# Сопутствующие статьи по теме Automation

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

OpenClaw vs. Hermes: Which One Is Right for You?

Two leading AI agent projects, OpenClaw and Hermes, represent a fundamental divergence in design philosophy rather than just a feature competition. OpenClaw, a GitHub phenomenon, prioritizes user control and customization, offering a powerful, flexible platform for building and orchestrating agents. It boasts a massive ecosystem with over 44,000 skills, extensive model flexibility (supporting Anthropic, OpenAI, and others), and deep integrations across multiple messaging platforms. In contrast, Hermes Agent, developed by Nous Research, champions automation and efficiency. It is designed for lower cost and a lower barrier to entry, learning and improving automatically from user workflows. It runs tasks in isolated environments for security and offers significantly lower token costs out-of-the-box. The choice between them mirrors historical tech divides like Windows vs. Mac. OpenClaw is for users who want maximum control, customization, and don't mind a complex setup. Hermes is the smarter default for those seeking an affordable, easy-to-use agent that learns autonomously. The real competition is not about which is better, but which philosophy—a programmable personal OS or a self-evolving work proxy—better suits the user's needs for control, cost, and ease of use.

marsbit04/26 06:42

OpenClaw vs. Hermes: Which One Is Right for You?

marsbit04/26 06:42

Ozak AI’s Forecast Range Expands to $8–$11 as AI Adoption Accelerates Across DeFi, Data, and Automation Markets

Ozak AI ($OZ) is emerging as a leading AI-backed crypto investment, positioned at the intersection of AI, DePIN (Decentralized Physical Infrastructure Network), and tokenized economic growth. With AI adoption accelerating in DeFi, data analytics, and automation, the project's forecasted value has expanded to a range of $8–$11. Currently in advanced presale stages, Ozak AI has raised over $6 million, with tokens priced at $0.014, indicating strong pre-listing commitment. Its DePIN architecture supports scalable, decentralized AI processing, distinguishing it from other AI tokens. The $OZ token offers utility through staking, voting, and network expansion, driving demand. The $8–$11 valuation is based on successful presale activity, exchange listings, and growing adoption in decentralized markets, positioning Ozak AI for significant potential growth.

TheNewsCrypto04/24 12:19

Ozak AI’s Forecast Range Expands to $8–$11 as AI Adoption Accelerates Across DeFi, Data, and Automation Markets

TheNewsCrypto04/24 12:19

OpenAI Launches Workflow Agent, GPTs Begin Countdown

OpenAI has launched Workspace Agents, an evolution of GPTs designed for teams. This new feature allows users to create reusable, shareable agents that automate repetitive workflows. Driven by Codex, these agents operate within their own workspace, can access files, call tools, and run continuously in the background. Users describe a workflow—such as collecting information, making judgments, generating results, and sending outputs—to ChatGPT, which then builds the agent. The entire team can use and refine the agent via ChatGPT or Slack. Once set up, the agent runs autonomously. Workspace Agents are team-shared, code-free, and manageable with predefined permissions and controls. They are suitable for structured, repeatable tasks involving multiple tools and continuous operation, such as software review, feedback整理, report generation, sales follow-up, and risk assessment. The system operates within clear rules, with sensitive actions requiring human confirmation. It aims to transform workflows from being person-dependent to being documented, executable, and reusable—akin to scientific management principles. Competing solutions from Microsoft and Google are also emerging in this space.

