Valuation Rout of Old Titans: The Demise of a Generation's Asset Valuation Framework

marsbitPublicado a 2026-06-26Actualizado a 2026-06-26

Resumen

"The Old Titans' Valuation Collapse: The Death of an Era's Valuation Framework" Between Alibaba's 2014 NYSE debut at $93.89 and its 2026 price of ~$95, twelve years have passed with zero price appreciation. This stagnation symbolizes a wholesale valuation reset for an entire generation of Chinese internet assets. Companies like Tencent, Pinduoduo, Meituan, Bilibili, and Kuaishou have seen catastrophic declines of 80-98% from their peaks. The core question arises: what framework now prices these companies, or has the framework itself expired? The valuation logic for Chinese internet stocks followed a clear "anchor-setting and anchor-removing" process. From 2014-2017, the dominant narrative was "US comparable discounting" – applying a growth premium and governance discount to US peers' multiples. This anchor loosened with the 2018 US-China trade war and the VIE structure risk, then was violently uprooted by the 2020-2021 regulatory crackdowns (Ant Group, Didi, anti-monopoly fines). The 2022 delisting panic and subsequent 2025-2026 geopolitical shocks (US military lists, AI espionage accusations) completed the demolition. The old "US对标打折" model is dead. However, this is not solely a China story. A structural mirror exists in US "old titan" stocks ("老登股"). In 2026, even Microsoft – with robust fundamentals – saw its PE compress from a 34x median to 22x, its worst performer status among the "Magnificent Seven" driven by a $190 billion annual AI capex crushing free cash flow. Th...

Author: Xiao Bing

On September 19, 2014, Alibaba listed on the New York Stock Exchange, closing at $93.89 on its first day. That day, Alibaba's market capitalization was $231 billion, exceeding the combined value of Oracle and Intel.

On June 25, 2026, Alibaba closed at $95.07.

Between these two numbers lies a full twelve years.

At the same time, Meituan closed at HK$65.45, falling below its 2018 IPO price of HK$69.

Pinduoduo hovered around $79, back to its level in June 2020.

Tencent's P/E ratio compressed to 12 times, nearly halved from its ten-year historical average of 25.7 times.

As for those younger Chinese internet companies, Bilibili fell from a high of $156 to $18, a drawdown of 89%; Kuaishou dropped from its Hong Kong IPO day high of HK$417 to HK$44, evaporating nearly 90% of its market value; iQiyi, Zhihu, Douyu, Huya—each experienced drawdowns between 85% and 98%.

An entire generation of Chinese internet assets has undergone collective valuation resets. What framework does the market use to price these companies? Or has the framework itself died?

The Establishment and Removal of Anchors

Looking back, the valuation logic of Chinese internet companies underwent an exceptionally clear process of "anchor establishment - anchor removal."

From 2014 to 2017, the core narrative for Chinese internet companies in global capital markets was "U.S. counterpart discounted."

Alibaba was China's Amazon, Tencent was China's Facebook plus China's Visa, Baidu was China's Google.

This methodology was concise and powerful: first find the valuation multiples of the comparable U.S. company, then multiply by a growth premium for the Chinese market and a governance discount, arriving at a reasonable price. Under this framework, Chinese internet companies generally enjoyed P/E ratios of 20 to 40 times.

Foreign capital flooded in, Chinese tech stocks were a must-have asset—this was the first anchor point.

In 2018, the China-U.S. trade war began. Global capital was forced for the first time to consider a question it had previously deliberately avoided: if Sino-U.S. relations shift from cooperation to competition, are the legal structures of those companies operating in China but listed in the U.S. still reliable? The VIE structure had never received explicit recognition from Chinese law, but no one cared during the bull market. The trade war exposed this hidden wound to sunlight for the first time. The valuation anchor loosened for the first time, but was not yet removed.

