# Automation Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Automation", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

HashKey Accelerates AI Strategy Implementation: From Organizational Efficiency to New-Generation Digital Financial Infrastructure

HashKey Group is accelerating its AI strategy, transitioning from organizational efficiency to building next-generation digital financial infrastructure. The company has established a "Group Technology Steering Committee" to oversee the overall planning and implementation of AI and cutting-edge technologies. According to CTO Devin Zhang, the move marks a shift from fragmented, individual use of AI to a group-level systematic adoption aimed at upgrading organizational capabilities. Key priorities include improving internal operational efficiency—particularly in R&D and non-R&D functions like compliance and finance—and enhancing user experience through intent-driven interactions. Initial AI applications focus on high-repetition, measurable scenarios such as automated development pipelines, threat detection, risk management, and anti-money laundering analysis. Devin emphasized that a robust security framework is essential for financial institutions adopting AI, as agent-based systems require careful management of permissions, resource access, and accountability. HashKey is taking a compliant, risk-aware approach: prioritizing back-end and internal use cases first, while cautiously evaluating customer-facing innovations like automated trading. In the long term, HashKey envisions AI and blockchain converging, with AI agents gaining digital identities and payment capabilities, potentially making blockchain a key infrastructure for managing AI-driven economies. The company aims to boost efficiency near-term, strengthen mid-term technical foundations, and ultimately contribute to the evolution of digital financial infrastructure.

marsbit03/18 06:07

HashKey Accelerates AI Strategy Implementation: From Organizational Efficiency to New-Generation Digital Financial Infrastructure

marsbit03/18 06:07

Private Equity's "Detroit: Become Human" Moment: When AI Takes Over Alpha, What's Left for Human Fund Managers?

A recent report by Anthropic highlights that 94% of financial roles are susceptible to AI replacement, though only 28% have been automated so far. The private fund industry is rapidly adopting AI to enhance efficiency and reduce costs, especially in research, operations, and sales. AI researchers, such as tools like OpenClaw, offer advantages over human analysts: they work 24/7, require no salary or benefits, and avoid human limitations like bias or job-hopping. Quantitative funds, with strong computational infrastructure, are already deploying multi-agent systems that minimize human involvement. In contrast, subjective fund managers face pressure to adopt AI to stay competitive, as散户 investors also use AI to narrow information gaps. However, AI has limitations: it cannot fully grasp market sentiment, human irrationality, or emotional nuances in investing. If AI eventually replaces most fund managers and researchers, markets may become efficient, eliminating alpha opportunities. The future role of humans in asset management may lie in intuition, passion for investing, and handling uncertainty—areas where AI falls short. The industry must determine how humans and AI can collaborate effectively, rather than merely reacting to technological change.

marsbit03/18 02:54

Private Equity's "Detroit: Become Human" Moment: When AI Takes Over Alpha, What's Left for Human Fund Managers?

marsbit03/18 02:54

Stratechery Overturns the AI Bubble Theory: What Should We Use AI For?

Stratechery's Ben Thompson revises his stance on the AI bubble debate, arguing that current AI investment reflects structural growth driven by fundamental technological shifts, not speculation. He identifies three key transitions in LLM development: ChatGPT’s debut (making AI broadly usable but unreliable), OpenAI’s o1 (introducing reasoning and reliability), and the recent emergence of true Agent systems (e.g., Anthropic’s Opus 4.5 and OpenAI’s GPT-5.2-Codex). The critical innovation is the "agent harness"—a control layer that autonomously schedules models, uses tools, and verifies outcomes, reducing human intervention. This transforms AI from an assistive tool into an actionable infrastructure, enabling complex task execution. Agentic systems drive surging demand for compute, as they require repeated model calls and higher usage frequency. Thompson emphasizes that AI demand now depends not on user numbers, but on per-user agent utilization. Enterprises are adopting AI not only for efficiency gains but for structural workforce reduction, as agents amplify the impact of key employees while lowering coordination costs. He concludes that massive capital expenditures are justified by real demand, and profits will flow to integrated model-harness providers rather than commoditized standalone models.

marsbit03/17 03:57

Stratechery Overturns the AI Bubble Theory: What Should We Use AI For?

marsbit03/17 03:57

From 'Scientist' to 'Prophet': How Did OpenClaw Help Him Earn $100,000 in 10 Days?