marsbit04/24 00:50

OpenAI Launches Workflow Agent, GPTs Begin Countdown

marsbit04/24 00:50

This Time, OpenAI Eliminated 90% of Human Designers

OpenAI's latest release, GPT-Image 2, marks a paradigm shift in AI-generated imagery, moving beyond aesthetic quality to logical reasoning and contextual understanding. The model introduces a "thinking mode," where it performs background reasoning—such as mathematical calculations and geographic knowledge—before generating images. This enables highly accurate and context-aware outputs, like a livestream overlay showing precise distance metrics or a brand-aligned poster design. The model excels in rendering Chinese text with remarkable accuracy and aesthetic quality, a significant improvement over previous versions. It supports multi-turn conversational editing via the new Responses API, allowing iterative refinements similar to chatting with a large language model. While GPT-Image 2 demonstrates unprecedented capabilities in commercial applications like marketing material and illustration—potentially displacing many human designers due to its cost efficiency—it still has limitations. Minor artifacts in fine text details persist, and complex prompts can cause extended processing times. Additionally, the technology raises ethical concerns around deepfakes and digital trust. Overall, GPT-Image 2 transitions AI image generation from a novelty to a powerful production-ready tool, redefining industry standards and pushing the boundary of what’s possible in visual AI.

marsbit04/23 10:03

This Time, OpenAI Eliminated 90% of Human Designers

marsbit04/23 10:03

Anthropic Survey of 80,000 Claude Users: Those Who Use AI to Improve Efficiency the Fastest Feel the Least Secure About the Future

Anthropic surveyed 81,000 Claude users and found a paradox: those who benefit most from AI efficiency gains—like programmers and designers—are also the most anxious about being replaced by AI. Early-career workers expressed greater job insecurity than senior professionals. High-wage and low-wage occupations reported the largest productivity improvements, often through task scope expansion. Nearly half of users cited expanded capabilities as the key benefit, while 40% highlighted increased speed. However, those experiencing the greatest speed boosts reported higher levels of anxiety about job displacement. The findings suggest that AI’s economic impact is already affecting the labor market psychologically, even as many individuals report personal gains from AI use.

marsbit04/23 04:51

Anthropic Survey of 80,000 Claude Users: Those Who Use AI to Improve Efficiency the Fastest Feel the Least Secure About the Future

marsbit04/23 04:51

Three Frameworks for Ordinary People to Achieve AI Capability Leap: Say Goodbye to the Dilemma of 'Repeating Inputs Every Day'

Summary: This article outlines three frameworks for maximizing AI efficiency, moving beyond basic prompt usage. 1. **Three-Layer Evolution**: Users progress from (1) **Prompt** (one-off instructions, reset each session), to (2) **Project** (context-aware within a specific project), to (3) **Skill** (permanent, auto-applied knowledge). Most users stagnate at the first layer, repeating the same instructions daily with no cumulative improvement. Skills transform the AI from a chat tool into a personalized work system. 2. **Transaction vs. Compound Interest Mindset**: Using prompts is a linear transaction—effort and output are 1:1, and stopping resets progress. Investing time in building Skills is compound interest; a small initial time investment pays continuous dividends, as each Skill permanently elevates the AI's baseline performance. 3. **Thin Harness, Fat Skills**: The system architecture should prioritize thick, well-defined Skills (90% of the value—containing processes, standards, and domain knowledge) and a thin "harness" (the minimal technical environment). Avoid over-engineering the toolchain while neglecting the AI's actual knowledge. Skills are permanent assets that automatically improve with model updates. The key takeaway: Identify tasks you repeat, encode them into Skills (using tools like Claude's Skill Creator), and shift focus from daily prompting to building a compounding, self-improving AI system.

marsbit04/22 06:43

Three Frameworks for Ordinary People to Achieve AI Capability Leap: Say Goodbye to the Dilemma of 'Repeating Inputs Every Day'

marsbit04/22 06:43

6,000 CEOs Admit AI 'Did Nothing', Yet It Was Used to Lay Off 40,000 People in Q1 This Year

A study by the National Bureau of Economic Research (NBER) surveying 6000 executives across four countries reveals that nearly 90% of businesses report AI has had "no measurable impact" on employment or productivity over the past three years. Despite global AI investments exceeding $250 billion in 2024, only 12% of CEOs reported both cost reductions and revenue growth from AI. Contrastingly, in Q1 2026, the industry saw 78,557 tech job cuts, with 47.9% attributed to AI and automation. Critics label this contradiction an "AI version of the Solow Paradox," referencing the visible lack of AI's effect in productivity data amid widespread adoption. While some leaders, like Anthropic’s CEO, predict AI will eliminate half of entry-level white-collar jobs, others accuse firms of "AI washing"—using AI as a pretext for layoffs originally planned due to over-hiring or weak demand. However, companies like IBM and Cognizant are bucking the trend by increasing entry-level hiring and retraining staff to work alongside AI. Economists suggest a "J-curve" effect may be underway, where initial productivity stagnation is followed by significant gains, as was seen with IT in the 1990s. The transition remains challenging, with true productivity improvements expected within 6–12 months.

