Surat Internal Empat Halaman, Apa yang Diincar OpenAI?

marsbitPublished on 2026-04-14Last updated on 2026-04-14

Abstract

OpenAI mengeluarkan surat internal 4 halaman yang menganalisis persaingan dengan Anthropic. Chief Revenue Officer Denise Dresser menyoroti perbedaan pencatatan pendapatan: Anthropic melaporkan pendapatan tahunan $300 miliar (berbasis gross), sementara OpenAI menghitungnya hanya $220 miliar (basis net), meski keduanya mematuhi standar akuntansi. Data Ramp AI Index menunjukkan Anthropic cepat mengejar OpenAI dalam pangsa pasar enterprise, dengan hanya selisih 4,6% pada April. Anthropic bahkan unggul di sektor TI, keuangan, dan jasa profesional. Dalam hal kapasitas komputasi, OpenAI memimpin 1,9 GW vs 1,4 GW Anthropic, dengan rencana ekspansi besar hingga 30 GW pada 2030. Anthropic menargetkan 7-8 GW pada 2027. OpenAI juga beralih dari Microsoft ke Amazon, menerima investasi $50 miliar dan akses ke pelanggan AWS. Namun, Amazon juga merupakan investor utama dan mitra cloud Anthropic, menciptakan dinamika persaingan kompleks di platform Bedrock mereka.

Menurut pembukuan Anthropic, pendapatan tahunannya adalah $30 miliar, tetapi menurut konversi OpenAI, angka penjualan yang sama hanya bernilai $22 miliar. Kedua angka ini tidak dipalsukan. Ini adalah tebasan pertama yang dilontarkan oleh kepala pendapatan OpenAI, Denise Dresser, dalam surat internal empat halaman yang dibocorkan ke media pada 13 April.

Awalnya adalah sebuah memo karyawan yang diperoleh The Information. Dalam suratnya, Dresser melakukan tiga hal sekaligus: memuji kerja sama baru dengan Amazon yang "permintaannya sangat besar", mengakui bahwa kerja sama dengan Microsoft "membatasi kami dalam menjangkau pelanggan", dan menghabiskan banyak waktu untuk menganalisis angka pendapatan Anthropic. Surat ini bocor tepat satu minggu setelah Anthropic mengumumkan tonggak pendapatan tahunan $30 miliar.

Secara permukaan adalah komunikasi internal perusahaan, tetapi pada dasarnya adalah perang informasi yang dibangun dengan saksama. Untuk memahaminya, cara paling langsung adalah dengan melihat dari tiga dimensi: metode penghitungan pendapatan, lanskap persaingan di sisi perusahaan, dan jalur persiapan komputasi, lalu menempatkannya dalam bagan struktur kerja sama cloud yang sama.

Dari mana selisih akuntansi $8 miliar berasal

Anthropic melaporkan pendapatan tahunan $30 miliar, OpenAI mengatakan angka sebenarnya adalah $22 miliar. Selisih $8 miliar berasal dari pilihan metode pencatatan pendapatan yang sangat berbeda antara kedua perusahaan.

Anthropic menggunakan pencatatan berdasarkan kotor (Gross): ketika sebuah perusahaan membeli kuota penggunaan Claude melalui AWS, Anthropic memasukkan jumlah penuh uang tersebut sebagai pendapatan puncak (top-line revenue), kemudian memperlakukan bagi hasil yang dibayarkan ke Amazon sebagai biaya. OpenAI melakukan sebaliknya, mereka hanya mencatat jumlah bersih yang benar-benar diterima dari Microsoft, bagi hasil Microsoft tidak masuk ke pendapatan puncak.

Kedua cara ini sesuai dengan Prinsip Akuntansi Berterima Umum AS (GAAP). Logika Anthropic adalah bahwa mereka adalah "pihak utama" (principal) dalam transaksi pelanggan, penyedia cloud hanyalah saluran distribusi. Logika OpenAI adalah mereka menganggap Microsoft sebagai "agen", pencatatan hanya menghitung bagian yang benar-benar diterima. Akar perbedaan bukanlah pada siapa yang memalsukan, tetapi pada siapa yang lebih agresif menegaskan posisi dominannya dalam rantai penjualan.

Dresser menulis dalam memo tersebut, Anthropic "menggunakan metode pencatatan yang membuat angka pendapatan terlihat lebih besar", termasuk memasukkan jumlah bagi hasil penuh dari AWS dan Google ke dalam pendapatan puncak kotor. Makna tersirat dari kalimat ini tidak sulit dipahami, nanti ketika Anthropic menyerahkan prospektus S-1 ke SEC, auditor akan memutuskan mengenai metode ini, dan mungkin perlu dilakukan penyesuaian dan pengungkapan dengan metode yang diseragamkan. Dengan metode yang sama dikonversi, Anthropic adalah $22 miliar, OpenAI adalah $24 miliar, pihak yang memimpin berganti posisi.

Perlu dijelaskan bahwa pertumbuhan pendapatan Anthropic sendiri sudah berada di tingkat sejarah. Menurut data dari Bloomberg dan Sacra dll, pendapatan tahunannya tumbuh dari sekitar $9 miliar pada akhir kuartal empat 2025 menjadi $30 miliar sekarang, lebih dari tiga kali lipat dalam kurang dari lima bulan, dan ini terutama didorong oleh pembelian nyata pelanggan, bukan hanya dapat dijelaskan oleh penyesuaian metode pencatatan. Inti dari kontroversi akuntansi ini bukanlah Anthropic menyusut, tetapi OpenAI menggunakan "metode" sebagai pisau untuk menggambar ulang batasan.

Kecepatan mengejar di sisi perusahaan, lebih cepat dari yang diperkirakan kebanyakan orang

Ramp melacak perilaku pengeluaran AI aktual dari ribuan perusahaan di platformnya, merupakan sumber data pertama untuk menilai pilihan nyata di sisi perusahaan.

Data Ramp AI Index April: Pangsa Anthropic di antara pelanggan berbayar perusahaan naik menjadi 30.6%, OpenAI adalah 35.2%, kesenjangan menyempit dari 11 poin persentase pada Februari menjadi 4.6 poin persentase. Dengan rata-rata kenaikan bulanan Anthropic +6.3 poin persentase dalam dua bulan terakhir (ini sendiri已是 rekor kenaikan bulanan terbesar untuk metrik ini), mereka akan melampaui OpenAI dalam metrik ini dalam sekitar dua bulan.

Yang lebih patut diperhatikan adalah sinyal struktural. Di tiga industri dengan daya beli tinggi, keunggulan Anthropic telah menjadi fakta, Teknologi Informasi/Perangkat Lunak (63% vs 54%), Layanan Keuangan (52% vs 46%), Layanan Profesional (47% vs 44%) semuanya melampaui OpenAI. Ketiga industri ini kebetulan adalah area di mana anggaran AI perusahaan paling terkonsentrasi dan keputusan pembelian paling profesional. Ini berarti bahwa perusahaan-perusahaan yang memiliki suara paling besar dalam rantai pembelian AI, telah mulai secara kolektif condong ke Anthropic.

Dresser dalam memo tersebut secara langka mengakui, Anthropic "memiliki keunggulan signifikan di antara pelanggan perusahaan", alasannya adalah kemampuan pemrograman. Kalimat ini keluar dari internal OpenAI, bobotnya sangat berbeda dengan evaluasi eksternal, ini adalah sebuah perusahaan yang memberi tahu karyawannya sendiri, bahwa pihak lawan menang di medan tempur inti. Dia sekaligus menambahkan sebuah peringatan: "You do not want to be a single-product company in a platform war." ("Dalam perang platform, Anda tidak ingin menjadi perusahaan produk tunggal.") Ini mengingatkan karyawan, keunggulan Claude dalam pemrograman jika tidak dapat meluas ke tingkat platform, pada akhirnya hanyalah tiket masuk bukan tiket kapal.

