# Сопутствующие статьи по теме AI

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

Hong Kong Web3 Carnival: The Watershed Moment for Web3 Entering the Execution Phase

The 2026 Hong Kong Web3 Carnival marked a significant shift from previous industry discussions, signaling that Web3 has moved beyond theoretical validation into a phase of institutional and structural implementation. Hong Kong is not merely building a "Web3 industry cluster" but developing an operating system for the next-generation financial infrastructure. Key developments include the expansion of asset tokenization beyond cryptocurrencies to encompass bonds, real estate, and future income rights. This transition represents a fundamental restructuring of financial logic—shifting from institution-dominated asset control to rule-driven, programmable asset流动性 and distribution. Tokenization enables lower-friction participation and broader access to financial resources. Concurrently, AI is evolving from a tool into an autonomous economic agent. The proposed Decentralized Agentic Economy (DAE) framework suggests AI agents, empowered by blockchain-based identity and programmable money, will independently execute transactions and strategies—redefining market dynamics and reducing intermediation. Regulatory progress has been systematic: Hong Kong has expanded oversight to include exchanges, custody, staking, and derivatives, while gradually approving products like tokenized funds and stablecoins. The "same risk, same regulation" principle, combined with sandbox mechanisms, provides stability and transparency—key advantages in a globally fragmented regulatory landscape. Hong Kong’s approach integrates three core elements: real-world asset (RWA) tokenization, stablecoin settlement networks, and AI-driven economic agents. This systemic build-up positions Hong Kong not just as a participant but as a potential rule-maker in the next-era financial system, where asset flow, rules, and participants are simultaneously transformed.

marsbit04/22 10:50

Hong Kong Web3 Carnival: The Watershed Moment for Web3 Entering the Execution Phase

marsbit04/22 10:50

A 120,000 Yuan Tombstone or 399 Yuan AI Immortality: Which Would You Choose?

"The 'Deathcare Moutai' Fushouyuan, once a highly profitable cemetery operator, has halted trading amid a severe crisis, with its net profit plummeting by 52.8% in 2024. This reflects a broader trend of people rejecting expensive traditional burials, as average grave prices in China have soared to over ¥120,000. In response, the industry is pivoting to digital alternatives, with companies like Fushouyuan offering AI-powered memorial services, such as virtual farewell halls and AI-generated recreations of the deceased. Simultaneously, a low-cost, unregulated AI 'resurrection' industry has emerged online, with services priced as low as ¥399. These often use open-source tools to create crude digital avatars from photos and voice clips, exploiting vulnerable individuals, particularly bereaved parents who have lost their only child. However, these services raise significant ethical and legal concerns, including data privacy risks and potential use in scams. Academic studies warn that such AI companions may exacerbate grief, leading to prolonged mourning disorders and emotional dependency, rather than providing genuine comfort. While regulations are being drafted to manage digital human services, the deep emotional drive to 'reconnect' with loved ones often overshadows rational concerns. Ultimately, the article questions whether digital immortality truly preserves memory or merely offers a commercialized illusion, emphasizing that no technology can replace the real, irreplaceable loss of a human life."

marsbit04/22 08:34

A 120,000 Yuan Tombstone or 399 Yuan AI Immortality: Which Would You Choose?

marsbit04/22 08:34

Anthropic Starts Poaching Scientists? $27K Weekly Onsite Stipend to Fix Claude's Expert-Level Errors

Anthropic has launched a new STEM Fellow program, offering $3,800 per week for a three-month, in-person residency in San Francisco. The role targets experts from science, technology, engineering, and mathematics (STEM) fields—machine learning experience is helpful but not required. Instead, Anthropic values scientific judgment and a willingness to learn quickly. Fellows will work with Claude models and internal tools under the guidance of an Anthropic researcher. Example projects include a materials scientist identifying errors in Claude’s reasoning or a climate scientist integrating atmospheric modeling software with Claude. The goal is to have experts "tell Claude where it's wrong" and improve its scientific capabilities. This initiative is part of Anthropic’s broader strategy to strengthen its scientific ecosystem, following earlier programs like the AI Safety Fellows and AI for Science programs. The company acknowledges that current AI models, while powerful, still produce high-confidence errors and lack end-to-end research autonomy. The program aims to embed domain expertise directly into model development, turning scientists into "high-level reviewers" for AI. Anthropic CEO Dario Amodei has previously emphasized AI’s potential to accelerate scientific breakthroughs, particularly in biology and healthcare. The company believes that the next phase of AI competition will depend not on scaling parameters, but on integrating human expertise to refine model accuracy and reliability.

marsbit04/22 07:44

Anthropic Starts Poaching Scientists? $27K Weekly Onsite Stipend to Fix Claude's Expert-Level Errors

marsbit04/22 07:44

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

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