CBRS Laporan Keuangan Pertama Setelah IPO: Pendapatan Meningkat Dua Kali Lipat Namun Panduan Margin Kotor Turun Drastis, Realisasi Kontrak OpenAI Membutuhkan Waktu Lama

marsbitPublished on 2026-06-24Last updated on 2026-06-24

Abstract

**Laporan Keuangan Pertama Cerebras (CBRS): Pendapatan Naik 2x, Tapi Panduan Margin Kasar Turun Drastis** Cerebras Systems (CBRS) melaporkan laporan kuartal pertama setelah IPO. Pendapatan inti Q1 mencapai $191.3 juta, naik 92% (y/y) dan melampaui ekspektasi pasar. Namun, panduan margin kotor inti untuk Q2 turun drastis dari 46.5% menjadi kisaran 36%-38%, menyebabkan saham anjlok >10% setelah jam perdagangan. **Poin Kunci:** 1. **Pertumbuhan & Panduan Kuat:** Panduan pendapatan inti tahunan $855-$865 juta (naik 69%) lebih tinggi dari ekspektasi pasar. Pendapatan layanan cloud melonjak 178%. 2. **Transformasi Model Bisnis:** CBRS beralih dari "menjual chip" ke "menjual daya komputasi" (cloud). Untuk memenuhi kontrak komputasi inferensi besar dengan OpenAI (>$20 miliar) dan AWS, perusahaan lebih banyak menempatkan perangkat keras ke cloud miliknya sendiri, yang sementara mengurangi margin. 3. **Tantangan:** Konsentrasi pelanggan masih tinggi (86% pendapatan dari dua entitas terkait UEA). Realisasi pendapatan penuh dari kontrak OpenAI dan AWS membutuhkan waktu (2026/2027). Valuasi tetap tinggi (~50x P/S berdasarkan panduan 2026). 4. **Logika Bull vs Bear:** Para **bull** percaya keunggulan kecepatan chip Cerebras untuk inferensi AI akan merebut pangsa pasar, didukung kontrak besar. Para **bear** meragukan keunggulan tersebut bisa bertahan, khawatir dengan margin yang lebih rendah dari model cloud, konsentrasi pelanggan, dan risiko pelepasan saham insider jika kapitalisasi ...

Penulis: David, Chao Xiang Research

Panduan Chao Xiang: Cerebras (CBRS) mengumumkan laporan kuartalan pertamanya setelah IPO, pendapatan inti Q1 mencapai $191 juta, tumbuh 92% year-on-year (YoY), melampaui ekspektasi pasar. Namun, panduan margin kotor inti Q2 turun drastis dari 46,5% menjadi 36%-38%, menyebabkan harga saham turun lebih dari 10% dalam perdagangan setelah jam pasar. Perusahaan yang membuat chip dari satu wafer silikon utuh dan bertaruh di jalur AI inference ini memegang kontrak OpenAI senilai lebih dari $20 miliar dan kerangka kerja kerja sama dengan AWS. Panduan pendapatan tahunan berada di kisaran $855-865 juta. Data pertumbuhannya kuat, namun kontroversi valuasinya juga besar.