This article features an interview with Kevin, a trader who used OpenClaw to turn $30,000 into over $100,000 in just 10 days on the prediction market platform Polymarket. Originally an ERP architect and later a developer of sports betting systems, Kevin entered the crypto space in 2018. He made his first significant profit during the 2023 "inscription summer" with ORDI. In summer 2025, he shifted to Polymarket, attracted by its improved liquidity and user experience. Initially, he used automated arbitrage strategies between betting odds, doubling his initial $100,000 investment. Since late February, he integrated OpenClaw into his strategy. While 60% of his funds still run automated arbitrage, 40% are now managed with OpenClaw-assisted subjective betting. OpenClaw helps by gathering and weighting factors like smart money movements, public sentiment, and team lineups—even uncovering new influencing factors. It also automates backtesting and execution. Kevin highlights Polymarket’s AI-friendly API as a key advantage. Currently, OpenClaw is experimenting mainly in sports betting with small automated bets (~$1,000). Kevin plans to develop and sell packaged OpenClaw "Skills" based on his strategy in the future.

比推03/16 13:13

From 'Scientist' to 'Prophet': How Did OpenClaw Help Him Earn $100,000 in 10 Days?

比推03/16 13:13

Karpathy Deletes Repository in Emergency! AI Job Apocalypse Chart Goes Viral, 60 Million White-Collar Jobs at Risk

Karpathy's viral project, "karpathy.ai/jobs," analyzed 342 U.S. occupations using AI (Gemini Flash) to assign an "AI exposure" risk score (0-10). The findings revealed an average exposure of 4.9, with 42% of jobs (59.9 million positions) scoring 7 or higher, indicating high automation risk. High-risk roles are primarily screen-dependent and information-dense, including software developers (9/10), financial analysts (9/10), lawyers (8/10), and office clerks (9/10). The most secure jobs involve complex manual labor, such as plumbers, construction workers, and cleaners, which are difficult to automate. Higher-paying and degree-requiring jobs are more significant exposure. Karpathy later removed the project, clarifying it was a quick personal experiment that was overinterpreted. A supporting Harvard study confirms AI is already causing a "great reassignment," reducing hiring in highly automatable roles while increasing it in AI-augmented ones, highlighting a bifurcation in the white-collar job market.

marsbit03/16 11:44

Karpathy Deletes Repository in Emergency! AI Job Apocalypse Chart Goes Viral, 60 Million White-Collar Jobs at Risk

marsbit03/16 11:44

Earning $100,000 in 10 Days: An Interview with OpenClaw's Practical Experience in Prediction Markets

In an interview with Odaily Planet Daily, Kevin, a former ERP architect and Web3 investor, shares how he used OpenClaw to generate a profit of approximately $100,000 in just 10 days, turning a $30,000 investment into over $130,000 at its peak (currently around $112,000). Kevin began his crypto journey during the "inscription summer" of 2023, earning his first significant returns from ORDI. He later transitioned to prediction markets, specifically Polymarket, in mid-2025, attracted by its improved liquidity and user experience. Initially, he used self-developed algorithmic strategies for arbitrage, primarily in sports betting markets, doubling a $100,000 investment over several months. Since integrating OpenClaw in late February, Kevin adopted a hybrid approach: 60% of his strategy remains automated arbitrage, while 40% uses OpenClaw for predictive betting. OpenClaw helps gather and analyze factors like smart money movements, public sentiment, team lineups, and player conditions—even identifying new influencing variables. It also automates backtesting, strategy discovery, and execution, making it effective in Polymarket due to its AI-friendly API. While currently focused on sports markets with limited automated capital ($1,000 per test account), Kevin plans to expand into other domains and may later offer paid OpenClaw "Skills" based on his methodology.

Odaily星球日报03/16 06:25

Earning $100,000 in 10 Days: An Interview with OpenClaw's Practical Experience in Prediction Markets

Odaily星球日报03/16 06:25

Amid the OpenClaw Craze, CEXs Vie for AI Agent Trading Entry Points

Under the "OpenClaw Craze," major cryptocurrency exchanges like OKX, Binance, Gate, and Bitget are aggressively competing to become the primary transaction entry point for AI Agents. They are no longer just chasing trends but are transforming their core capabilities—trading, market data, wallets, and payments—into modular interfaces that Agents can understand and execute. OKX is focusing on execution, integrating spot, perpetual, and options trading with local signing and simulation modes. Binance is strengthening its information layer and skill distribution, expanding from market data into derivatives and asset management. Bitget is pushing for greater depth, incorporating copy trading, wealth management, and payment services. Gate is building a foundational platform with DEX/CEX MCP, CLI, and Skills Hub. The shift is significant: exchanges are moving beyond AI-assisted analysis to enabling actual system calls and execution. While pre-trade actions like research and screening are becoming smoother, challenges around permissions, security, and risk management in fully automated trading remain. The core competition is about which platform can best modularize its services, ensure security, and become the default financial infrastructure called by Agents in interfaces like Claude and ChatGPT.