In October 2020, the suspension of Ant Group's IPO turned the market's pricing of "Chinese regulatory risk" from a vague discount factor into an explicit core variable. The antitrust storm of 2021 pushed this logic to its extreme. Alibaba was fined 18.2 billion yuan, Didi was investigated the day after its listing, and the after-school tutoring industry was wiped out overnight. Chinese tech stocks shifted from "growth premium" to "regulatory discount."

In 2022, the delisting panic for Chinese stocks reached its peak.

The SEC placed over a hundred Chinese stocks including Alibaba, Baidu, and JD.com on the "pre-delisting list." Although China and the U.S. eventually reached a compromise on audit working papers, the damage was done. Global index funds began systematically reducing their weighting in Chinese stocks, and some institutional investors liquidated entirely due to compliance requirements. The structural exit from the capital side turned the valuation compression from sentiment-driven to liquidity-driven.

In early 2025, the emergence of DeepSeek briefly ignited a wave of hope. Deutsche Bank called it China's "Sputnik moment," predicting the disappearance of the valuation discount for Chinese assets.

Alibaba and Tencent's stock prices rebounded over 60% in the first two months of 2025. However, this AI-narrative-driven revaluation lasted less than half a year before fizzling out. Entering 2026, the Pentagon placed Alibaba and Tencent on its "Chinese military-related companies" list, Anthropic publicly accused Chinese companies of launching large-scale distillation attacks on its Claude model, and Nasdaq introduced new listing rules targeting Chinese stocks, tightening liquidity thresholds. Every attempt to rebuild valuation anchors was swiftly destroyed by new geopolitical shocks.

At this point, the "U.S. counterpart discounted" valuation methodology has completely failed. The market no longer prices these companies based on their business models, growth rates, or profitability.

But it's not that simple.

The "Old Titans" on Both Sides of the Pacific

Shifting focus from the Chinese tech stocks on the NYSE to the American tech giants trading in the same building reveals: What the market has abandoned is far more than just Chinese internet companies.

Microsoft in 2026 was the worst-performing stock among the "Magnificent Seven," down over 20% for the year, falling from near $490 at the end of 2025 to around $360. Its P/E ratio compressed from a five-year median of 34 times to 22 times, the lowest level in three years.

The company's fundamentals remain intact: Azure cloud revenue grew 39% year-over-year, AI business annualized revenue exceeded $37 billion, and quarterly net profit reached a record $31.8 billion.

The market doesn't care about these numbers; it's more concerned about another number: $190 billion—Microsoft's full-year 2026 capital expenditure budget, almost entirely directed towards AI infrastructure. Quarterly capital expenditure alone exceeded the total for the entire year five years prior. Free cash flow dropped from $20.3 billion to $15.8 billion, the gap between profit and cash widening further.

Microsoft's experience is not an isolated case.

In 2026, all seven Magnificent Seven stocks underperformed the S&P 500. The four hyperscale cloud vendors (Amazon, Microsoft, Alphabet, Meta) have combined capital expenditure approaching $700 billion this year. The GPU clusters and data centers bought with this money will only become revenue over a 3 to 5-year depreciation cycle—investment upfront, returns deferred, with free cash flow crushed in the middle.

The deeper issue is: These companies are using massive capital to chase a technological paradigm that may disrupt their very own business models.

Microsoft's core revenue comes from Office subscriptions and Windows licensing, a SaaS model with per-user pricing nearing growth saturation. The AI era's business logic is consumption-based billing, paying per token used.

CEO Satya Nadella has publicly acknowledged that every Microsoft business charged per user will shift to a hybrid "user + usage" model. GitHub Copilot already switched to a fully consumption-based pricing model in June 2026, but the market's concern lies precisely in this: the old model had extremely high profit margins; whether the new model can maintain the same level, no one knows.

From a distance, this picture forms a structural mirror image of the predicament faced by Alibaba and Tencent.

Alibaba's core e-commerce business is a highly profitable advertising engine, as stable as Microsoft's Office, yet the valuation multiples assigned to it by the market keep falling. Tencent's WeChat ecosystem remains the most solid moat in the Chinese internet, but slowing game revenue growth and advertising business facing erosion from short-video platforms parallels Microsoft's search advertising being squeezed by Alphabet.

Old giants on both sides are desperately investing in AI to save themselves—Alibaba is pouring $55 billion into AI infrastructure, Microsoft $190 billion—yet markets on both sides have cast a vote of no confidence on "whether this money can be earned back."

Chinese internet practitioners often attribute their companies' decline to regulatory crackdowns and geopolitics, while American tech practitioners often blame Microsoft's decline on "spending too much." Peeling back the surface narratives, what's happening at the underlying level is the same thing: AI-native companies are redefining the entire technology industry's value chain, and the last generation's platform giants, regardless of nationality, are shifting from "companies defining the future" to "companies needing to prove they won't be left behind by the future."

On the Chinese internet, such stocks have acquired an accurate nickname—Old Titan Stocks.

Nikkei: The Precedent of a Dying Valuation System

This phenomenon of "the valuation coordinate system itself being replaced" is not unprecedented in global capital market history. The closest historical parallel is Japan after 1989.

On December 29, 1989, the Nikkei 225 index closed at 38,915 points, setting its all-time high.

That year, eight of the world's top ten companies by market capitalization were Japanese. NTT's stock price surged to 3 million yen per share two months after its 1987 IPO, with a market cap exceeding the combined value of America's eight largest companies at the time. Tokyo land prices were 350 times those of Manhattan. Sony acquired Columbia Pictures, and Mitsubishi bought Rockefeller Center.

Japanese investors of that era, much like Chinese internet practitioners in 2020, genuinely believed the system they were in would dominate the future of the global economy.

The trigger for the bubble's burst was the Bank of Japan raising interest rates. But the magnitude of the decline is only the most superficial feature of this crisis; the duration and nature of the decline were truly suffocating.

The Nikkei lost half its value in the first half of 1990 alone, and halved again to 14,000 points by 1992. If things stopped there, it would have been just an ordinary bubble burst and valuation correction. But the Nikkei didn't stop. It continued its slow decline for another ten years, falling to 7,600 points in 2003, an 80% drawdown from its peak.

The core reason for this decade-long decline was not the collapse of Japanese corporate competitiveness.

Toyota remained the world's best automaker, Sony continued to create groundbreaking consumer electronics. The problem lay at a deeper level: Global capital no longer believed in the "Japan premium."

Prior to 1989, the market's valuation framework for Japanese companies was "the world's most efficient manufacturing civilization + perpetually growing domestic market + unique corporate governance advantages."

After the bubble burst, these three assumptions were negated one by one. Manufacturing advantage was caught up by South Korea and China, the domestic market fell into deflation and an aging population, and corporate governance proved to be a haven for inefficiency. The old valuation framework died, but a new one was slow to be established.

In 1989, 32 of the world's top 50 companies by market cap were Japanese. By 2018, only Toyota remained.

How long did this vacuum period last? Approximately 25 years. The Nikkei didn't begin a genuine trend reversal until 2012, only reclaiming the 38,915-point level in February 2024. What catalyzed this revaluation was not a comprehensive revival of the Japanese economy.

One specific individual redefined "why one should buy Japanese assets" using a new language.

In the summer of 2019, Warren Buffett began buying shares of Japan's five major trading houses. The logic of this investment was entirely different from how the market had viewed Japan for the previous thirty years. Buffett didn't talk about GDP growth rates, population trends, or technological innovation. His reasons were exceedingly simple: these five companies had low valuations, high dividends, stable cash flows, and were genuinely advancing corporate governance reform. He hedged currency risk with yen-denominated debt financing and used his own credibility to endorse Japanese assets. By 2025, Berkshire Hathaway's stake in the five trading houses had approached 10%.

Buffett provided a brand new valuation language for Japanese assets. The old language was "Japan will dominate the global economy"; the new language was "low valuation + high dividend + corporate governance reform."

Where is the "New Language" for Chinese Internet?

Placing Japan's timeline side by side with the experience of Chinese internet, several structural similarities are impossible to ignore.

The old valuation framework is dead. The failure of the "U.S. counterpart discounted" model is akin to the collapse of the "Japan will rule the world" narrative. The corporate fundamentals of both did not completely deteriorate; what was negated were the macro assumptions underpinning the valuation premium. For Chinese internet, the macro assumption was "the deep integration between the Chinese market and global capital markets will continue"; for Japan, it was "the Japanese model represents the most efficient form of capitalism." Both assumptions have been disproven.

A new valuation framework has yet to be established. The market's current pricing of Chinese internet assets is essentially applying discounts on the ruins of the old framework. Just like Japan in 1995, the market knows the old price was wrong, but doesn't know what the new price should be.

Looking at Japan's experience, this vacuum period could be much longer than most expect. Japan took about 25 years from bubble burst to the market's acceptance of a new valuation framework. The systematic collapse of Chinese internet's valuation system began in 2020, only six years ago. If Japan's timeline has any reference value, the current position might only be the early-to-mid stage of this revaluation process.

However, there are also key differences between China and Japan. Japan's asset revaluation was accompanied by long-term deflation and population shrinkage, and corporate profitability did significantly deteriorate after the bubble burst. Chinese internet's leading companies are still profitable today—Tencent's annual net profit exceeds 220 billion yuan, Alibaba's core e-commerce cash flow remains robust. This means that if a new valuation language can be constructed, the revaluation speed could be faster than Japan's.

What could become the "new valuation language" for Chinese internet?

AI is the most obvious candidate, but also the most contradictory one.

Over the past two decades, the underlying business model of global internet companies has been highly convergent: capture user attention, aggregate traffic onto platforms, then monetize through advertising, e-commerce commissions, or in-game purchases.

AI is shaking the very foundation of this business.

When AI agents can compare prices, place orders, and plan trips for users, users no longer need to open Taobao and scroll page by page. When AI can recommend or even generate content based on preferences, the time users spend "scrolling" on any single platform shortens. When attention shifts from human eyes to AI agent interfaces, the point of traffic entry changes, and the platform's strategic position as a middleman is bypassed. This threatens e-commerce, search, social media, content, gaming—almost every core internet sector.

If any Chinese internet company can lead the transition from an "attention platform" to an "AI infrastructure and service provider," it could potentially acquire a brand new valuation language.

The cruelty of this path is that proactive disruption means dismantling the most profitable old business with one's own hands.

Taobao's advertising revenue is built on merchants bidding for rankings. If AI agents bypass rankings to help users choose products directly, this revenue will shrink. Every step of transformation erodes existing profits, while the profitability of the new model remains unproven.

If you chase AI, you bear the crushing of massive capital expenditure on free cash flow—Microsoft's P/E falling from 34x to 22x is precisely the outcome of this story. If you don't chase AI, you are judged by the market as being left behind by the times.

Microsoft is betting $190 billion on rewriting its revenue architecture. If it wins, it's the infrastructure of a new era. If it loses, it's history's greatest capital misallocation.

Shareholder returns are the second candidate. Both Tencent and Alibaba are engaged in large-scale buybacks; Tencent's dividend yield has risen to 1.25%. This closely resembles Buffett's logic for pricing Japanese trading houses: since the market is unwilling to pay for growth, use real buybacks and dividends to build a valuation floor. However, the current scale of buybacks remains limited relative to the market cap decline, insufficient yet to become an independent pricing anchor.

The current situation of Chinese internet assets is highly similar to Japanese assets around 1995: old framework dead, new framework unborn, the market waits in a vacuum for a person or event that can redefine "why one should buy."

