# Сопутствующие статьи по теме Cost

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

The Last Time I'll Talk About Backpack, and Also Discussing My Airdrop Farming Principles

The author outlines two primary approaches to airdrop farming (referred to as "撸毛"): a labor-intensive" method of mass participation in many projects, and their own "sniper" method. The sniper approach relies on a rigorous four-point checklist to filter projects and avoid "industrial garbage." The checklist evaluates: 1. **Team (People):** Founders must be intelligent, have strong execution skills, and be genuinely well-intentioned. This is assessed through their social media content and, if possible, personal interactions. 2. **Product (Product-Market Fit):** The product must have a clear market fit, be delivered competently, and the team must show a responsible attitude towards its quality, avoiding releases full of basic errors. 3. **Narrative (Story):** The project should operate in a promising, unproven narrative within Web3 that also aligns with major investment trends in Web2 (e.g., AI). 4. **Timing & Cost (Market Conditions):** Avoid participating when market sentiment is overly FOMO-driven and participation costs are high. If an opportunity causes hesitation, it's best to skip it, as overcrowded airdrops yield minimal or negative returns. Applying this framework, the author explains why they avoided heavily farming the Backpack exchange airdrop: * **Narrative:** They are skeptical of the "compliant CEX" narrative, questioning its unique selling point against giants like Binance and OKX. * **Product:** They criticize Backpack's frequent technical failures, rollbacks, and what they perceive as a lack of product development rigor, comparing it unfavorably to competitors like Hyperliquid. * **Timing & Cost:** The participation cost was high compared to zero-fee alternatives available at the time. The author concludes that Backpack lacks the technical and operational prowess of a serious exchange and views its token more as a "VC-backed meme coin" for secondary market speculation rather than a worthwhile airdrop target.

比推03/23 20:38

The Last Time I'll Talk About Backpack, and Also Discussing My Airdrop Farming Principles

比推03/23 20:38

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

Lobster Key 11 Questions: The Most Easy-to-Understand Breakdown of OpenClaw Principles

"OpenClaw Demystified: A Beginner's Guide to AI Agent Principles" explains the popular OpenClaw AI assistant by breaking down its core functions into 11 key questions. The article first clarifies that the underlying large language model is merely a "text prediction engine" with no real understanding, memory, or senses. OpenClaw acts as a "shell" around this model, creating the illusion of memory by appending massive prompts containing its personality files (AGENTS.md, SOUL.md, USER.md) and the entire conversation history before each interaction. This mechanism is why it's "expensive"—each query processes thousands of tokens of context, not just the latest message. A core differentiator is tool use. The model itself only outputs text; OpenClaw parses this output for specific structured commands (e.g., `[Tool Call] Read("file.txt")`) and executes the corresponding action (reading the file) locally on the user's machine. This allows it to act, not just advise. For complex tasks, it can even write and run its own Python scripts, a powerful but dangerous capability. To manage limited context windows and complex tasks, OpenClaw uses sub-agents. A main agent can spawn sub-agent to handle a sub-task and return a summarized result, preventing the main context from being overloaded. Crucially, sub-agents cannot spawn their own to avoid infinite loops. Unlike standard chatbots, OpenClaw is proactive due to its heartbeat mechanism, which periodically prompts the model to check for tasks. It can also "sleep" via cron jobs to wait for long-running tasks, saving resources. The guide ends with critical security warnings. OpenClaw has extensive local access, making it a significant risk. It can malfunction (e.g., deleting emails uncontrollably) or fall victim to prompt injection attacks, where malicious input from the web is mistaken for a user's command. The strong recommendation is to run it on a dedicated, isolated "sacrificial" computer with minimal permissions and mandatory human confirmations for destructive actions.

Odaily星球日报03/11 09:53

Lobster Key 11 Questions: The Most Easy-to-Understand Breakdown of OpenClaw Principles

Odaily星球日报03/11 09:53

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