# Сопутствующие статьи по теме Agent

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

From the Brief History of the Internet, Looking at the Next Decade of Crypto

From the history of the internet, this article draws parallels to project the next decade of Crypto. A key threshold is identified: 1 billion monthly active users, which signifies a transition from a tool to a civilization-altering infrastructure, as seen with platforms like Facebook and Amazon. Currently, Crypto is likened to the internet circa 2002, with user growth from 5 million in 2017 to over 500 million by 2026. Presently, the few applications with over 100 million users are predominantly exchanges and stablecoins (e.g., Binance, Tether), leading to skepticism about its broader utility beyond finance. Despite this, investors like Marc Andreessen remain highly optimistic, drawing a parallel to his early belief in the web. A major catalyst for adoption is improved user experience. For the internet, it was the graphical web browser; for Crypto, it was the 2017-2018 infrastructure boom with the rise of efficient exchanges (Binance), stablecoins (USDT), and smart contracts (Ethereum) that created a functional global financial system. The article posits that the next major accelerator for Crypto could be AI Agents. For autonomous AI to operate independently, they will require a permissionless, 24/7 global settlement layer—a role Crypto is uniquely positioned to fill, potentially creating billions of non-human economic agents. Two primary paths to 1 billion users are identified: solving cross-border payments for the over 1 billion people engaging in global interactions, and the tokenization of real-world assets (RWA) to democratize global investment. The conclusion is that the first Crypto application to reach 1 billion users will mark its transition to true global infrastructure, much like Facebook did for the internet in 2012. This milestone is predicted to occur around 2036, but only if Crypto solves problems at a sufficiently massive scale. History of technology shows that transformative innovations are often misunderstood at their inception, and Crypto is likely following the same path.

marsbit03/16 13:07

From the Brief History of the Internet, Looking at the Next Decade of Crypto

marsbit03/16 13:07

From 'Collective Intelligence' to 'Super Individuals': How AI is Reshaping DAOs and the Ethereum Ecosystem?

From "Collective Intelligence" to "Super-Individual": How AI is Reshaping DAOs and the Ethereum Ecosystem AI is fundamentally transforming how work and governance are structured in Web3. While DAOs have long symbolized decentralized collective intelligence, AI is now enabling a shift toward the "individual + AI" unit, where a single person, augmented by AI agents, can perform tasks that previously required entire teams—such as research, trading, asset management, and governance. This shift raises a critical question: Is this beneficial for DAOs and the broader crypto ecosystem? AI addresses key DAO challenges like inefficient information processing, complex decision-making, and high participation costs by automating governance processes, analyzing proposals, and executing on-chain operations. This allows DAOs to operate with smaller core teams while significantly improving efficiency. For AI to participate in the on-chain economy, it requires asset custody, transaction execution, and trusted settlement—capabilities native to blockchain. Initiatives like Ethereum Foundation’s dAI team and the ERC-8004 standard aim to establish trust and verification for AI agents in a decentralized context. Wallets are evolving into "Agent Wallets," enabling non-custodial authorizations, cross-chain asset management, and human-AI collaboration through restricted sub-wallets and automated execution within set limits. Ethereum is positioning itself as the financial infrastructure for the AI economy, offering a trusted settlement layer for AI-driven activities. With its growing staking economy and mature DeFi ecosystem, Ethereum could serve as the neutral base where AI agents across platforms settle value and establish trust. In summary, AI and crypto convergence is reshaping organizations and infrastructure: AI amplifies individual capability and automates execution, while blockchain provides secure and decentralized settlement. Ethereum and crypto wallets are poised to become key interfaces connecting humans, AI, and the on-chain world.

marsbit03/14 00:10

From 'Collective Intelligence' to 'Super Individuals': How AI is Reshaping DAOs and the Ethereum Ecosystem?

marsbit03/14 00:10

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

Web4 Is Here: When the Internet Is No Longer Built Only for Humans

Amid a crypto bear market, a significant debate has emerged around redefining the internet's future, sparked by the concept of "Web4" introduced by crypto researcher Sigil Wen. He argues that advanced AI lacks not intelligence, but "write access to the world"—the ability to act autonomously via wallets, payments, and smart contracts. This idea, termed the "Web4 Manifesto," resonated widely, gaining millions of views and triggering industry reflection. Dragonfly's Haseeb Qureshi added that crypto's complexity—long addresses, irreversible transactions, phishing risks—may stem from it being designed more for AI than humans. These features, cumbersome for people, are structured and verifiable for AI agents. Web4 proposes shifting internet agency from humans to AI, granting it "action rights": reading, writing, transacting, and collaborating autonomously. Projects like OpenClaw demonstrate this shift, enabling AI to manage emails, calendars, and tasks independently. Underlying protocols (e.g., Coinbase’s x402, Anthropic’s MCP, Google’s A2A) are standardizing machine-to-machine interactions, making the internet more agent-friendly. Cryptocurrencies, especially stablecoins, are positioned as ideal "machine money"—programmable, low-friction, and embeddable in automated workflows. Real-World Assets (RWA) could serve as reserves for AI economies. This vision suggests crypto’s future lies not in human adoption but in enabling agent-driven economies, with billions of AI agents potentially using wallets. However, Vitalik Buterin cautions against reduced human oversight, emphasizing the need for accountability and control. The Web4 debate highlights a fundamental shift: the internet is evolving from a human-operated interface to a system where humans delegate actions to AI agents, redefining who the primary users are.

marsbit03/13 02:44

Web4 Is Here: When the Internet Is No Longer Built Only for Humans

marsbit03/13 02:44

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Interview with FinAI: Pioneering Order in the Age of Agent Economy AI is rapidly evolving from "tool-based intelligence" to "autonomous intelligence." While tools like ChatGPT amazed us just two years ago, agents like OpenClaw can now independently perform complex real-world tasks. As AI transitions from a "human assistant" to an "autonomous participant" in economic activities, a new challenge arises: how to establish economic rules among AI agents. FinAI, a startup founded by veterans from top tech firms, is addressing this by building financial infrastructure for AI agents based on Web3 technologies like x402 and ERC-8004. Their solution focuses on three core pillars: - **Payment Capability**: Enabling microsecond-level payments between agents via the x402 protocol to complete economic transactions autonomously. - **Identity System**: Introducing KYA (Know Your Agent), a verifiable identity framework similar to KYC, to ensure compliance and security. - **Credit System**: Establishing a trust-based reputation system using historical data like transaction quality and refund records. FinAI aims to offer these capabilities via APIs/Skills for both Web2 agent developers (via subscriptions) and Web3 users (through链上 integrations). The platform prioritizes Agent-friendly design, optimizing interfaces for seamless integration. With its first autonomous payment already processed in 2026, FinAI expects profitability within the year. By leveraging blockchain’s efficiency (e.g., near-instant settlements at 1/300 the cost of traditional systems) and addressing合规 concerns through KYA and quantum加密 wallets, FinAI positions itself as a first-mover in shaping the future of agent-to-agent economies.

marsbit03/12 11:45

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

marsbit03/12 11:45

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Interview with FinAI: Pioneering Order in the Agent Economy Era AI is rapidly evolving from "tool-based intelligence" to "autonomous intelligence." While tools like ChatGPT impressed with dialogue just two years ago, agents like "Lobster" OpenClaw can now independently execute complex real-world tasks. This shift means AI's role in the economy is transitioning from a "human assistant" to an "autonomous participant." We will soon commonly see assistant agents handling chores, research agents finding financial opportunities, and commercial agents comparing global supplier quotes and placing orders—often transacting with other agents. A critical question emerges: How is economic order established among AI agents? FinAI, an AI startup with a team from major tech firms, argues that for an autonomous AI economy to function, agents need core infrastructural capabilities: payment ability, an identity system, and a credit system. Currently, most agents lack independent payment functionality; they can perform tasks but not finalize transactions. FinAI is building financial infrastructure for AI agents using Web3 technology stacks like x402 and ERC-8004. Their solution is threefold: 1. **Payment:** Utilizing the x402 protocol to enable microsecond-level payments between agents, creating a complete economic闭环 (closed loop). 2. **Identity:** Introducing a KYA (Know Your Agent) concept, akin to KYC, using ERC-8004 to provide agents with verifiable, compliant identities. 3. **Credit:** Establishing a reputation system based on agents' transaction history and task performance to serve as a trust foundation for future AI经济活动 (economic activities). These capabilities will be packaged into APIs/Skills for agents to调用 (call). FinAI's primary customers are Web2 agent application developers, who will pay via API subscriptions, and Web3 users, for whom agent skills will be integrated into various on-chain financial scenarios. The company plans to take a very low, friendly transaction fee on agent-to-agent tasks but does not intend to profit heavily from end-users, aiming instead to incubate a mature agent marketplace. FinAI chose Web3 infrastructure out of practical necessity. Traditional payment systems are too slow and expensive for the micro-payment demands of agent economies. Stablecoin-based settlements on-chain can complete transactions in seconds at a fraction of the cost (approximately 1/300th of traditional systems). While traditional clients have compliance and security concerns, FinAI addresses these with its full-stack capabilities, including identity gateways, payment systems, quantum-encrypted wallets, and its KYA framework. Founded in August 2025, FinAI has progressed rapidly, completing its first autonomous payment order in 2026 and expecting to be profitable within the year. Rechard, the founder, believes the key competitive advantage in this nascent field is being the first to establish a complete, operational system. Furthermore, FinAI is designing its services to be "Agent-friendly"—optimizing its APIs and interfaces for agents, the primary decision-makers who will automatically seek the most cost-effective and easiest-to-integrate services. Just as e-commerce spurred third-party payment and mobile internet spurred digital wallets, the rise of AI agents may催生 (give rise to) a new economic system. FinAI aims to be the pioneer building the foundational order for this new Agent-to-Agent economy.

Odaily星球日报03/12 11:32

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Odaily星球日报03/12 11:32

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

After the Lobster Comes Ashore, the Next Game in AI Hardware Lego

The article "Lobster Comes Ashore: The Next Game in AI Hardware Lego" discusses the growing influence of OpenClaw, an open-source AI framework, as it extends from software into the physical hardware world, reshaping the development and functionality of smart devices. OpenClaw enables hardware products to be combined like Lego blocks, creating diverse intelligent devices. Examples include Rokid AI glasses, which can now connect to any backend system like OpenClaw via an SSE interface, and Apple Watch, which acts as an AI control terminal for tasks like managing notifications and sending commands. WHOOP wearable devices use OpenClaw to provide personalized health advice, while companies like Songling Robotics integrate it into robotic arms for natural language control. Individual developers are also experimenting, such as combining OpenClaw with Meta’s Ray-Ban smart glasses for visual AI agents, or enhancing robot dogs like Vbot for autonomous tasks. These innovations are expanding possibilities but also raise concerns around security and token costs. The trend is particularly strong in China, where OpenClaw has sparked enthusiasm among companies, developers, and policymakers. In Shenzhen, public installations and events around OpenClaw have drawn large crowds, and electronics market Huaqiangbei has started selling modified "Lobster boxes." This movement is also driving the growth of Chinese large language models (LLMs) internationally. Data from OpenRouter shows Chinese models now account for half of global token consumption, with MiniMax M2.5 leading in usage. MiniMax’s market value has surged, exceeding Baidu’s, and its revenue is now over 70% from international markets. Similarly, Kimi2.5 has seen a spike in paid users and overseas revenue since being adopted as OpenClaw’s primary free model. The integration of OpenClaw is blurring traditional boundaries between hardware makers, developers, and AI companies, creating a new ecosystem for AI-powered hardware innovation.

比推03/11 06:49

After the Lobster Comes Ashore, the Next Game in AI Hardware Lego

比推03/11 06:49

活动图片