The current position likely marks only the mid-stage of this prolonged revaluation.

This article represents only the analytical views of Trend Research and does not constitute any investment advice. Individual stock analysis mentioned is based on public information. Investors should make independent judgments and bear their own risks.

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Preguntas relacionadas

QAccording to the article, what was the core valuation methodology used for Chinese internet companies from 2014 to 2017, and why has it failed?

AThe core valuation methodology from 2014 to 2017 was 'US counterpart discounting.' This framework involved finding a comparable US company (e.g., Alibaba as China's Amazon, Tencent as China's Facebook + Visa), applying a premium for Chinese market growth, and a discount for governance risks. It has failed due to a series of structural shocks: the US-China trade war (2018) exposed legal/VIE risks, the intensified anti-monopoly and regulatory crackdowns (2020-2021), the delisting恐慌 of Chinese stocks from US exchanges (2022), and subsequent geopolitical tensions (e.g., US defense list inclusions, AI-related accusations in 2025-2026). These events systematically dismantled the assumptions of sustained integration between the Chinese market and global capital, rendering the old framework obsolete.

QWhat does the term 'laodeng gu' or 'old登 stocks' refer to in the context of the article?

AIn the article, 'laodeng gu' or 'old登 stocks' is a term originating from Chinese internet discourse that refers to a generation of aging platform giants, both in China (like Alibaba, Tencent) and the US (like Microsoft). These companies are characterized by their former dominance built on legacy business models (e.g., e-commerce, social media, SaaS software) that generated high-margin, stable profits. The term captures their current dilemma: they are transitioning from being 'companies that define the future' to 'companies that must prove they won't be淘汰 by the future.' They face massive capital expenditure in AI to avoid disruption, which crushes near-term free cash flow and creates uncertainty about future profitability, leading to severe valuation compression regardless of nationality.

QHow does the article use Japan's post-1989 experience as a historical parallel for China's current internet stock valuation crisis?

AThe article draws a parallel between Japan's post-1989 asset collapse and China's internet valuation crisis, highlighting a key structural similarity: the death of a dominant valuation framework. For Japan, the old framework of 'Japanese premium' (most efficient manufacturing + perpetual domestic growth + superior governance) collapsed after the bubble burst. For Chinese internet stocks, the 'US counterpart discounting' framework collapsed. In both cases, the underlying companies did not see an immediate, complete collapse in fundamentals, but the macroeconomic and geopolitical narratives supporting their premium valuations were proven false. Both entered a prolonged 'vacuum period' where the old pricing was known to be wrong, but a new, consensus valuation language had not yet been established, leading to a drawn-out revaluation process.

QWhat is the fundamental strategic dilemma facing 'old登 stocks' like Microsoft and Alibaba regarding AI investment, as described in the article?

AThe fundamental strategic dilemma is a catch-22 regarding AI investment. If these 'old登 stocks' aggressively pursue AI (like Microsoft's $190 billion annual Capex or Alibaba's $55 billion infrastructure build), they must endure a massive, upfront capital outlay that destroys near-term free cash flow and creates uncertainty about whether the new, usage-based AI business models can ever match the high-profit margins of their legacy, user/subscription-based models. The market punishes this uncertainty, as seen in Microsoft's compressed PE ratio. However, if they do not invest heavily in AI, the market will judge them as being obsolete and destined for disruption by AI-native companies, leading to an even steeper valuation decline. They are trapped between sacrificing current profits for an unproven future and being left behind.

QWhat are the two potential candidates for a 'new valuation language' for Chinese internet assets suggested by the article, and what are their respective challenges?