marsbit04/20 11:05

6,000 CEOs Admit AI 'Did Nothing', Yet It Was Used to Lay Off 40,000 People in Q1 This Year

marsbit04/20 11:05

The Only True AI Token Is USDC

The article argues that the only true "AI token" is the stablecoin USDC (and others like USDT, USDS), not the various AI-themed altcoins promoted in crypto circles. It uses the example of "Felix," an AI agent that autonomously runs a company, generating revenue, paying expenses, and hiring other AI agents, all funded and transacted with stablecoins. The core thesis is that AI agents, which are software-based companies, cannot hold traditional bank accounts due to legal and regulatory barriers. Stablecoins in crypto wallets provide the essential financial infrastructure for these agents to operate independently—receiving payments, paying costs, and transacting without human intervention. The author dismisses the narrative that a specific "AI blockchain" will dominate, comparing public blockchains to utility providers (like UPS or FedEx) that AI agents will indifferently use based on cost and efficiency for each transaction. The real value capture is in the stablecoin layer and critical infrastructure like reputation and orchestration systems, not in speculative AI agent tokens, which have collectively lost significant market value. The article concludes that crypto was built for autonomous software, not humans, and that the massive, overlooked transaction volume of stablecoins is the true indicator of the AI agent economy's growth.

marsbit04/20 06:54

The Only True AI Token Is USDC

marsbit04/20 06:54

Back at the AI Table, Zuckerberg's First Move Is Layoffs?

After a period of lagging behind in the AI race, Meta is reportedly planning significant layoffs, with the first round targeting around 8,000 employees (10% of its global workforce) starting May 20, followed by additional cuts later this year. This move comes just 10 days after Meta’s AI team, Meta Superintelligence Labs (MSL), launched its first in-house AI model, Muse Spark—a multimodal reasoning model with advanced capabilities like tool use and multi-agent orchestration. While Muse Spark is seen as a key step for Meta to re-enter competition with leaders like OpenAI and Google, the company is now focusing on an “AI-driven efficiency” strategy. Internal goals aim for 65% of engineers to have AI assist in writing over 75% of their code by mid-2026, and AI usage is reportedly tied to employee performance reviews and promotions. This trend of AI-driven layoffs isn’t isolated; companies like Amazon, Block, and Snap have also cut jobs citing AI’s role in boosting productivity. However, some firms, like Block, later rehired staff after overestimating AI’s immediate impact, highlighting the challenges in balancing AI integration with workforce stability.

marsbit04/18 03:38

Back at the AI Table, Zuckerberg's First Move Is Layoffs?

marsbit04/18 03:38

Back at the AI Table, Zuckerberg's First Move Is Layoffs?

Meta is reportedly planning significant layoffs, with the first round set for May 20, potentially cutting around 8,000 jobs (10% of its workforce), according to sources. Further layoffs may follow later in the year, with adjustments based on AI developments. This comes just 10 days after Meta’s AI team, led by Alexandr Wang, launched its most powerful AI model yet, Muse Spark—a multimodal reasoning tool seen as key to Meta’s re-entry into the AI race. Despite strong financials, Meta is pushing for a leaner, AI-driven structure, aiming for 65% of engineers to have AI generate over 75% of their code by mid-2026. The company has also tied AI usage to performance reviews and promotions. This trend isn’t isolated: Amazon, Block, and Snap have also cited AI efficiency gains to justify layoffs, though Block later rehired some employees, highlighting potential implementation risks.

Odaily星球日报04/18 03:32

Back at the AI Table, Zuckerberg's First Move Is Layoffs?

Odaily星球日报04/18 03:32

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