Poin Perhatian Utama

  1. Pendapatan melampaui ekspektasi, panduan bahkan lebih baik. Pendapatan inti Q1 sebesar $191,3 juta (YoY +92%), lebih tinggi dari konsensus ekspektasi sekitar $181 juta. Panduan pendapatan inti tahunan $855-865 juta (YoY +69%), lebih tinggi dari ekspektasi pasar $828 juta. Dalam ukuran GAAP, pendapatan layanan & cloud $82,8 juta, tumbuh 178% YoY, merupakan segmen dengan pertumbuhan tercepat.
  2. Panduan margin kotor yang turun drastis adalah negatif terbesar kuartal ini. Margin kotor inti Q1 sebesar 47%, meningkat hampir 5 poin persentase YoY. Namun panduan Q2 turun menjadi 36%-38%, turun sekitar 10 poin persentase dari Q1; panduan tahunan 38%-41%. Manajemen mengaitkan penyebabnya dengan kekurangan kapasitas data center: perusahaan sedang menyewa kembali sistem sementara dari pelanggan yang sudah membeli perangkat keras untuk menempatkan kapasitas, sehingga biaya jangka pendek memburuk. Harga saham turun >10% setelah jam pasar.
  3. Konsentrasi pelanggan menunjukkan arah perbaikan, namun jauh dari terselesaikan. 86% pendapatan tahun fiskal 2025 berasal dari dua entitas terkait UAE (MBZUAI 62%, G42 24%). OpenAI mulai berkontribusi pada pendapatan mulai Februari 2026, kerja sama dengan AWS diharapkan baru tercermin secara finansial pada 2027. Diversifikasi pendapatan sejati baru dapat diverifikasi pada 2027.
  4. Valuasi sudah mencerminkan tahun 2028. Dengan harga sekitar $200 setelah jam pasar, CBRS diperdagangkan pada sekitar 90 kali pendapatan dua belas bulan terakhir (P/S TTM); bahkan dengan panduan tahunan titik tengah $860 juta, forward P/S masih di atas 50 kali. Harga target median dari 10 analis yang meliput adalah $300 (range $250-$340), dengan premis implisit bahwa kontrak OpenAI >$20 miliar dan penerapan AWS terpenuhi tepat waktu dan sesuai volume.
  5. Faktor katalis dan tekanan jangka pendek berdampingan. Katalis: Percepatan penempatan daya komputasi 750MW OpenAI, implementasi solusi inference AWS, kapasitas data center baru online pada paruh kedua tahun. Faktor tekanan: Periode lock-up mengandung klausul pembebasan tidak konvensional (dapat dipicu jika kapitalisasi pasar melebihi $40 miliar, saat ini mendekati ambang batas tersebut), jalur pemulihan margin kotor tidak jelas, OpenAI sendiri belum profitabel dan telah mengurangi beberapa komitmen daya komputasi.

Laporan Keuangan Mengungkap Transformasi Model Bisnis: Dari Menjual Chip ke Menjual Daya Komputasi

Perubahan yang paling mudah terlewatkan dalam laporan Q1 adalah perubahan struktur pendapatan.

Dalam ukuran inti, pendapatan perangkat keras $111,6 juta, menyumbang 58% total pendapatan; pendapatan layanan & cloud $79,8 juta, menyumbang 42%. Pada periode yang sama setahun lalu, rasio ini kira-kira 70:30. Pendapatan layanan cloud tumbuh 167% YoY, hampir tiga kali lipat kecepatan pertumbuhan perangkat keras.

Manajemen menyampaikan tren ini lebih jelas dalam konferensi telepon:

Pendapatan perangkat keras akan turun secara bertahap dalam beberapa kuartal mendatang, karena perusahaan akan menempatkan lebih banyak kapasitas perangkat keras ke cloud milik sendiri untuk memenuhi kontrak daya komputasi inference OpenAI dan AWS, bukan menjualnya langsung ke pelanggan. Cerebras sedang berubah dari "perusahaan penjual chip" menjadi "perusahaan penjual daya komputasi".

Transformasi ini juga secara langsung menjelaskan mengapa margin kotor Q2 turun drastis.

Dalam konferensi telepon, seorang analis menanyakan detail penempatan kapasitas, manajemen mengungkapkan:

Kendala perusahaan saat ini bukan pada pasokan chip dari TSMC, melainkan pada ruang fisik data center. Untuk segera menyerahkan daya komputasi ke OpenAI, Cerebras sedang "menyewa kembali sementara" sistem perangkat keras yang telah dijual dari G42 (pelanggan terbesar sebelumnya dan juga investor minoritas).

Menyewa fasilitas pihak ketiga untuk menempatkan sistem milik sendiri akan memburuk struktur biaya jangka pendek, ini adalah penyebab utama turunnya panduan margin kotor dari 47% menjadi 36%-38%. Manajemen memberikan jadwal bahwa data center baru akan mulai online pada paruh kedua tahun, saat itu tekanan biaya akan mereda.

Struktur keuangan kontrak OpenAI ini juga layak untuk dibongkar. Di permukaan, ini adalah pembelian daya komputasi jangka panjang senilai lebih dari $20 miliar, namun di bawahnya terdapat tiga lapisan hubungan yang tumpang tindih: OpenAI menyediakan pinjaman modal kerja $1 miliar ke Cerebras (tercermin sebagai pinjaman lancar $621 juta dan pinjaman tidak lancar $362 juta di neraca Q1), sekaligus memperoleh warrant saham Cerebras.

Dengan kata lain, OpenAI memainkan tiga peran sekaligus terhadap Cerebras: pelanggan terbesar, kreditur, dan calon pemegang saham. Peringatan risiko dalam S-1 menyatakan, jika Cerebras gagal memberikan kapasitas sesuai perjanjian, OpenAI berhak mengakhiri kontrak dan memicu pelunasan pinjaman.

Kerangka kerja kerja sama AWS menggunakan arsitektur "split inference": Chip Trainium 3 AWS bertanggung jawab untuk memproses input kata kunci (tahap prefill), sistem CS-3 Cerebras khusus bertanggung jawab untuk menghasilkan output dengan kecepatan tinggi (tahap decode). Desain ini memungkinkan Cerebras tidak perlu menanggung rantai inference penuh, hanya melakukan bagian di mana keunggulan kecepatannya paling besar. Namun manajemen menolak mengungkapkan skala spesifik kerja sama AWS pada sesi Q&A, dan menyatakan kontribusi pendapatan baru akan tercermin secara finansial pada 2027.

Ciri umum dari dua kontrak besar ini adalah: Volume kontrak sangat besar, namun jalur realisasinya panjang, dan sangat bergantung pada kemajuan pembangunan data center Cerebras.

Panduan pendapatan tahunan $855-865 juta berarti tiga kuartal berikutnya perlu rata-rata mencapai sekitar $220 juta per kuartal, dengan pertumbuhan yang harus meningkat setiap kuartal. Pernyataan manajemen adalah "pertumbuhan YoY setiap kuartal tahun 2026 akan meningkat, lebih banyak pendapatan terkonsentrasi di paruh kedua tahun".

Logika Bull (Optimis): Sembilan Bank Investasi Sama-sama Merekomendasikan Beli, Apa yang Mereka Beli

Pada 8 Juni, hari berakhirnya masa tenang IPO, sembilan bank penjamin emisi meluncurkan liputan secara bersamaan, semuanya memberikan peringkat beli atau overweight. CBRS pada hari itu naik 18,3% dalam satu hari. Jenis pandangan kolektif "membuka pintu air" seperti ini tidak jarang dalam saham baru AS (bank penjamin secara alami memiliki kepentingan yang terikat), namun logika taruhan mereka menunjuk pada proposisi inti yang sama.

Proposisi 1: Medan perang daya komputasi AI sedang beralih dari pelatihan (training) ke inferensi (inference), dan aturan kompetisi dalam skenario inference berbeda dengan pelatihan.

Analis Morgan Stanley Joseph Moore dalam laporan liputan pertamanya tanggal 8 Juni memberikan peringkat overweight, target harga $250. Argumen intinya adalah: Skenario pelatihan mengutamakan throughput daya komputasi total, kluster GPU Nvidia mendominasi mutlak di sini; skenario inference mengutamakan kecepatan dan latensi respons tunggal, karena model perlu memproses jutaan permintaan pengguna per detik, cepat lambat secara langsung memengaruhi biaya layanan dan pengalaman pengguna. Chip skala wafer Cerebras karena kapasitas SRAM on-chip jauh melebihi GPU biasa, data tidak perlu sering dipindahkan ke penyimpanan eksternal, memiliki keunggulan struktural dalam latensi inference. Ungkapan Moore adalah, Cerebras adalah "satu-satunya perusahaan yang menerapkan prosesor skala wafer secara komersial", membentuk keunggulan pertama terhadap Nvidia.

Analis Citi Atif Malik memberikan target harga tertinggi dalam liputan, $340. Mizuho dalam laporan riset tanggal 8 Juni menambahkan detail teknis: Chip WSE-3 memiliki SRAM internal 44GB, beberapa kali lipat lebih besar dari TPU terbaru Google dan LPU Groq, kesenjangan di tingkat perangkat keras ini tidak dapat diatasi dalam waktu singkat melalui optimisasi arsitektur.

Proposisi 2: Dua kontrak besar mendorong Cerebras dari "cerita teknologi" ke "cerita pendapatan".

Kontrak OpenAI lebih dari $20 miliar, mencakup daya komputasi inference 750MW, pengiriman multi-tahun. Dengan amortisasi lima tahun, hanya kontrak ini saja menyumbang sekitar $4 miliar pendapatan per tahun, hampir 5 kali lipat dari panduan pendapatan tahunan 2026 titik tengah. Kerja sama AWS meskipun manajemen menolak mengungkapkan jumlah spesifik, namun kerangka kerja sudah dikonfirmasi: Kemampuan inference Cerebras akan tersedia untuk pelanggan perusahaan global melalui Amazon Bedrock.

Data laporan Q1 memberikan validasi awal. OpenAI mulai menempatkan sistem Cerebras dari Februari, pendapatan layanan cloud dalam satu kuartal melonjak dari kurang dari $30 juta tahun lalu menjadi hampir $80 juta. Sikap manajemen adalah "pertumbuhan YoY setiap kuartal tahun 2026 akan meningkat, lebih banyak pendapatan terkonsentrasi di paruh kedua tahun", panduan tahunan $855-865 juta lebih tinggi dari konsensus ekspektasi $828 juta.

Proposisi 3: Kepadatan liputan setelah periode tenang berakhir itu sendiri merupakan sebuah sinyal.

Target harga median 10 analis adalah $300, terendah $250 (Morgan Stanley), tertinggi $340 (Citi). Dengan harga setelah jam pasar $200, target harga median menyiratkan ruang kenaikan sekitar 50%. Wedbush (target $270), Needham ($300), Barclays ($280), TD Cowen ($275), Craig-Hallum (Beli) semua memulai liputan pada minggu yang sama.

Asumsi dasar logika bull dapat disimpulkan dalam satu kalimat:

Jika AI inference menjadi pasar daya komputasi yang lebih besar daripada pelatihan (banyak lembaga memperkirakan pengeluaran daya komputasi inference akan melampaui pelatihan pada 2027), dan keunggulan kecepatan Cerebras nyata dan berkelanjutan, maka ia hanya perlu mengambil 3%-5% dari pasar di mana Nvidia menguasai >80% pangsa, sudah cukup untuk mendukung valuasi saat ini.

Logika Bear (Pesimis): Margin Kotor, Konsentrasi Pelanggan, dan Kerapuhan Valuasi $50 Miliar

Tiga proposisi bull, masing-masing memiliki sanggahan dari bear.

Sanggahan 1: Parit pertahanan (moat) keunggulan kecepatan inference mungkin lebih sempit dari yang dibayangkan.

Keunggulan kecepatan Cerebras dibangun di atas kapasitas SRAM on-chip, namun Nvidia tidak tinggal diam. NVIDIA merilis chip B300 pada Maret yang secara signifikan meningkatkan bandwidth HBM, arsitektur LPU Groq juga beriterasi cepat pada skenario inference.

Dari sudut pandang lain: Pelanggan Cerebras saat ini sangat terkonsentrasi pada OpenAI dan AWS, sementara OpenAI juga merupakan salah satu pembeli GPU Nvidia terbesar, chip Trainium buatan sendiri AWS juga mencakup semakin banyak skenario inference. Klien besar Cerebras secara bersamaan bertaruh pada alternatif, ini berarti premium kecepatannya akan terus menghadapi tekanan negosiasi harga.

Sanggahan 2: Penurunan margin kotor mungkin tidak hanya "sementara".

Manajemen mengaitkan penyebab turunnya margin kotor Q2 dari 47% menjadi 36%-38% dengan biaya sewa sementara akibat kekurangan kapasitas data center. Namun penjelasan ini berasumsi "biaya akan membaik setelah data center baru online di paruh kedua tahun".

Mengingat skala pendapatan akan melonjak di paruh kedua tahun (manajemen secara eksplisit menyatakan pendapatan terkonsentrasi di bagian belakang), dan panjatan kapasitas data center baru itu sendiri juga membutuhkan waktu dan investasi modal, jalur pemulihan ini tidak mudah.

Masalah yang lebih dalam adalah dampak transformasi model bisnis itu sendiri terhadap margin kotor. Cerebras beralih dari menjual perangkat keras ke menjual daya komputasi cloud, berarti harus menanggung biaya pembangunan, operasi, dan depresiasi data center. Dengan biaya depresiasi data center yang dibangun sendiri masuk ke dalam, apakah margin kotor layanan cloud dapat dipertahankan di atas 50% masih belum pasti. Plafon profitabilitas model bisnis ini belum diuji.

Sanggahan 3: Konsentrasi pelanggan adalah masalah yang "berganti nama tetapi tidak terselesaikan".

Tahun 2024, G42 sendiri menyumbang 85% pendapatan Cerebras. Tahun 2025, pangsa G42 turun menjadi 24%, namun MBZUAI (Universitas Kecerdasan Buatan Mohamed bin Zayed) melonjak dari nol menjadi 62%. Prospektus S-1 secara jelas menandai kedua entitas ini sebagai "pihak terkait". Dua entitas terkait UAE bersama-sama masih menyumbang 86% pendapatan. Diversifikasi sumber pendapatan lebih merupakan pergantian nama, bukan penyebaran substantif.

Terakhir, periode lock-up IPO CBRS mengandung klausul tidak konvensional:

Jika kapitalisasi pasar perusahaan terus melebihi $40 miliar, saham internal dapat dibebaskan lebih awal. Dengan harga setelah jam pasar $200, kapitalisasi pasar saat ini sekitar $45 miliar, sudah mendekati garis pemicu. Di sisi posisi short (bear), hingga 29 Mei, rasio short interest adalah 17,15% dari saham yang beredar, termasuk level yang agak tinggi. Begitu periode lock-up dibebaskan lebih awal melepaskan banyak saham internal, ditambah tekanan short yang sudah ada, harga saham mungkin menghadapi penjualan terpusat.

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Related Questions

QApa poin positif utama dari laporan keuangan kuartal pertama Cerebras (CBRS) setelah IPO?

APoin positif utamanya adalah pendapatan inti Q1 sebesar $191,3 juta, meningkat 92% secara tahunan (YoY) dan melampaui ekspektasi pasar sekitar $181 juta. Panduan pendapatan inti untuk tahun ini juga dinaikkan menjadi $855-865 juta (naik 69% YoY), lebih tinggi dari ekspektasi pasar $828 juta. Selain itu, pendapatan layanan cloud dan layanan (GAAP) tumbuh pesat sebesar 178% YoY.

QApa penyebab utama penurunan panduan margin laba kotor CBRS untuk Q2, dan bagaimana dampaknya terhadap harga saham?

APanduan margin laba kotor inti untuk Q2 turun tajam dari 47% menjadi 36%-38% terutama karena kendala kapasitas pusat data. Untuk mempercepat penyebaran daya komputasi bagi OpenAI, Cerebras terpaksa 'menyewa kembali sementara' sistem perangkat keras yang telah dijual kepada klien seperti G42. Biaya sewa pihak ketiga ini secara sementara memperburuk struktur biaya. Berita ini menyebabkan harga saham CBRS turun lebih dari 10% dalam perdagangan setelah jam pasar.

QBagaimana struktur dan ketergantungan pendapatan pelanggan utama Cerebras?

AKetergantungan pada sejumlah kecil pelanggan masih sangat tinggi. Pada tahun fiskal 2025, 86% pendapatan berasal dari dua entitas terkait Uni Emirat Arab: MBZUAI (62%) dan G42 (24%). Meskipun kontribusi G42 menurun, ketergantungan berpindah ke MBZUAI, sehingga diversifikasi sebenarnya belum terwujud. OpenAI baru akan mulai berkontribusi pada pendapatan mulai Februari 2026, sedangkan kolaborasi dengan AWS baru akan berdampak finansial pada tahun 2027.

QApa logika utama yang digunakan oleh analis yang bullish (optimis) terhadap saham CBRS?

ALogika bull berpusat pada tiga proposisi: 1) Peralihan medan perang komputasi AI dari pelatihan ke inferensi, di mana chip wafer-scale Cerebras memiliki keunggulan struktural dalam kecepatan dan latensi. 2) Kontrak besar dengan OpenAI (>$200 miliar) dan kemitraan dengan AWS telah mengubah Cerebras dari 'cerita teknologi' menjadi 'cerita pendapatan' dengan visibilitas pertumbuhan jangka panjang. 3) Setelah masa tenang berakhir, 9 bank sekaligus memberikan rating beli dengan harga target rata-rata sekitar $300, menunjukkan keyakinan institusional.

QApa kekhawatiran atau argumen utama dari pihak yang bearish (pesimis) terhadap prospek CBRS?

APihak bearish mengemukakan beberapa kekhawatiran: 1) Keunggulan kecepatan inferensi Cerebras mungkin tidak seluas yang dibayangkan, karena pesaing seperti NVIDIA dan Groq juga terus berinovasi. 2) Penurunan margin laba kotor mungkin bukan fenomena sementara, terkait dengan transformasi model bisnis dari penjualan perangkat keras ke penyediaan daya komputasi cloud yang memerlukan investasi modal besar dan biaya operasi pusat data. 3) Konsentrasi pendapatan pada entitas terkait tetap menjadi risiko struktural. 4) Adanya klausul pelepasan kuncian saham secara prematur yang dapat dipicu jika kapasitas pasar bertahan di atas $40 miliar, berpotensi menyebabkan tekanan jual besar-besaran dari pihak dalam.

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Sonic: Pioneering the Future of Gaming in Web3 Introduction to Sonic In the ever-evolving landscape of Web3, the gaming industry stands out as one of the most dynamic and promising sectors. At the forefront of this revolution is Sonic, a project designed to amplify the gaming ecosystem on the Solana blockchain. Leveraging cutting-edge technology, Sonic aims to deliver an unparalleled gaming experience by efficiently processing millions of requests per second, ensuring that players enjoy seamless gameplay while maintaining low transaction costs. This article delves into the intricate details of Sonic, exploring its creators, funding sources, operational mechanics, and the timeline of significant events that have shaped its journey. What is Sonic? Sonic is an innovative layer-2 network that operates atop the Solana blockchain, specifically tailored to enhance the existing Solana gaming ecosystem. It accomplishes this through a customised, VM-agnostic game engine paired with a HyperGrid interpreter, facilitating sovereign game economies that roll up back to the Solana platform. The primary goals of Sonic include: Enhanced Gaming Experiences: Sonic is committed to offering lightning-fast on-chain gameplay, allowing players and developers to engage with games at previously unattainable speeds. Atomic Interoperability: This feature enables transactions to be executed within Sonic without the need to redeploy Solana programmes and accounts. This makes the process more efficient and directly benefits from Solana Layer1 services and liquidity. Seamless Deployment: Sonic allows developers to write for Ethereum Virtual Machine (EVM) based systems and execute them on Solana’s SVM infrastructure. This interoperability is crucial for attracting a broader range of dApps and decentralised applications to the platform. Support for Developers: By offering native composable gaming primitives and extensible data types - dining within the Entity-Component-System (ECS) framework - game creators can craft intricate business logic with ease. Overall, Sonic's unique approach not only caters to players but also provides an accessible and low-cost environment for developers to innovate and thrive. Creator of Sonic The information regarding the creator of Sonic is somewhat ambiguous. However, it is known that Sonic's SVM is owned by the company Mirror World. The absence of detailed information about the individuals behind Sonic reflects a common trend in several Web3 projects, where collective efforts and partnerships often overshadow individual contributions. Investors of Sonic Sonic has garnered considerable attention and support from various investors within the crypto and gaming sectors. Notably, the project raised an impressive $12 million during its Series A funding round. The round was led by BITKRAFT Ventures, with other notable investors including Galaxy, Okx Ventures, Interactive, Big Brain Holdings, and Mirana. This financial backing signifies the confidence that investment foundations have in Sonic’s potential to revolutionise the Web3 gaming landscape, further validating its innovative approaches and technologies. How Does Sonic Work? Sonic utilises the HyperGrid framework, a sophisticated parallel processing mechanism that enhances its scalability and customisability. Here are the core features that set Sonic apart: Lightning Speed at Low Costs: Sonic offers one of the fastest on-chain gaming experiences compared to other Layer-1 solutions, powered by the scalability of Solana’s virtual machine (SVM). Atomic Interoperability: Sonic enables transaction execution without redeployment of Solana programmes and accounts, effectively streamlining the interaction between users and the blockchain. EVM Compatibility: Developers can effortlessly migrate decentralised applications from EVM chains to the Solana environment using Sonic’s HyperGrid interpreter, increasing the accessibility and integration of various dApps. Ecosystem Support for Developers: By exposing native composable gaming primitives, Sonic facilitates a sandbox-like environment where developers can experiment and implement business logic, greatly enhancing the overall development experience. Monetisation Infrastructure: Sonic natively supports growth and monetisation efforts, providing frameworks for traffic generation, payments, and settlements, thereby ensuring that gaming projects are not only viable but also sustainable financially. Timeline of Sonic The evolution of Sonic has been marked by several key milestones. Below is a brief timeline highlighting critical events in the project's history: 2022: The Sonic cryptocurrency was officially launched, marking the beginning of its journey in the Web3 gaming arena. 2024: June: Sonic SVM successfully raised $12 million in a Series A funding round. This investment allowed Sonic to further develop its platform and expand its offerings. August: The launch of the Sonic Odyssey testnet provided users with the first opportunity to engage with the platform, offering interactive activities such as collecting rings—a nod to gaming nostalgia. October: SonicX, an innovative crypto game integrated with Solana, made its debut on TikTok, capturing the attention of over 120,000 users within a short span. This integration illustrated Sonic’s commitment to reaching a broader, global audience and showcased the potential of blockchain gaming. Key Points Sonic SVM is a revolutionary layer-2 network on Solana explicitly designed to enhance the GameFi landscape, demonstrating great potential for future development. HyperGrid Framework empowers Sonic by introducing horizontal scaling capabilities, ensuring that the network can handle the demands of Web3 gaming. Integration with Social Platforms: The successful launch of SonicX on TikTok displays Sonic’s strategy to leverage social media platforms to engage users, exponentially increasing the exposure and reach of its projects. Investment Confidence: The substantial funding from BITKRAFT Ventures, among others, emphasizes the robust backing Sonic has, paving the way for its ambitious future. In conclusion, Sonic encapsulates the essence of Web3 gaming innovation, striking a balance between cutting-edge technology, developer-centric tools, and community engagement. As the project continues to evolve, it is poised to redefine the gaming landscape, making it a notable entity for gamers and developers alike. As Sonic moves forward, it will undoubtedly attract greater interest and participation, solidifying its place within the broader narrative of blockchain gaming.