AThe article suggests two potential candidates for a new valuation language: 1. **AI Transformation:** The path involves evolving from an 'attention platform' to an 'AI infrastructure and service provider.' The challenge is its inherent contradiction: successfully transitioning requires actively undermining the company's most profitable legacy businesses (e.g., Alibaba's ad revenue from search rankings) before the new AI-driven revenue model's profitability is proven. It's a high-risk capital allocation gamble. 2. **Shareholder Returns:** Emulating Warren Buffett's rationale for investing in Japanese trading houses by emphasizing high dividends and aggressive share buybacks to establish a valuation floor based on cash returns. The current challenge is that the scale of buybacks and dividends from companies like Tencent and Alibaba, while growing, is still insufficient relative to their market cap decline to act as a standalone, convincing valuation anchor that can replace growth narratives.

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Enfoque en la Inclusión: Al ofrecer tarifas de transacción bajas e interfaces amigables para el usuario, SPERO,$$s$ busca atraer a una base de usuarios diversa, incluyendo a individuos que anteriormente pueden no haber participado en el espacio cripto. Este compromiso con la inclusión se alinea con su misión general de empoderamiento a través de la accesibilidad. Cronología de SPERO,$$s$ Entender la historia de un proyecto proporciona información crucial sobre su trayectoria de desarrollo y hitos. A continuación se presenta una cronología sugerida que mapea eventos significativos en la evolución de SPERO,$$s$: Fase de Conceptualización e Ideación: Las ideas iniciales que forman la base de SPERO,$$s$ fueron concebidas, alineándose estrechamente con los principios de descentralización y enfoque comunitario dentro de la industria blockchain. Lanzamiento del Whitepaper del Proyecto: Tras la fase conceptual, se lanzó un whitepaper completo que detalla la visión, los objetivos y la infraestructura tecnológica de SPERO,$$s$ para generar interés y retroalimentación de la comunidad. Construcción de Comunidad y Primeras Interacciones: Se realizaron esfuerzos de divulgación activa para construir una comunidad de primeros adoptantes y posibles inversores, facilitando discusiones en torno a los objetivos del proyecto y obteniendo apoyo. Evento de Generación de Tokens: SPERO,$$s$ llevó a cabo un evento de generación de tokens (TGE) para distribuir sus tokens nativos a los primeros seguidores y establecer liquidez inicial dentro del ecosistema. Lanzamiento de la dApp Inicial: La primera aplicación descentralizada (dApp) asociada con SPERO,$$s$ se puso en marcha, permitiendo a los usuarios interactuar con las funcionalidades centrales de la plataforma. Desarrollo Continuo y Alianzas: Actualizaciones y mejoras continuas a las ofertas del proyecto, incluyendo alianzas estratégicas con otros actores en el espacio blockchain, han moldeado a SPERO,$$s$ en un jugador competitivo y en evolución en el mercado cripto. Conclusión SPERO,$$s$ se erige como un testimonio del potencial de web3 y las criptomonedas para revolucionar los sistemas financieros y empoderar a los individuos. Con un compromiso con la gobernanza descentralizada, la participación comunitaria y funcionalidades diseñadas de manera innovadora, allana el camino hacia un paisaje financiero más inclusivo. Como con cualquier inversión en el espacio cripto que evoluciona rápidamente, se anima a los posibles inversores y usuarios a investigar a fondo y participar de manera reflexiva con los desarrollos en curso dentro de SPERO,$$s$. El proyecto muestra el espíritu innovador de la industria cripto, invitando a una mayor exploración de sus innumerables posibilidades. Mientras el viaje de SPERO,$$s$ aún se desarrolla, sus principios fundamentales pueden, de hecho, influir en el futuro de cómo interactuamos con la tecnología, las finanzas y entre nosotros en ecosistemas digitales interconectados.

88 Vistas totalesPublicado en 2024.12.17Actualizado en 2024.12.17

Qué es $S$

Qué es AGENT S

Agent S: El Futuro de la Interacción Autónoma en Web3 Introducción En el paisaje en constante evolución de Web3 y las criptomonedas, las innovaciones están redefiniendo constantemente cómo los individuos interactúan con las plataformas digitales. Uno de estos proyectos pioneros, Agent S, promete revolucionar la interacción humano-computadora a través de su marco agente abierto. Al allanar el camino para interacciones autónomas, Agent S busca simplificar tareas complejas, ofreciendo aplicaciones transformadoras en inteligencia artificial (IA). Esta exploración detallada profundizará en las complejidades del proyecto, sus características únicas y las implicaciones para el dominio de las criptomonedas. ¿Qué es Agent S? Agent S se presenta como un marco agente abierto innovador, diseñado específicamente para abordar tres desafíos fundamentales en la automatización de tareas informáticas: Adquisición de Conocimiento Específico del Dominio: El marco aprende inteligentemente de diversas fuentes de conocimiento externas y experiencias internas. Este enfoque dual le permite construir un rico repositorio de conocimiento específico del dominio, mejorando su rendimiento en la ejecución de tareas. Planificación a Largo Plazo de Tareas: Agent S emplea planificación jerárquica aumentada por la experiencia, un enfoque estratégico que facilita la descomposición y ejecución eficiente de tareas complejas. Esta característica mejora significativamente su capacidad para gestionar múltiples subtareas de manera eficiente y efectiva. Manejo de Interfaces Dinámicas y No Uniformes: El proyecto introduce la Interfaz Agente-Computadora (ACI), una solución innovadora que mejora la interacción entre agentes y usuarios. Utilizando Modelos de Lenguaje Multimodal de Gran Escala (MLLMs), Agent S puede navegar y manipular diversas interfaces gráficas de usuario sin problemas. A través de estas características pioneras, Agent S proporciona un marco robusto que aborda las complejidades involucradas en la automatización de la interacción humana con las máquinas, preparando el terreno para una multitud de aplicaciones en IA y más allá. ¿Quién es el Creador de Agent S? Si bien el concepto de Agent S es fundamentalmente innovador, la información específica sobre su creador sigue siendo elusiva. El creador es actualmente desconocido, lo que resalta ya sea la etapa incipiente del proyecto o la elección estratégica de mantener a los miembros fundadores en el anonimato. Independientemente de la anonimidad, el enfoque sigue siendo en las capacidades y el potencial del marco. ¿Quiénes son los Inversores de Agent S? Dado que Agent S es relativamente nuevo en el ecosistema criptográfico, la información detallada sobre sus inversores y patrocinadores financieros no está documentada explícitamente. La falta de información disponible públicamente sobre las bases de inversión u organizaciones que apoyan el proyecto plantea preguntas sobre su estructura de financiamiento y hoja de ruta de desarrollo. Comprender el respaldo es crucial para evaluar la sostenibilidad del proyecto y su posible impacto en el mercado. ¿Cómo Funciona Agent S? En el núcleo de Agent S se encuentra una tecnología de vanguardia que le permite funcionar de manera efectiva en diversos entornos. Su modelo operativo se basa en varias características clave: Interacción Humano-Computadora Similar a la Humana: El marco ofrece planificación avanzada de IA, esforzándose por hacer que las interacciones con las computadoras sean más intuitivas. Al imitar el comportamiento humano en la ejecución de tareas, promete elevar las experiencias de los usuarios. Memoria Narrativa: Empleada para aprovechar experiencias de alto nivel, Agent S utiliza memoria narrativa para hacer un seguimiento de las historias de tareas, mejorando así sus procesos de toma de decisiones. Memoria Episódica: Esta característica proporciona a los usuarios una guía paso a paso, permitiendo que el marco ofrezca apoyo contextual a medida que se desarrollan las tareas. Soporte para OpenACI: Con la capacidad de ejecutarse localmente, Agent S permite a los usuarios mantener el control sobre sus interacciones y flujos de trabajo, alineándose con la ética