUs).