Baru Saja, Model Dunia Pertama di Dunia dengan Frame Tinggi Super Lahir, Konten NVIDIA 0, Melaju 50 FPS

marsbitPublished on 2026-07-08Last updated on 2026-07-08

Abstract

MoWorld, model dunia "Flash World Model" pertama di dunia yang dikembangkan oleh MoXin Tech bersama tim akademisi Pan Yunhao dari Universitas Zhejiang, telah mencapai terobosan signifikan dalam kecepatan dan efisiensi. Model ini mampu melakukan inferensi real-time dengan kecepatan >50 FPS, mengatasi tantangan utama model dunia sebelumnya yang sering terhambat pada 5-10 FPS. Yang membedakan, MoWorld dibangun sepenuhnya menggunakan platform NPU (Neural Processing Unit) dalam negeri Tiongkok (seperti Huawei Ascend), tanpa bergantung pada GPU Nvidia. Pendekatan "full-stack" ini—mulai dari pelatihan, distilasi, hingga penyebaran—telah menurunkan biaya inferensi hingga 70% dibandingkan solusi GPU skala sebanding. Model 14B parameter ini didukung oleh pipeline data yang dikumpulkan dan diberi anotasi 3D secara mandiri, serta optimasi sistem seperti perhatian paralel ultra-padat dan kuantisasi presisi campuran dinamis untuk NPU. Kemampuannya termasuk kontrol kamera 6-DoF, konsistensi geometri tinggi, dan pembangkit adegan hingga 2000 frame. Aplikasi potensialnya mencakup: * **Game & Hiburan Interaktif:** Eksplorasi imersif real-time. * **Kecerdasan Berwujud & Mobil Otonom:** Simulator dunia virtual untuk pelatihan. * **Pembuatan Film:** Pra-preview real-time dan pengeditan lensa. * **Kembaran Digital & Rekonstruksi 3D:** Solusi rekonstruksi spasial yang presisi dan hemat biaya. Pencapaian MoWorld membuktikan kelayakan platform komputasi domestik untuk model dunia canggih ...

Model dunia akhirnya masuk ke era real-time. Ketika industri masih bergumul dengan 5FPS, 10FPS, sebuah tim dari China langsung mendorong model dunia interaktif real-time ke 50FPS. Yang lebih penting, mereka tidak menggunakan GPU NVIDIA.

Moxin Technology, yang berfokus pada penelitian dan industrialisasi model dunia 4D, bersama tim Akademisi Pan Yunhe dari Universitas Zhejiang, merilis MoWorld — Flash World Model pertama di dunia, sekaligus model dunia interaktif real-time pertama yang seluruhnya dibangun berdasarkan NPU domestik.

Dari pelatihan, distilasi hingga deployment, seluruh proses telah berhasil dijalankan dalam siklus tertutup daya komputasi domestik; biaya inferensi turun 70% dibandingkan dengan solusi GPU dengan skala yang sama.

Titik balik industrialisasi model dunia, mungkin datang lebih awal dari yang semua orang perkirakan.

Masalah Real-time yang Menjadi Hambatan Seluruh Industri

Ditembus oleh Tim China

Jika Anda pernah mencoba model dunia utama saat ini, kemungkinan besar akan merasakan hal yang sama:

  • Bisa dilihat, tapi tidak bisa dimainkan.
  • Robot membutuhkan pengambilan keputusan real-time.
  • Game membutuhkan umpan balik real-time.
  • Dunia digital membutuhkan simulasi real-time.

Penelitian sebelumnya menunjukkan bahwa jika frame rate di bawah 30FPS, semua rasa imersi akan hancur.

Inilah mengapa dalam waktu yang lama, model dunia selalu terjebak di laboratorium dan sulit benar-benar masuk ke skenario industri.

Real-time, pernah menjadi jurang terakhir yang menghalangi jalan komersialisasi model dunia.

Sekarang, jurang ini berhasil ditembus oleh sebuah tim dari China.

50FPS!

Model Dunia Pertama Kali Benar-benar Masuk Era Real-time

Laporan teknis telah dirilis, berat model dan kode akan segera diopen-source, dan layanan akan diberikan kepada publik berdasarkan supernode NPU domestik.

Laporan Teknis: https://moxin-tech.github.io/moworld/

Moxin Technology pertama kali mengusulkan konsep Flash World Model, MoWorld adalah "Flash World Model" pertama di industri yang mencapai inferensi >50FPS, sekaligus model dunia interaktif real-time berbiaya rendah pertama yang seluruhnya dibangun berdasarkan NPU domestik.

MoWorld untuk pertama kalinya mencapai siklus tertutup lengkap dari pelatihan, distilasi hingga deployment inferensi real-time di platform daya komputasi domestik sepenuhnya, sementara biaya dalam konfigurasi inferensi tipikal turun 70% dibandingkan dengan solusi GPU dengan skala yang sama.

Saat Semua Orang Menumpuk GPU

Mereka Memilih Jalan Lain yang Sulit tapi Benar

MoWorld dari awal, tidak dibangun di sekitar GPU, melainkan memilih jalur yang lebih sulit dan lebih sedikit dicoba — NPU domestik sepenuhnya.

Ini berarti, itu bukan sekadar memindahkan model ke chip domestik untuk inferensi, tetapi setiap tahap dari data, pelatihan, distilasi hingga deployment inferensi dirancang ulang berdasarkan NPU domestik.

Pertama, adalah data.

Dibandingkan model generasi video, model dunia tidak hanya membutuhkan video dan teks, tetapi juga informasi seperti lintasan kamera. Video internet jauh tidak memenuhi kebutuhan pelatihan.

Untuk itu, MoWorld membangun satu set sistem produksi dan tata kelola data yang lengkap, dan meng-upgrade-nya menjadi mesin data yang melayani model dunia.

Berdasarkan akumulasi teknis tim Moxin selama bertahun-tahun dalam pemodelan 3D/4D, pipeline data di balik MoWorld adalah pipeline yang sepenuhnya dikumpulkan sendiri dan sepenuhnya beranotasi 3D, tidak hanya meng-annotasi kamera, tetapi juga ukuran geometri dan struktur spasial objek. Informasi ini membangun basis data MoWorld yang kokoh.

Dan tantangan yang lebih sulit, terjadi pada tahap pelatihan dan inferensi.

Menyesuaikan karakteristik perangkat keras NPU domestik, MoWorld mendesain ulang sistem pelatihan, memperkenalkan teknologi seperti parallelisme perhatian ultra-padat, parallelisme token urutan panjang, dll., yang secara signifikan meredakan tekanan memori yang disebabkan oleh pelatihan video ultra-panjang, membuat model dunia untuk pertama kalinya memiliki kemampuan pelatihan dan inferensi panjang 2000 frame.

Dan pada tahap inferensi, tim terus mengoptimalkan tingkat sistem untuk NPU domestik, seperti eksekusi pipeline, parallelisme urutan hierarkis, kuantisasi presisi campuran dinamis, dan serangkaian optimasi lainnya.

Akhirnya, model dunia MoE dengan parameter 14B, di platform Huawei Ascend 910C CloudMatrix384 NPU mencapai kecepatan inferensi real-time melebihi 50FPS secara ekstrem.

Yang lebih penting, dalam konfigurasi inferensi tipikal, biaya inferensi turun 70% dibandingkan dengan solusi GPU dengan skala yang sama.

Bagi seluruh industri, ini bukan hanya jalur rekayasa baru, tetapi juga cara berpikir industrialisasi baru.

Pintu Termahal Model Dunia, Telah Didorong Terbuka

Selama ini, perkembangan model dunia selalu ada kontradiksi.

Model semakin kuat.

Biaya juga semakin tinggi.

Dulu, mendeploy model dunia berarti investasi GPU yang tinggi, pemeliharaan kluster yang rumit, dan biaya deployment yang sulit direplikasi.

Sekarang, kemampuan model dunia yang sama dapat dijalankan di platform daya komputasi domestik yang lebih menguntungkan secara biaya.

Ini tidak hanya mengubah cara model berjalan, tetapi juga mengubah jalan model dunia menuju industrialisasi.

Bagi perusahaan, ini berarti ambang batas deployment yang lebih rendah, verifikasi aplikasi yang lebih cepat, dan replikasi skala besar yang lebih mudah.

Bagi seluruh industri, ini berarti model dunia mulai beralih dari "bisa dibuat" ke "bisa digunakan", lalu ke "terjangkau".

Apa yang benar-benar mendorong suatu teknologi mengubah industri, bukanlah rekor tertinggi di laboratorium.

Tapi adalah pertama kalinya, membuat lebih banyak orang benar-benar bisa menggunakannya.

Model Dunia Keluar dari Laboratorium

Industri Mana yang Akan Menghadapi Perubahan

Beberapa tahun terakhir, model dunia selalu dianggap sebagai teknologi masa depan.

Tapi masa depan, akhirnya harus kembali ke kenyataan.

Ketika interaksi real-time menjadi mungkin, ketika biaya deployment mulai turun, nilai sebenarnya dari model dunia, baru saja mulai dilepaskan.

Yang akan berubah pertama, adalah industri yang paling bergantung pada pemahaman dunia nyata dan umpan balik real-time.

Game & Hiburan Interaktif: Interaksi Real-time, Eksplorasi Bebas

MoWorld mendukung kontrol kamera 6 derajat kebebasan penuh, pengguna dapat melalui W/A/S/D dan mouse mencapai pengalaman jelajah imersif tingkat film dan game.

Skenario nyata, HD, mendukung resolusi 1080P dan di atasnya. Baik pemandangan alam, anime, maupun game animasi, semuanya didukung.

Kecerdasan Berwujud & Mengemudi Otonom: Pelatihan Virtual, Verifikasi Nyata

Model dunia telah menjadi jembatan penting yang menghubungkan AI generatif dan kecerdasan berwujud.

MoWorld dapat menyediakan "lapangan latihan digital" berbiaya rendah dan tinggi realisme untuk robot, sistem mengemudi otonom, adalah simulator dunia paling potensial yang menggabungkan nilai simulasi dan nilai ekonomi untuk industri, dapat menyediakan lingkungan yang banyak dan presisi tinggi untuk semua tim mengemudi cerdas, membuat AI belajar berinteraksi dengan lingkungan fisik nyata di dunia virtual.

Kreasi Film: Penyutradaraan Gerakan Kamera, Pra-tinjau Real-time

Storyboard film tradisional membutuhkan siklus rendering yang panjang.

MoWorld memungkinkan kreator bebas menyesuaikan sudut pandang di dunia virtual yang dihasilkan, melihat pratinjau efek gambar secara real-time, mengedit gambar lensa secara presisi, kontrol lensa halus, mendukung gerakan kamera tingkat sutradara yang melampaui imajinasi.

Digital Twin & Rekonstruksi 3D: Rekonstruksi Spasial, Restorasi Presisi

Video yang dihasilkan MoWorld memiliki konsistensi geometri yang melampaui industri, dapat langsung digunakan untuk rekonstruksi 3D skenario dalam ruangan — presisi tinggi, struktur stabil, konsistensi spasial yang baik adalah efek signifikan MoWorld yang membedakannya dari rekan-rekan sejenis.

Ini menyediakan solusi yang menggabungkan presisi tinggi dan rasio biaya-manfaat untuk skenario seperti digital twin, visualisasi arsitektur, pameran virtual, game imersif, dll.

Model Dunia yang Diwakili oleh MoWorld

Saat Ini Berdiri di Momen DeepSeek AI Fisik

Beberapa tahun terakhir, AI menyelesaikan lompatan berturut-turut dari generasi teks, generasi gambar ke generasi video, setiap kali lompatan teknologi melahirkan sejumlah pemimpin industri baru.

Dan ketika AI mulai menuju model dunia interaktif real-time, jendela baru sedang terbuka.

Dibandingkan model bahasa besar dan model generasi video yang perlahan membentuk pola persaingan, model dunia masih berada di tahap awal industri, secara global sedang mengeksplorasi jalur implementasi rekayasa, standar industri jauh dari terbentuk.

Ini berarti, model dunia domestik mendapat kesempatan langka "garis start yang sama" — tidak hanya berpeluang berpartisipasi dalam persaingan, tetapi juga berpeluang ikut mendefinisikan standar teknis kecerdasan spasial generasi berikutnya.

Makna MoWorld, tidak hanya terletak pada pencapaian interaksi real-time lebih dari 50FPS, juga tidak hanya pada penurunan biaya inferensi 70% dibandingkan solusi GPU dengan skala yang sama.

Yang lebih penting, ini membuktikan masalah yang sebelumnya selalu dieksplorasi industri, tetapi tidak pernah terverifikasi:

Daya komputasi domestik sepenuhnya, juga mampu mendukung model dunia menuju interaksi real-time dan deployment industri.

Ini berarti, persaingan model dunia, sedang beralih dari "siapa yang memiliki model lebih besar", ke "siapa yang benar-benar bisa masuk ke dunia nyata".

Moxin Technology di balik MoWorld, dengan kemampuan model unik dan kemajuan industrialisasi yang menonjol, baru-baru ini menerima pendanaan lebih dari satu miliar dolar AS dari modal cadangan strategis nasional, lembaga dolar AS terkenal Timur Tengah, dana pasar terkemuka, serta lebih dari sepuluh modal industri; sebelumnya, Moxin Technology telah menerima investasi dari Hubble Investment di bawah Huawei dan dana di bawah Legend Holdings.

Era yang benar-benar milik model dunia, dimulai dari Flash World Model, akan melangkah maju dengan cepat.

Artikel ini berasal dari akun WeChat publik "Xin Zhi Yuan", penulis: ASI Qishi Lu

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Related Questions

QApa itu MoWorld dan mengapa dianggap sebagai terobosan?

AMoWorld adalah Flash World Model pertama di dunia yang dikembangkan oleh MoXin Tech (魔芯科技) dan tim akademisi Pan Yunhe dari Universitas Zhejiang. Ini merupakan model dunia interaktif real-time pertama yang dibangun sepenuhnya di atas NPU (Neural Processing Unit) dalam negeri. Terobosannya terletak pada kemampuannya mencapai kecepatan inferensi lebih dari 50 FPS, yang dianggap sebagai ambang batas untuk interaksi real-time, serta mengurangi biaya inferensi hingga 70% dibandingkan solusi GPU dengan skala serupa.

QApa tantangan utama yang dihadapi model dunia sebelum ini, dan bagaimana MoWorld mengatasinya?

ATantangan utama model dunia sebelumnya adalah real-time interactivity (interaktivitas waktu nyata). FPS (frame per second) yang rendah (misalnya 5 atau 10 FPS) menghancurkan imersi dan menghambat aplikasi praktis seperti robotika, game, dan simulasi dunia digital. MoWorld mengatasi ini dengan desain arsitektur dan optimasi sistem khusus untuk NPU dalam negeri, mencapai >50 FPS sehingga membuka jalan untuk aplikasi industri yang memerlukan respons real-time.

QMengapa MoWorld disebut sebagai 'solusi bebas NVIDIA' dan apa manfaatnya?

AMoWorld disebut 'bebas NVIDIA' atau 'kandungan NVIDIA 0' karena seluruh prosesnya—mulai dari pelatihan, distilasi, hingga penyebaran inferensi—dibangun dan dijalankan sepenuhnya di atas platform NPU (Neural Processing Unit) dalam negeri, khususnya Huawei Ascend, bukan pada GPU NVIDIA. Manfaat utamanya adalah menciptakan ekosistem komputasi tertutup yang mandiri, mengurangi ketergantungan pada perangkat keras impor, dan secara signifikan menurunkan biaya inferensi hingga 70% sehingga membuat model dunia lebih terjangkau untuk adopsi industri.

QIndustri apa saja yang berpotensi diubah oleh teknologi model dunia seperti MoWorld?

ABeberapa industri yang berpotensi diubah adalah: 1. **Game & Hiburan Interaktif**: Menyediakan pengalaman eksplorasi real-time dengan kontrol kamera 6-DoF. 2. **Kecerdasan Berwujud (Embodied AI) & Mobil Otonom**: Berfungsi sebagai 'lapangan latihan digital' yang murah dan akurat untuk pelatihan robot dan sistem otonom. 3. **Produksi Film**: Memungkinkan pratinjau real-time dan pengeditan presisi untuk storyboard dan gerakan kamera. 4. **Kembaran Digital & Rekonstruksi 3D**: Menghasilkan video dengan konsistensi geometris tinggi untuk rekonstruksi ruang dan visualisasi yang akurat.

QApa makna strategis dari keberhasilan MoWorld bagi perkembangan teknologi AI di China?

AKeberhasilan MoWorld memiliki makna strategis yang besar. Ini membuktikan bahwa tumpukan komputasi AI sepenuhnya dalam negeri (full-stack domestic NPU) mampu mendukung pengembangan dan penyebaran model dunia canggih yang memerlukan interaktivitas real-time. Ini menciptakan peluang bagi China untuk tidak hanya bersaing, tetapi juga berpotensi ikut menentukan standar teknologi untuk generasi berikutnya dari kecerdasan spasial (spatial AI), sekaligus mengurangi ketergantungan pada rantai pasokan teknologi asing di bidang AI yang kritis.

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This adaptability is paramount for sustaining relevance in the ever-changing crypto landscape. Community Engagement: The project emphasises community-driven initiatives, employing mechanisms that incentivise collaboration and feedback. By nurturing a strong community, SPERO,$$s$ can better address user needs and adapt to market trends. Focus on Inclusion: By offering low transaction fees and user-friendly interfaces, SPERO,$$s$ aims to attract a diverse user base, including individuals who may not previously have engaged in the crypto space. This commitment to inclusion aligns with its overarching mission of empowerment through accessibility. Timeline of SPERO,$$s$ Understanding a project's history provides crucial insights into its development trajectory and milestones. Below is a suggested timeline mapping significant events in the evolution of SPERO,$$s$: Conceptualisation and Ideation Phase: The initial ideas forming the basis of SPERO,$$s$ were conceived, aligning closely with the principles of decentralisation and community focus within the blockchain industry. Launch of Project Whitepaper: Following the conceptual phase, a comprehensive whitepaper detailing the vision, goals, and technological infrastructure of SPERO,$$s$ was released to garner community interest and feedback. Community Building and Early Engagements: Active outreach efforts were made to build a community of early adopters and potential investors, facilitating discussions around the project’s goals and garnering support. Token Generation Event: SPERO,$$s$ conducted a token generation event (TGE) to distribute its native tokens to early supporters and establish initial liquidity within the ecosystem. Launch of Initial dApp: The first decentralised application (dApp) associated with SPERO,$$s$ went live, allowing users to engage with the platform's core functionalities. Ongoing Development and Partnerships: Continuous updates and enhancements to the project's offerings, including strategic partnerships with other players in the blockchain space, have shaped SPERO,$$s$ into a competitive and evolving player in the crypto market. Conclusion SPERO,$$s$ stands as a testament to the potential of web3 and cryptocurrency to revolutionise financial systems and empower individuals. With a commitment to decentralised governance, community engagement, and innovatively designed functionalities, it paves the way toward a more inclusive financial landscape. As with any investment in the rapidly evolving crypto space, potential investors and users are encouraged to research thoroughly and engage thoughtfully with the ongoing developments within SPERO,$$s$. The project showcases the innovative spirit of the crypto industry, inviting further exploration into its myriad possibilities. While the journey of SPERO,$$s$ is still unfolding, its foundational principles may indeed influence the future of how we interact with technology, finance, and each other in interconnected digital ecosystems.

100 Total ViewsPublished 2024.12.17Updated 2024.12.17

What is $S$

What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

768 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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