Kesenjangan komputasi: hari ini mirip, tahun 2030 empat kali lipat

Kapasitas komputasi adalah dimensi persaingan yang paling sulit untuk dipersingkat dalam jangka pendek antar perusahaan AI, karena siklus pembangunannya bertahun-tahun, ambang batas dana puluhan miliar.

Angka saat ini terlihat tidak jauh berbeda: OpenAI sekitar 1.9 Gigawatt, Anthropic sekitar 1.4 Gigawatt, berbeda sekitar 35%. Dresser dalam memo menggambarkan Anthropic sebagai "operating on a meaningfully smaller curve", tetapi pernyataan ini dalam perbandingan kapasitas saat ini tidak berlebihan, kesenjangan itu nyata ada, hanya belum sampai pada tingkat yang menentukan.

Percabangan sebenarnya terjadi setelah tahun 2027. OpenAI merencanakan mencapai 30 Gigawatt komputasi pada tahun 2030, didukung oleh kontrak komputasi cloud $30 miliar selama lima tahun dengan Oracle, seluruh proyek infrastruktur Stargate, serta komitmen pembangunan total $1.4 triliun.

Jalur ketergantungan Anthropic adalah sebuah perjanjian chip khusus Broadcom, kapasitas 3.5 Gigawatt, diterapkan melalui Google Cloud, efektif mulai tahun 2027, ditambah dengan kluster pelatihan yang sudah ada di AWS, target akhir tahun 2027 adalah 7-8 Gigawatt.

Bahkan jika Anthropic sepenuhnya mencapai target tahun 2027, masih ada kesenjangan empat kali lipat dengan perencanaan OpenAI tahun 2030. Jurang ini secara teknis bukan tidak dapat diatasi, jika peningkatan efisiensi model cukup untuk membuat setiap unit komputasi menghasilkan lebih banyak keuntungan, Anthropic dapat membuat produk yang cukup baik dengan lebih sedikit komputasi.

Tetapi ini harus dilakukan under the premise bahwa momentum Claude di sisi perusahaan terus berlanjut, melalui pendapatan langganan yang berkelanjutan untuk mendukung biaya pembelian komputasinya: menurut perkiraan Sacra, biaya yang dibayarkan Anthropic kepada mitra cloud tahun ini akan sekitar $1.9 miliar, tahun 2027 akan naik menjadi sekitar $6.4 miliar.

Amazon, bertaruh pada dua pesaing sekaligus

Kalimat paling menarik dalam memo ini, adalah kualifikasi langsung Dresser terhadap hubungan kerja sama Microsoft, dia menulis kerja sama ini "juga membatasi kami dalam menjangkau perusahaan di tempat mereka berada".

Pergeseran OpenAI ke Amazon sudah sangat jelas: menurut laporan CNBC, pada bulan Februari tahun ini, Amazon mengumumkan investasi $50 miliar ke OpenAI, sekaligus mendapatkan资格 distribusi cloud pihak ketiga eksklusif untuk platform manajemen Agent enterprise OpenAI, Frontier.

Ini adalah peralihan aktif dari orbit Microsoft ke orbit Amazon, logika di belakangnya langsung, banyak infrastruktur AI pelanggan perusahaan sudah dibangun di platform Bedrock AWS, klausul eksklusif Microsoft membuat OpenAI sulit menjual langsung di sana.

Namun, sisi lain Amazon dalam persaingan ini juga patut diperhatikan, mereka adalah mitra infrastruktur cloud terbesar dan investor strategis Anthropic saat ini, investasi kumulatif $8 miliar, kluster Project Rainier yang dikerjakan bersama telah menerapkan sekitar 500.000 chip Trainium 2. Total taruhan Amazon dalam seluruh perlombaan AI adalah $58 miliar, mengalir secara bersamaan kepada dua lawan yang sedang bertempur langsung di pasar enterprise.

Ini bukanlah taruhan多元 dari satu penyedia cloud hyperscale, tetapi sebuah struktur yang lebih tepat: Amazon既是 "sekutu strategis dan penyandang dana terbesar" Anthropic, 又是 infrastruktur cloud baru OpenAI untuk "menggantikan Microsoft".

