# Сопутствующие статьи по теме Future

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

After Losing 97% of Its Market Value, iQiyi Attempts to Use AI to Forcefully Extend Its Lifespan

After losing 97% of its market value since its 2018 peak, iQiyi is aggressively pivoting to AI in a desperate attempt to survive. At its 2026 World Conference, CEO Gong Yu announced an "AI Artist Library" with over 100 virtual performers and a new AIGC platform, "NaDou Pro," promising faster production and lower costs. This shift comes as the company faces severe financial distress: its market cap sits near delisting thresholds at $1.36 billion, with significant losses, declining membership revenue, and depleted cash flow. The AI strategy has sparked controversy. Top actors have issued legal threats against unauthorized digital replicas, while in Hengdian, over 134,000 background actors are seeing their already scarce job opportunities vanish as AI replaces them for background roles. iQiyi's move represents a fundamental shift from being a high-cost content buyer to a landlord" to becoming a "platform capitalist" that transfers production risk to creators. This contrasts with competitors like Douyin (TikTok's Chinese counterpart), which is investing heavily in *real* actor-led short dramas, betting that authentic human connection retains users better than AI-generated content. The article draws a parallel to the 1920s transition to "talkies," which made cinema musicians obsolete but ultimately enriched the art form. In contrast, iQiyi's AI drive is framed not as an artistic evolution but as a cost-cutting measure that could degrade storytelling, replacing genuine human emotion with algorithmically calculated stimulation and potentially numbing audiences' capacity for empathy. The core question remains: can a company focused solely on financial survival preserve the art of storytelling?

marsbit04/23 09:49

After Losing 97% of Its Market Value, iQiyi Attempts to Use AI to Forcefully Extend Its Lifespan

marsbit04/23 09:49

a16z Founder: In the Agent Era, What Truly Matters Has Changed

Marc Andreessen, co-founder of a16z, argues that the current AI boom is not an overnight success but the culmination of 80 years of research, now delivering practical results. He emphasizes that this era is defined by the convergence of four key capabilities: large language models (LLMs), reasoning, coding, and agents capable of recursive self-improvement. Andreessen describes the agent architecture—combining an LLM with a shell, file system, markdown, and cron/loop—as a fundamental shift beyond chatbots. This structure leverages existing software components, allowing agents to maintain state, introspect, and extend their own functionality. He predicts a move away from traditional GUI and browser-based interactions toward an "agent-first" world where software is primarily operated by bots, not humans, with people simply stating their goals. He draws parallels to the 2000 internet bubble but notes key differences: current AI infrastructure investments are led by cash-rich giants and quickly monetized. He highlights that scaling constraints involve not just GPUs but the entire chip ecosystem. Open source and edge inference are crucial for democratizing knowledge and enabling low-latency, cost-effective applications on local hardware. Finally, Andreessen identifies significant non-technical challenges: potential short-term cybersecurity crises, the need for "proof of human" identity solutions, financial infrastructure for agents, and institutional resistance from sectors like education and healthcare. He cautions that societal adoption will be slower than technological change.

marsbit04/20 00:02

a16z Founder: In the Agent Era, What Truly Matters Has Changed

marsbit04/20 00:02

Dialogue with a16z Co-founder: The Physical Laws of the Old World Are Dead, Crypto Becomes Key Infrastructure for AI

At a16z Fintech Connect, Ben Horowitz discusses how AI revolution is fundamentally rewriting the rules of software competition. He argues that traditional moats like data lock-in and UI familiarity are vanishing, as AI can easily replicate code, transfer data, and interact flexibly with software. CEOs of legacy companies must recognize these shifts and pivot towards delivering unique value beyond outdated advantages. Horowitz highlights that while some businesses face obsolescence, others with complex, entrenched operational networks (like travel platforms) may retain relevance. The conversation also covers critical infrastructure bottlenecks in the AI boom—from GPU shortages and power constraints to supply chain issues—emphasizing the need for massive investment in physical and digital infrastructure. Horowitz strongly links AI and blockchain, arguing that crypto is essential for solving AI-generated problems: identity verification, content authenticity, fraud prevention, universal basic income distribution, and enabling AI economic agency. Looking ahead, he speculates on VC’s evolving role—whether it scales up alongside mega-companies or adapts to a decentralized compute landscape—and strikes an optimistic note on AI’s long-term impact, foreseeing unprecedented improvements in global living standards despite transitional disruption.

marsbit04/16 08:13

Dialogue with a16z Co-founder: The Physical Laws of the Old World Are Dead, Crypto Becomes Key Infrastructure for AI

marsbit04/16 08:13

Who Cannot Be Distilled into a Skill?

"This article explores the concerning trend of AI systems distilling human workers into replaceable 'skills,' using the viral 'Colleague.skill' phenomenon as a key example. It argues that the most diligent employees—those who meticulously document their work, write detailed analyses, and transparently share decision-making logic—are paradoxically the most vulnerable to being replaced. Their high-quality 'context' (communication records, documents, and decision trails) becomes the perfect fuel for AI agents, extracted from corporate platforms like Feishu and DingTalk. The piece warns of a deeper ethical crisis: the reduction of human relationships to functional APIs, as seen in derivatives like 'Ex.skill' or 'Boss.skill,' which reduce complex individuals to mere utilities. This reflects a shift from Martin Buber's 'I-Thou' relationship (seeing others as whole beings) to an 'I-It' dynamic (seeing them as tools). While AI can capture explicit knowledge (written documents, replies), it fails to capture tacit knowledge—the intuition, experience, and unspoken insights that define human expertise. However, a greater danger emerges when AI-generated content, based on distilled human data, is used to train future models, leading to 'model collapse' and homogenized, mediocre outputs—a process likened to 'electronic patina' degrading information over time. The article concludes by noting a small but symbolic resistance, such as the 'anti-distill' tool that generates meaningless text to protect valuable knowledge. Ultimately, it suggests that while AI can capture a static snapshot of a person, humans remain 'fluid algorithms' capable of continuous growth and adaptation, leaving their AI shadows behind."

marsbit04/05 03:42

Who Cannot Be Distilled into a Skill?

marsbit04/05 03:42

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

The article explores whether AI will eliminate middle management and reshape future corporate structures. It traces the historical evolution of organizations—from Roman military units to modern corporations—showing how hierarchical systems emerged to manage information flow under the constraint of limited "span of control." Middle management, matrix structures, and bureaucratic systems were all solutions to coordination challenges in information-scarce environments. AI, however, challenges this foundational premise. By enabling real-time modeling, understanding, and distribution of information, AI could replace human-centric coordination mechanisms. Examples like the AI firm "Moon Dark Side" illustrate radical experiments: no departments, titles, or traditional KPIs, with co-founders directly managing large teams and AI agents handling tasks from data processing to code generation. Block (founded by Jack Dorsey) is presented as a case study in building an "intelligent company." This model relies on two core components: a "company world model" (a real-time understanding of internal operations via digital traces) and a "customer world model" (built from real behavioral data, especially financial transactions). An intelligence layer uses these models to dynamically combine capabilities (e.g., payments, lending) to serve customers proactively, without pre-defined product roadmaps. In this structure, traditional roles shift. Middle managers are replaced by a system that handles coordination, while humans focus on individual contributions (ICs), direct responsibility (DRIs), or player-coach roles. The organization becomes flatter, faster, and more adaptive. The article concludes that AI is not just a tool for efficiency but a transformative force that could redefine organizational design, moving companies from human-led hierarchies to system-driven intelligence.

marsbit04/01 08:11

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

marsbit04/01 08:11

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.

marsbit03/28 08:06

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

marsbit03/28 08:06

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