CoinGate:波场TRON占其Q2总订单的32% 领先其他区块链

币界网Publicado a 2024-08-05Actualizado a 2024-08-05

币界网报道:

加密支付服务商CoinGate发布的数据显示,波场TRON占据其二季度总订单的32%,领先于其他区块链。

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作为重要的全球支付网络,凭借安全、高效、用户友好等特点,近年来波场链上活跃度正持续提升。截至目前,波场TRON账户数突破2.48亿,交易总数突破81亿,总锁仓量(TVL)超207亿美元。此外,波场TRON拥有行业领先的用户活跃度,TVL和链上稳定币总市值均高居全球公链第二,并已承载了价值超13万亿美元的交易。

未来,波场TRON将持续打造更强大、更友好、更多元的生态,继续普惠全球用户。

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After Missing the 20x, I've Found a 'Dumb' Method for AI Investing

**Missing the 20x Opportunity: A Simple 'Dumb' Approach to AI Investing** The AI boom, driving NVIDIA's revenue from $60B to $216B in two years, creates immense investment pressure. However, like the internet bubble of 2000, the largest AI opportunities likely lie ahead, perhaps after a correction. Instead of rushing in now or waiting paralyzed for a crash, the author proposes a third way: building a "knowledge warehouse" by systematically mapping the AI industry to be ready when opportunities arise. The core of the strategy is understanding AI's four-layer value chain: 1. **Compute Infrastructure (The "Engine"):** This foundational layer, where all money eventually flows, includes: a) **Chip Design:** NVIDIA's dominance via its CUDA ecosystem, b) **Chip Manufacturing/Packaging/Memory:** TSMC's near-monopoly in advanced manufacturing and SK Hynix's lead in High Bandwidth Memory (HBM), c) **Optical Interconnects:** Essential for large-scale AI clusters (e.g., Lumentum, Coherent), d) **Cooling & Power:** Critical for high-density AI data centers (e.g., Vertiv), e) **Servers/Data Centers & Cloud Platforms:** The physical and virtual wholesale providers. 2. **Models & Tools (The "OS"):** The competitive layer of foundation models (OpenAI, Anthropic, Google, Meta, xAI), now generating real revenue. A key shift is the center of gravity moving from **Training** models to **Inference** (running models), which demands different chip characteristics and could challenge NVIDIA's monopoly. 3. **Middleware & Platform ("The Glue"):** Connects models and applications (e.g., Scale AI, Hugging Face). This layer could explode if applications take off. 4. **Vertical Applications ("The Cash Register"):** Where AI meets end-users (e.g., enterprise AI, coding tools, medical AI, robotics). A critical cross-cutting constraint is **Energy**, as AI's massive power consumption drives investment in nuclear and other energy infrastructure. The author identifies four key questions for further research: 1) How will the shift from Training to Inference reshape the competitive landscape? 2) With tech giants spending over $600B on capex, where is the ROI from AI applications? 3) What are the under-the-radar opportunities in the "second" and "third" circles of the value chain (e.g., cooling, specialty foundries)? 4) How will geopolitics (e.g., U.S.-China chip restrictions) bifurcate the supply chain? The conclusion is that missed opportunities stem from insufficient research, not slow timing. By methodically studying each layer—its business models, competition, and valuations—investors can build the "killer intuition" needed to act decisively when the market presents its chance.

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After Missing the 20x, I've Found a 'Dumb' Method for AI Investing

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