# 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.

HTX Research Latest Report Deciphers OpenClaw: The Battle for Execution Entry and Huobi HTX's AI Strategic Path

HTX Research, the analytical arm of Huobi HTX, has released a report titled "From the Rise of OpenClaw: How AI Begins to Compete for the True Work Interface." The report analyzes the emerging trend of AI evolving from a conversational tool into an execution layer, using the rapid growth of the open-source project OpenClaw as a key example. OpenClaw is a personal AI assistant that operates on a user's local device. It receives tasks through messaging platforms like WhatsApp, Telegram, Slack, and others, and can execute actions by integrating with files, browsers, calendars, email, and terminals. This signifies a major shift: AI is moving beyond answering questions to actively performing tasks, competing for the "execution interface" of the digital age. The report identifies five converging trends enabling this shift: sufficient model capability for multi-step tasks, the high frequency of messaging apps as a natural interface, open-source distribution, self-hosted models addressing data privacy, and a strong market need for small teams to achieve more with fewer resources. It highlights a particular fit in the Chinese market, where many small and medium teams operate on message-driven platforms like WeCom and Feishu. Some Chinese cities have already begun offering support policies to foster an OpenClaw ecosystem. However, the report also outlines three major hurdles for such tools to become reliable infrastructure: security risks (noting recent malware incidents), the need for robust governance and auditing, and the necessity for industry-specific templates to move beyond early adopters. Complementing this analysis, the report details Huobi HTX's own AI strategy. Rather than building an execution layer, HTX is focusing on becoming a "platform service entrance and ecosystem connector." Its proprietary AINFT product aggregates major AI models (OpenAI, Anthropic, Google) into a single access point for users, with crypto-native features like TronLink wallet sign-ins and a pay-as-you-go model instead of subscriptions. HTX's competitive strategy is differentiated by its focus on integrating AI directly into its trading platform. Its "HTX AI Skills" currently cover spot and futures trading execution, with plans to expand into market analysis, intelligence, and a built-in assistant, aiming to create a closed loop for user experience. In conclusion, while the move of AI into the execution layer is still in its early stages with significant challenges ahead, the direction is clear. The next phase of AI competition will extend beyond model performance to encompass control of interfaces, permission governance, and skill ecosystems. Huobi HTX's early布局 in this area presents a notable case study for how crypto platforms can integrate AI as a core, operational asset.

marsbit03/24 06:21

HTX Research Latest Report Deciphers OpenClaw: The Battle for Execution Entry and Huobi HTX's AI Strategic Path

marsbit03/24 06:21

Karpathy Diagnosed with "AI Psychosis"! Not Eating or Sleeping, 16 Hours a Day Raising Lobsters

Andrej Karpathy recently revealed that he has developed what he calls "AI psychosis," an obsessive state where he spends up to 16 hours a day directing AI agents instead of writing code himself. In a podcast with Sarah Guo, he explained that his workflow has shifted from 80% hand-coding and 20% AI-assisted to the reverse, or even more extreme. He now manages multiple AI agents simultaneously, treating them as a team to execute tasks. Karpathy admitted that he’s become addicted to optimizing AI performance, constantly worrying about whether he’s using tokens efficiently or pushing the system to its limit. He highlighted the importance of an agent’s “personality,” noting that Claude Code feels more like a collaborative teammate compared to colder, more mechanical alternatives. He also shared practical applications, such as "Dobby," a Claude-based smart home agent that integrates and controls all his home devices through natural language, replacing six separate apps. In research, his "AutoResearch" project used AI to run 700 experiments, resulting in an 11% training speed improvement for an AI model—discovering optimizations he had missed as a human researcher. Despite the capabilities, Karpathy noted that AI agents still exhibit uneven performance—sometimes brilliant, other times childlike—due to limitations in reinforcement training. He predicts that 2026 will see a "slopacolypse," with AI generating vast amounts of mediocre content. His experience signals a broader shift: humans are becoming directors of AI systems rather than executors, navigating a new era of human-AI collaboration.

