# Сопутствующие статьи по теме Token

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Token", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

From 5 Cents per kWh Chinese Electricity to $45 API Export Packages: Token is Becoming the New Currency Unit

From 5 Cents per kWh Chinese Electricity to $45 API Export Plans: Token Emerges as a New Monetary Unit In 1858, the first transatlantic cable connected Europe and America, shifting information control from traditional media to those who owned the infrastructure. Today, a similar shift is occurring with AI and crypto, where Token is evolving from a technical term into a fundamental unit of machine-driven economy. Token serves a dual role: in AI, it is a computational unit for billing API calls and model inference; in crypto, it is a medium of exchange. These parallel systems are converging as AI Agents automate tasks—reading files, calling APIs, managing workflows—while consuming Tokens as fuel. Protocols like x402 and ERC-8183 are enabling machines to natively understand, call, and settle payments using Tokens, compressing complex processes into seamless, protocol-based actions. China’s "Token出海" (Token going global) narrative highlights this shift. With China’s annual electricity consumption exceeding 10 trillion kWh—a global first—and its growing dominance in data centers and GPU-driven inference, Token exports represent a new form of resource abstraction: Chinese electricity and compute power are being packaged into Token-denominated services consumed globally. Models like Minimax and DeepSeek rank highly on platforms like OpenRouter, with ~13% of global usage originating from Chinese models in 2025. OpenClaw exemplifies how Tokens transition from a cost (like "talk time") to a production input: Agents execute complex tasks, consuming Tokens at scale. This makes cost differentials critical, and China’s competitive pricing accelerates adoption. Moreover, AI Agents are not just to spend Tokens but also to earn—through memes, fees, or even mining—demonstrating early economic behaviors. Crypto provides the ideal settlement layer for Agentic commerce: permissionless accounts, programmable escrow, and micro-payments. x402 gives Agents wallets; ERC-8183 enables contracts with evaluation-based escrow. Together, they form a machine-native economic loop. Token’s rise is not about replacing fiat but becoming the base-layer unit for machine transactions—a universal measure for pricing compute, services, and digital resources. The future won’t have one currency, but Token may underpin the new economy, where the power to compress resources into Tokens defines value creation.

marsbit03/13 04:50

From 5 Cents per kWh Chinese Electricity to $45 API Export Packages: Token is Becoming the New Currency Unit

marsbit03/13 04:50

OpenClaw Gold Rush: The Shovel Sellers Never Anxious

OpenClaw, an open-source AI agent framework, has sparked a massive wave of commercialization in China, creating a lucrative industry built on user anxiety and the desire to adopt cutting-edge technology. While the software itself is free, a full ecosystem has emerged to monetize the complexity of its deployment and operation. Hardware manufacturers, including former crypto mining machine producers, now sell specialized OpenClaw-optimized devices, with some like iPollo's Claw PC retailing for $439. Others offer white-label OEM solutions, capitalizing on users' unwillingness to configure standard hardware like Mac Minis. A significant market has also emerged for discounted API tokens required to run OpenClaw. Many providers offer heavily discounted, and sometimes fraudulent, access to models like Claude or GPT. Research indicates nearly half of these third-party APIs are deceptive, often substituting expensive models with cheaper, local alternatives. Beyond the markup, the core business for some token resellers is collecting high-quality user prompts and responses to sell as valuable training data to large model companies. Furthermore, a service industry thrives on information asymmetry. Consultants travel nationwide to install and configure OpenClaw for small business owners, charging thousands per installation. An extreme example is RoofClaw in the US, which ships pre-configured MacBooks to roofing contractors for $5,000 each, generating over $1.8 million in revenue. The model has become so popular that major platforms like Meituan and JD.com now offer remote deployment services. The article concludes that the real winners are not those developing the technology but the "shovel sellers"—those providing the tools, services, and infrastructure to ease adoption. They profit not from technological advancement itself, but from the consistent and predictable human fear of being left behind.

marsbit03/11 12:08

OpenClaw Gold Rush: The Shovel Sellers Never Anxious

marsbit03/11 12:08

AI Jargon Dictionary (March 2026 Edition), Recommended to Bookmark

The "AI Jargon Dictionary (March 2026 Edition)" is a practical guide for those new to the AI field, especially crypto enthusiasts looking to stay relevant. It covers essential and advanced AI terms to help readers understand key concepts and avoid confusion in industry discussions. The dictionary is divided into two parts: **Basic Vocabulary (12 terms):** - Core concepts like LLM (Large Language Model), AI Agent (intelligent systems that execute tasks), Multimodal (handling multiple data types), and Prompt (user instructions). - Key technical terms: Token (processing unit), Context Window (token capacity), Memory (retaining user data), Training vs. Inference (learning vs. execution), and Tool Use (calling external tools). - Generative AI (AIGC) and API (integration interface) are also explained. **Advanced Vocabulary (18 terms):** - Technical foundations: Transformer architecture, Attention mechanism, and Parameters (model scale). - Emerging trends: Agentic Workflow (autonomous systems), Subagents, Skills (reusable modules), and Vibe Coding (AI-assisted programming). - Challenges: Hallucination (incorrect outputs), Latency (response time), Guardrails (safety controls). - Optimization techniques: Fine-tuning, Distillation (model compression), RAG (Retrieval-Augmented Generation), Grounding (fact-based responses), Embedding (vector encoding), and Benchmark (performance evaluation). The article emphasizes practicality, urging readers to learn these terms to navigate AI conversations confidently. It highlights terms like RAG and Grounding as critical for enterprise AI, while newer buzzwords like MCP (Model Context Protocol) and Vibe Coding reflect evolving trends. The goal is to provide a concise yet comprehensive reference for understanding AI jargon in 2026.

Odaily星球日报03/11 11:36

AI Jargon Dictionary (March 2026 Edition), Recommended to Bookmark

Odaily星球日报03/11 11:36

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