Ketika dua perusahaan memperebutkan pelanggan perusahaan yang sama, saluran yang diperebutkan kebetulan adalah platform Bedrock Amazon, platform ini secara bersamaan mendistribusikan model kedua perusahaan. Siapa pun yang memiliki tingkat konversi lebih tinggi di Bedrock, Amazon tetap untung, tetapi OpenAI dan Anthropic saling merugi.

Di bawah tekanan pangsa pasar perusahaan yang terus terkikis dan munculnya keretakan struktural dalam kerja sama Microsoft, OpenAI memilih untuk membangun narasi ulang dengan perang angka yang dihitung dengan saksama, sekaligus memanfaatkan Amazon untuk menyusun ulang saluran distribusi. Tiga kelompok angka masing-masing dibongkar, persaingan ini lebih kompleks dari yang ingin ditunjukkan oleh pihak mana pun.

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Related Questions

QApa perbedaan cara pencatatan pendapatan antara Anthropic dan OpenAI yang menyebabkan selisih $80 miliar?

AAnthropic menggunakan pencatatan pendapatan kotor (gross) dengan memasukkan seluruh nilai transaksi pelanggan melalui AWS sebagai pendapatan, lalu memperlakukan bagi hasil platform sebagai biaya. OpenAI menggunakan pencatatan pendapatan bersih (net) dengan hanya mencatat bagian yang benar-benar diterima dari Microsoft, tidak termasuk bagi hasil Microsoft.

QBagaimana tren persaingan OpenAI dan Anthropic di segmen enterprise menurut data Ramp AI Index?

ABerdasarkan data Ramp AI Index April, pangsa Anthropic pada pelanggan enterprise berbayar naik menjadi 30,6%, sementara OpenAI 35,2%. Jarak menyempit dari 11 poin persentase pada Februari menjadi hanya 4,6 poin. Anthropic bahkan sudah unggul di tiga industri kunci: teknologi informasi/perangkat lunak (63% vs 54%), jasa keuangan (52% vs 46%), dan jasa profesional (47% vs 44%).

QApa proyeksi perbedaan kapasitas komputasi (computing power) antara OpenAI dan Anthropic pada tahun 2030?

AOpenAI berencana mencapai 30 gigawatt (GW) kapasitas komputasi pada 2030 melalui proyek Stargate dan kontrak komputasi awan dengan Oracle. Anthropic menargetkan 7-8 GW pada akhir 2027. Meskipun Anthropic memenuhi targetnya, masih akan ada kesenjangan sekitar empat kali lipat dengan rencana OpenAI untuk 2030.

QMengapa OpenAI beralih bekerja sama dengan Amazon, dan bagaimana hubungan Amazon dengan kedua perusahaan ini?

AOpenAI beralih ke Amazon karena kemitraan eksklusif dengan Microsoft dianggap membatasi jangkauan mereka ke pelanggan enterprise yang infrastrukturnya sudah dibangun di platform AWS Bedrock. Amazon adalah sekutu strategis dan investor terbesar Anthropic (investasi $8 miliar) dan sekaligus menjadi penyedia infrastruktur cloud baru bagi OpenAI, menciptakan situasi di mana Amazon mendanai dan mendukung kedua pesaing langsung ini.

QApa makna peringatan 'You do not want to be a single-product company in a platform war' dalam memo internal OpenAI?

APeringatan ini, yang disampaikan oleh CRO OpenAI Denise Dresser, adalah pengakuan internal bahwa keunggulan Anthropic dalam pemrograman (melalui Claude) memberikan mereka keuntungan signifikan di pasar enterprise. Namun, ini juga memperingatkan bahwa keunggulan pada satu produk saja tidak cukup untuk memenangkan perang platform jangka panjang, di mana kemenangan ditentukan oleh ekosistem produk yang lebih luas dan integrasi platform, bukan hanya satu kemampuan unggul.

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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.

733 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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