“We’re at the beginning of a completely different era of computing.” – Rodrigo Liang, co-founder & CEO of @SambaNovaAI. Full interview👇 piped.video/watch?v=TzfeDotn… #SambaNova #NYSEWired #theCUBE

“No, no, no, no, no, no, no, no. There’s nothing cool about a tennis match that finishes at 3:33 a.m. It’s ridiculous.” Ben Shelton defeats Carlos Alcaraz in a glorious match that finished at an inhumane hour. Columnist @jasongay asks: Why does tennis keep burying its best product? on.wsj.com/3TlobO4

Today, we’re partnering with Nscale to deploy up to 100,000 GPUs on the NVIDIA Vera Rubin Platform We're committing $3.5 billion initially, with plans to scale beyond $6 billion Bringing a robot into every home demands compute at an unprecedented scale

The story of ClickHouse is truly insane. Started as an open-source project; scaled into the fastest-growing database product ever. Year 1: $0 Year 2: $12M Year 3: $50M Year 4: $200M Year 5 (not complete): My bet is $450M. My notes from our discussion with @ceo_clickhouse below 👇 1. Are Large U.S. Enterprises Scared to Work With Frontier Model Providers? Large enterprises remain skeptical of “zero data retention” claims and wary of sending proprietary source code to frontier labs due to IP indemnification and data leakage concerns. Rather than exposing production code, companies may limit frontier model usage to less sensitive workflows like code review while turning to open-weight alternatives for critical data. 2. How Do You Assess Defensibility and Moat in Companies That Scale Faster Than Ever Before? When an application scales from zero to $100M in ARR in a single year, investors must rigorously question its underlying moat. Hypergrowth without high switching costs leaves companies vulnerable to rapid churn as customers move effortlessly to the next model or tool that leapfrogs the incumbent. 3. How Does This AI Cycle Compare to Prior Technology Shifts and Transitions? Unlike the gradual adoption curves of the internet and mobile eras, the current AI wave is accelerating at an unprecedented pace. Agentic experiences are maturing rapidly, driving explosive revenue growth and placing historically unique performance demands on underlying data infrastructure. 4. What Job Does Not Exist Today That Will Be Very Prevalent in Five Years? A critical new corporate role could be an AI finance function dedicated entirely to managing token consumption and resource allocation across the enterprise. But the role may ultimately be short-lived as autonomous AI agents increasingly manage their own infrastructure spend and budget execution. 5. What Should Investors Be Worried About Today That They Are Not? The biggest overlooked risk in AI today is revenue durability. While infrastructure software benefits from high switching costs, agentic applications can have exceptionally low barriers to switching, raising questions about long-term retention as models and products continually leapfrog one another. 6. Why Revenue Concentration Is a Real Concern Operators and investors should treat revenue concentration as a critical risk, with any single customer or vertical accounting for more than 10% of revenue representing significant exposure. Sustainable enterprise value requires a diversified customer base so losing one account never threatens the company’s overall growth trajectory. (links in comments)