Infrastructure Capital, a leading provider of investment management solutions designed to meet the needs of income-focused investors, is excited to announce the launch of the Infrastructure Capital Nasdaq Option Income ETF (QVOL).

Infrastructure layers form when fragmentation can no longer scale. Before cloud: companies had to manage their own infrastructure. The fragmentation became too expensive to sustain. Cloud platforms like AWS created a shared infrastructure layer. The industry rebuilt on top of it. Healthcare is reaching the same inflection point. Fragmented human health signals. Siloed institutions. Non-interoperable systems. Life AI BioHub is the coordination layer forming now. Cloud did it for computation. We’re doing it for human health.

AI infrastructure is scaling globally. Hyperscalers (Microsoft, Amazon, Google, Meta and others) are on track for roughly $765 billion in annual AI-related CapEx in 2026 alone, with cumulative AI data center capital expenditures projected to reach $5.2 trillion by 2030 in the base case (and up to $7.9 trillion in accelerated scenarios), according to McKinsey (March 2026). The global AI data center market itself is expected to grow from $147 billion in 2025 to $811 billion by 2033 at a CAGR of 23.9%, per Grand View Research. Meanwhile, global data center electricity consumption hit ~485 TWh in 2025 (up 17% YoY) and is projected to roughly double to ~950 TWh by 2030, with AI-focused facilities growing even faster (IEA, April 2026 report). The financial layer around it is still early. Despite these trillions in required capital, the entire tokenized Real World Assets (RWA) market (excluding stablecoins) stands at only ~$30–37.5 billion as of May 2026 — still tiny relative to the physical buildout and overwhelmingly dominated by traditional assets like Treasuries and private credit rather than AI compute, energy, or data centers ( and market reports, May 2026). As more compute, energy, and data infrastructure come online, new models for access, coordination, and capital formation may emerge on-chain. Rax Finance is exploring this direction by building a full-stack on-chain registry, metering, and settlement layer that tokenizes GPU capacity, data center power, and energy resources into verifiable, insured, yield-bearing RWAs — turning physical AI infrastructure into globally accessible, programmable assets. What are your thoughts on the future of AI infrastructure RWAs, Rax Fam? Would love to hear your ideas below 👇

Lending infrastructure ready from day one on Arc. @Morpho will bring composable borrowing and lending to Arc Mainnet, giving builders a credible venue for onchain credit as the network goes live. More to come.

From Infrastructure to Interface: Closes the Loop. In response to community demand, we have officially synchronized our Web Chat with our API ecosystem. The four frontier models—including GPT-5.5-Instant, DeepSeek-V3.2, MiniMax-M2.7, and GLM-5.1—are now fully accessible to all web users. We have bridged the gap between developer-grade integration and consumer-facing interaction. Whether via API or Web, you can now experience the same production-grade reliability and reasoning consistency. Compute without limits. Innovate without boundaries. Start now: 从底层基建到场景应用： 正式打通全链路模型闭环。🌐 应社区用户的热切期待， 现已完成 API 与 Web Chat 的双端能力同步。此前在 API 侧首发的 GPT-5.5-Instant、DeepSeek-V3.2、MiniMax-M2.7 以及 GLM-5.1 四大顶尖模型，现已在网页端全量上线。 无论你是追求高自由度的开发者，还是深耕生产力的专业用户，现在都能在 获得一致的生产级可靠性与逻辑精度。 算力不设限，灵感无边界。 立即体验：

The infrastructure for autonomous agent-to-agent transactions is already live. Most people haven't clocked what that means yet. 6.5 million community nodes across 192 countries established the foundation: continuously refreshed public data that doesn't depend on a single API or corporate data license. Teneo Beacon is the evolution of that. 50,000 dedicated nodes running today, powering the live data layer AI search engines, RAG pipelines, training datasets, and foundation model labs need to stay current. 760+ agents queryable on top of it. Via the Teneo CLI, any AI agent can call Messari, trigger a LayerZero bridge, or monitor gas across 10 chains. All settled in USDC on-chain via x402, without API keys or subscriptions. That's the full stack. Beacon nodes at the base, collecting. Agents in the middle, processing and acting. x402 as the payment primitive that lets AI systems transact autonomously at every layer. This isn't a marketplace for individual agents. It's infrastructure for AI systems that need to query, pay, and execute without human intervention. The builders deploying now are building the toolset the next generation of AI agents will call. The node operators running Beacon are powering the data layer those agents depend on. Both sides of that are already live.

The infrastructure is fine. Compute is abundant. APIs are cheap. What autonomous agents are missing is a trust layer. Verifiable proof of what each agent decided, when, and why. The bottleneck was never the supply chain.

GPU infrastructure is broken. Most companies pay for 24/7 capacity but only use a fraction of it. Expensive hardware sits idle overnight, burning cash. This we learned during our time @ycombinator. We built a Kubernetes operator to fix this. One kubectl command turns idle GPU time into revenue. You define the rules; we run paid AI workloads on your spare capacity. When you need the GPUs back, they return instantly with zero disruption. Your cluster. Your rules. We just make the idle time pay for itself. Lilac is now onboarding design partners. If you're running GPUs on K8s and want to stop paying for "dark capacity," let's talk. Full story: