# Automation İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Automation" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

Dialogue with MIT Economist: Don't Panic About 'AI Doomsday Theory', Verification Capability is a Scarce Resource

In a discussion with MIT economist Christian Catalini, the core argument is that the true scarcity in the AI economy is not intelligence but verification—the human capacity to check, judge, and confirm the correctness of AI outputs. Catalini explains that while automation costs are falling exponentially, verification remains constrained by human biological limits, at least for now. Entry-level jobs are most vulnerable, as AI can easily replicate tasks that rely on measurable, existing knowledge. However, even top experts are inadvertently training their own replacements by generating data that AI learns from—a phenomenon termed the "coder’s curse." Three roles will remain critical in the AI-driven economy: - **Directors**: Those who set intentions and steer AI agents toward goals, dealing with "unknown unknowns." - **Meaning Makers**: Individuals who create cultural, social, or narrative value based on human consensus and status games. - **Liability Underwriters**: Top-tier experts (e.g., lawyers, doctors) who assume responsibility for edge cases and final validation. Catalini advises against panic and encourages experimentation with AI tools to automate current roles and discover new opportunities. He emphasizes that uniquely human traits—like judgment in unmeasurable contexts—will retain value, and crypto-based verification infrastructure may play a key role in ensuring authenticity. The transition will be disruptive, but leveraging AI can amplify human potential exponentially.

marsbit4 saat önce

Dialogue with MIT Economist: Don't Panic About 'AI Doomsday Theory', Verification Capability is a Scarce Resource

marsbit4 saat önce

Technological Fantasy or "Career Killer"? Deep Reflection Under the Wave of AI Layoffs

Amid the rapid adoption of AI tools like OpenClaw, a wave of layoffs is sweeping across industries from North America to Asia. Major companies, including Meta and Crypto.com, are cutting jobs—up to 20% or more in some cases—not due to economic pressure but as part of a strategic shift toward AI-driven productivity. In Q1 2026 alone, over 20% of tech layoffs were attributed to AI and automation. Roles most affected include programmers, customer service reps, data entry clerks, and marketing specialists—jobs with high language or data-processing components. Even creative and industrial roles are at risk if they involve repetitive, template-based tasks. Industries like finance, media, and logistics are also experiencing disruption as AI automates standardized workflows. The report from Anthropic highlights that positions requiring low emotional intelligence, physical interaction, or complex decision-making remain safer. To stay relevant, workers must focus on skills AI can’t replicate: empathy, creative problem-solving, and strategic judgment. The key is not to resist AI but to adapt, using it as a tool while deepening human-centric capabilities. The era of AI collaboration has begun—those who evolve will thrive; those who don’t may face obsolescence.

marsbit12 saat önce

Technological Fantasy or "Career Killer"? Deep Reflection Under the Wave of AI Layoffs

marsbit12 saat önce

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

OpenAI Exposes 'Polaris' Project, the '2028 Great Unemployment' May Really Be Coming

OpenAI has disclosed its "North Star" project, aiming to build a fully automated multi-agent AI research system by 2028. This goal, announced by Chief Scientist Jakub Pachocki, includes launching an "autonomous AI research intern" capable of handling specific research tasks by September 2024. The project represents a major strategic shift, consolidating resources and products like ChatGPT and Codex into a unified super-app. The initiative reflects a broader industry trend, with competitors like Anthropic also advancing AI agent integration into workflows, such as through Claude Code on platforms like Discord. However, Pachocki acknowledges significant challenges in safety and controllability, noting that full control over LLMs remains unresolved. Economically, the project could be highly lucrative, with projections suggesting AI agents—including a $20,000/month "research agent"—generating $29 billion annually by 2029. The core implication is profound: if AI can autonomously conduct research, the pace of scientific and AI advancement could accelerate beyond human limitations, potentially reshaping labor markets and research paradigms.

marsbit03/24 02:46

OpenAI Exposes 'Polaris' Project, the '2028 Great Unemployment' May Really Be Coming

marsbit03/24 02:46

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

Zuckerberg is Building an AI Agent to Assist Him as CEO

Meta CEO Mark Zuckerberg is developing a personal AI agent to assist him in his executive duties, enabling faster information retrieval and reducing reliance on hierarchical reporting. This initiative is part of Meta’s broader effort to become an "AI-native" company, streamlining operations and increasing efficiency amid growing competition from smaller, agile AI startups. Internally, Meta is encouraging widespread AI adoption, with tools like My Claw and Second Brain—an AI "chief of staff"—gaining traction among employees. The company has also made acquisitions to bolster its AI capabilities. However, this shift has raised concerns about potential layoffs, as Meta reportedly considers significant workforce reductions to align with its new AI-driven structure.

marsbit03/23 09:59

Zuckerberg is Building an AI Agent to Assist Him as CEO

marsbit03/23 09:59

Visa Spent $1.8 Billion Just to Avoid Being Left Behind by AI

Visa's $1.8 billion acquisition of stablecoin infrastructure firm BVNK is a defensive move against the rise of AI agents disrupting its core business model. Visa’s empire is built on interchange fees (2-3% per transaction), which fund rewards, fraud protection, and status-driven perks that appeal to human psychology. However, AI agents are purely rational: they seek the cheapest, fastest payment path, avoid fees, and have no use for rewards or brand loyalty. A recent report warning that AI agents could bypass traditional card networks by 2027 using stablecoins and decentralized payment protocols (like x402 and Tempo) caused significant stock drops for Visa, Mastercard, and Amex. While current transaction volumes on new infrastructures remain small, projects like Visa CLI, Circle’s Nanopayments, and Stripe’s blockchain initiatives are laying the groundwork for machine-to-machine commerce. Visa isn’t idle—it’s participating in new protocols and launching crypto tools—but its historical advantage (consumer trust and merchant acceptance) relies on human behavior. In an AI-driven economy, that advantage vanishes. The disruption begins with micro-payments for API calls and AI services, but may eventually extend to consumer spending. Visa’s massive investment signals it knows the threat is real.

比推03/20 17:55

Visa Spent $1.8 Billion Just to Avoid Being Left Behind by AI

比推03/20 17:55

活动图片

Bitcoin