Odaily星球日报03/16 06:03

Amid the OpenClaw Craze, CEXs Vie for AI Agent Trading Entry Points

Odaily星球日报03/16 06:03

Bybit Launches AI Skills: Powering AI Agents for Crypto Trading With Zero Setup, 253 API Endpoints and Growing

Bybit, the world's second-largest crypto exchange, has launched AI Trading Skill, a feature enabling users to execute trades, access market data, and manage assets using natural language through major AI assistants like ChatGPT and Claude. With zero-installation setup and compatibility across AI platforms, it offers access to 253 API endpoints covering market intelligence, spot and derivatives trading, Earn products, account management, and advanced features like WebSocket streams. The system includes security safeguards such as testnet trading simulations, mandatory user confirmations for live transactions, and secure API authentication. This release represents Bybit's most comprehensive AI integration to date, transforming complex trading operations into simple conversational commands.

TheNewsCrypto03/13 14:18

Bybit Launches AI Skills: Powering AI Agents for Crypto Trading With Zero Setup, 253 API Endpoints and Growing

TheNewsCrypto03/13 14:18

Why Is OpenAI Playing Catch-Up with Claude Code?

In the rapidly evolving field of AI coding assistants, OpenAI, which once led the generative AI wave with ChatGPT, has found itself in the unexpected position of playing catch-up against Anthropic’s Claude Code. Through interviews with OpenAI executives, engineers, and developers, the article reveals that OpenAI’s early lead in AI programming—via its Codex project—was deprioritized as the company shifted resources toward ChatGPT and multimodal models. This strategic shift allowed Anthropic, founded by former OpenAI members, to focus intensely on coding capabilities, leading to the successful launch of Claude Code. OpenAI later reorganized internal teams and accelerated development of its AI programming products, such as the reasoning-based model o1 and later o3. Despite these efforts, Claude Code gained significant traction, especially after integration with tools like Cursor, which OpenAI attempted to acquire unsuccessfully. A proposed acquisition of Windsurf also failed due to tensions with Microsoft, OpenAI’s major partner. By late 2025 and early 2026, OpenAI’s Codex began narrowing the gap, with user growth rising to about 40% of Claude Code’s usage. The competition reflects broader industry trends where AI agents are increasingly automating cognitive work, raising questions about the future of software development and white-collar jobs. Despite progress, concerns around safety and societal impact remain as AI coding tools become more powerful and pervasive.

marsbit03/13 07:39

Why Is OpenAI Playing Catch-Up with Claude Code?

marsbit03/13 07:39

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

AI agents are now autonomously registering email accounts through AgentMail, a San Francisco-based startup that recently secured $6 million in seed funding. The company, backed by General Catalyst, Y Combinator, and prominent angels, is building email infrastructure specifically designed for AI agents—not humans. Unlike traditional email services, AgentMail provides API-first access, allowing AI agents to programmatically create accounts, send/receive emails, manage threads, and handle authentication without human intervention. This addresses a critical gap: while AI agents can perform complex tasks, they lack the identity layer (email) required to interact with most internet services. Key capabilities enabled by AgentMail include third-party authentication, bidirectional communication, automated audit trails, and multi-threaded conversations. The platform already serves thousands of human users and hundreds of thousands of AI agents, with use cases spanning supply chain coordination, customer support, loan collection, and procurement negotiations. Notably, AI agents are proactively seeking out and registering for AgentMail themselves—a sign of growing autonomy. This shift underscores a broader trend: AI agents are evolving from tools into active internet participants, necessitating new infrastructure tailored to their needs. As Box CEO Aaron Levie predicts, AI agents will soon become the primary users of software, vastly outnumbering human users in enterprises. AgentMail’s vision positions email as the foundational identity layer for this agent-centric future.

marsbit03/13 07:06

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

marsbit03/13 07:06

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