descentralizada de Web3. Fácil Integración con APIs Externas: Su versatilidad y compatibilidad con varias plataformas de IA aseguran que Agent S pueda encajar sin problemas en ecosistemas tecnológicos existentes, convirtiéndolo en una opción atractiva para desarrolladores y organizaciones. Estas funcionalidades contribuyen colectivamente a la posición única de Agent S dentro del espacio cripto, ya que automatiza tareas complejas y de múltiples pasos con una intervención humana mínima. A medida que el proyecto evoluciona, sus posibles aplicaciones en Web3 podrían redefinir cómo se desarrollan las interacciones digitales. Cronología de Agent S El desarrollo y los hitos de Agent S pueden encapsularse en una cronología que resalta sus eventos significativos: 27 de septiembre de 2024: El concepto de Agent S fue lanzado en un documento de investigación integral titulado “Un Marco Agente Abierto que Usa Computadoras Como un Humano”, mostrando las bases del proyecto. 10 de octubre de 2024: El documento de investigación fue puesto a disposición del público en arXiv, ofreciendo una exploración profunda del marco y su evaluación de rendimiento basada en el benchmark OSWorld. 12 de octubre de 2024: Se lanzó una presentación en video, proporcionando una visión visual de las capacidades y características de Agent S, involucrando aún más a posibles usuarios e inversores. Estos marcadores en la cronología no solo ilustran el progreso de Agent S, sino que también indican su compromiso con la transparencia y la participación comunitaria. Puntos Clave Sobre Agent S A medida que el marco Agent S continúa evolucionando, varios atributos clave destacan, subrayando su naturaleza innovadora y potencial: Marco Innovador: Diseñado para proporcionar un uso intuitivo de las computadoras similar a la interacción humana, Agent S aporta un enfoque novedoso a la automatización de tareas. Interacción Autónoma: La capacidad de interactuar de manera autónoma con las computadoras a través de GUI significa un salto hacia soluciones informáticas más inteligentes y eficientes. Automatización de Tareas Complejas: Con su metodología robusta, puede automatizar tareas complejas y de múltiples pasos, haciendo que los procesos sean más rápidos y menos propensos a errores. Mejora Continua: Los mecanismos de aprendizaje permiten a Agent S mejorar a partir de experiencias pasadas, mejorando continuamente su rendimiento y eficacia. Versatilidad: Su adaptabilidad en diferentes entornos operativos como OSWorld y WindowsAgentArena asegura que pueda servir a una amplia gama de aplicaciones. A medida que Agent S se posiciona en el paisaje de Web3 y criptomonedas, su potencial para mejorar las capacidades de interacción y automatizar procesos significa un avance significativo en las tecnologías de IA. A través de su marco innovador, Agent S ejemplifica el futuro de las interacciones digitales, prometiendo una experiencia más fluida y eficiente para los usuarios en diversas industrias. Conclusión Agent S representa un audaz avance en la unión de la IA y Web3, con la capacidad de redefinir cómo interactuamos con la tecnología. Aunque aún se encuentra en sus primeras etapas, las posibilidades para su aplicación son vastas y atractivas. A través de su marco integral que aborda desafíos críticos, Agent S busca llevar las interacciones autónomas al primer plano de la experiencia digital. A medida que nos adentramos más en los reinos de las criptomonedas y la descentralización, proyectos como Agent S sin duda desempeñarán un papel crucial en la configuración del futuro de la tecnología y la colaboración humano-computadora.

500 Vistas totalesPublicado en 2025.01.14Actualizado en 2025.01.14

Qué es AGENT S

Cómo comprar S

¡Bienvenido a HTX.com! Hemos hecho que comprar Sonic (S) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Sonic (S) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Sonic (S)Después de comprar tu Sonic (S), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Sonic (S)Tradear fácilmente con Sonic (S) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

1.0k Vistas totalesPublicado en 2025.01.15Actualizado en 2026.06.02

Cómo comprar S

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de S (S).

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