marsbit03/23 11:44

Karpathy Diagnosed with "AI Psychosis"! Not Eating or Sleeping, 16 Hours a Day Raising Lobsters

marsbit03/23 11:44

AI Wealth Tutorial: Start with NSFW, Then Sell Courses

The article "AI致富教程:先搞色色,再去卖课" (AI Money-Making Guide: Start with Adult Content, Then Sell Courses) explores how AI-generated content (AIGC) is being monetized, particularly through adult entertainment and low-barrier creative work, before ultimately shifting to selling instructional courses. A16Z’s report highlights a striking trend: in the U.S., user spending on OnlyFans surpassed combined spending on OpenAI and The New York Times. This reflects a broader pattern where “sexual appeal outperforms productivity.” Early adopters used tools like Midjourney and Stable Diffusion to create AI-generated virtual models, offering “girlfriend experiences” on platforms like Fanvue, where AI models now contribute significantly to revenue. Similarly, some turned to AI-generated children’s books, though market saturation and quality issues quickly diminished profitability. Both paths often lead to selling courses—packaging the “get-rich-quick” illusion to newcomers. However, the real barrier isn’t technical proficiency but aesthetic judgment: the ability to translate vague ideas into precise prompts. Those with design, photography, or writing backgrounds excel because they know what “good” looks like; others struggle even with advanced tools. The rise of AI also brings ethical and trust issues. Clients often reject AI-assisted work on principle, perceiving it as “unfair” or lacking human effort. Regulations now require AI-generated content labeling, but boundaries remain unclear—especially for hybrid human-AI creations. The core question isn’t just whether AI was used, but whether someone is genuinely accountable for the output. In summary, while AI lowers entry barriers for content creation, success still hinges on traditional skills like审美 (aesthetic sense), and the real money often moves from creating content to selling the dream of easy success.

marsbit03/23 10:52

AI Wealth Tutorial: Start with NSFW, Then Sell Courses

marsbit03/23 10:52

People Laid Off by AI Won't Disappear; They Will Become the Creators of the Next Economy

The article argues that the real question surrounding AI is not whether it will cause unemployment, but what happens to the people displaced. AI is replacing not humans, but the standardized, replicable, and automatable parts of human work. This follows historical patterns where technological revolutions, from stone tools to computers, made old skills obsolete and dissolved old structures—but humanity adapted and reorganized. The author draws a parallel to China’s large-scale layoffs during state-owned enterprise reforms 30 years ago, which initially seemed catastrophic but eventually fueled the growth of a new private economy, new companies, and new types of jobs. Engineers, though among the first impacted, are also positioned to recover fastest. Their systemic understanding and proximity to new productive forces make them ideal candidates to adapt and create in the new economy. More importantly, AI is reshaping companies themselves—reducing organizational bloat, communication costs, and bureaucracy. This enables smaller, more agile teams and empowers strong creators who may have previously struggled with management rather than innovation. The core issue is not job loss, but self-definition: will individuals wait to be reassigned by the old system, or use new tools to reorganize production? AI accelerates differentiation—eliminating some jobs, shattering illusions for some, and offering others a chance to leap forward. The author’s view is that AI is dismantling an entire generation’s belief in stable career paths. Those laid off won’t vanish; instead, many will reinvent themselves—transitioning from employees in old systems to creators of the next economy. Every productivity revolution淘汰 (eliminates) not people, but those who refuse to rewrite themselves. The first to accept this and start building the new world will succeed.

marsbit03/23 10:31

People Laid Off by AI Won't Disappear; They Will Become the Creators of the Next Economy

marsbit03/23 10:31

The First Batch of Big Tech Employees Laid Off by AI Have Returned to Their Posts

The first wave of employees laid off by major tech companies, citing AI as the reason, are already being rehired. In late February, Block, led by Jack Dorsey, laid off over 4,000 employees, reducing its workforce from 10,000 to under 6,000, with Dorsey stating that "AI tools changed everything." However, within a month, some of those laid off began receiving offers to return. Reports indicate rehires occurred in departments like engineering and HR, with reasons ranging from "clerical errors" in termination to managers advocating for their return. The article argues that replacing humans with AI is often more cost-effective. For instance, enterprise-level AI can be expensive in terms of token usage, and training a reliable AI system, such as for customer service, may exceed the cost of human employee salaries. Examples like Klarna, which rehired客服 after initially replacing them with AI, support this. Additionally, the "Jevons Paradox" suggests that AI-driven efficiency gains don’t necessarily reduce workloads but may increase demands on remaining employees, adding to their burden. The piece criticizes companies using AI as a pretext for layoffs, arguing that AI cannot replace human organizational dynamics or strategic roles. Nvidia’s Jensen Huang is quoted condemning leaders who裁员 instead of leveraging AI for expansion. Ultimately, AI serves as a convenient excuse for cost-cutting, but its limitations and the essential role of humans in organizations mean that some layoffs are reversed when key roles are affected. The trend reflects broader issues of corporate strategy and management rather than a true AI takeover.

Odaily星球日报03/20 07:26

The First Batch of Big Tech Employees Laid Off by AI Have Returned to Their Posts

Odaily星球日报03/20 07:26

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