1.7k Total ViewsPublished 2024.04.04Updated 2024.12.03

What is SONIC

What is $S$

Understanding SPERO: A Comprehensive Overview Introduction to SPERO As the landscape of innovation continues to evolve, the emergence of web3 technologies and cryptocurrency projects plays a pivotal role in shaping the digital future. One project that has garnered attention in this dynamic field is SPERO, denoted as SPERO,$$s$. This article aims to gather and present detailed information about SPERO, to help enthusiasts and investors understand its foundations, objectives, and innovations within the web3 and crypto domains. What is SPERO,$$s$? SPERO,$$s$ is a unique project within the crypto space that seeks to leverage the principles of decentralisation and blockchain technology to create an ecosystem that promotes engagement, utility, and financial inclusion. The project is tailored to facilitate peer-to-peer interactions in new ways, providing users with innovative financial solutions and services. At its core, SPERO,$$s$ aims to empower individuals by providing tools and platforms that enhance user experience in the cryptocurrency space. This includes enabling more flexible transaction methods, fostering community-driven initiatives, and creating pathways for financial opportunities through decentralised applications (dApps). The underlying vision of SPERO,$$s$ revolves around inclusiveness, aiming to bridge gaps within traditional finance while harnessing the benefits of blockchain technology. Who is the Creator of SPERO,$$s$? The identity of the creator of SPERO,$$s$ remains somewhat obscure, as there are limited publicly available resources providing detailed background information on its founder(s). This lack of transparency can stem from the project's commitment to decentralisation—an ethos that many web3 projects share, prioritising collective contributions over individual recognition. By centring discussions around the community and its collective goals, SPERO,$$s$ embodies the essence of empowerment without singling out specific individuals. As such, understanding the ethos and mission of SPERO remains more important than identifying a singular creator. Who are the Investors of SPERO,$$s$? SPERO,$$s$ is supported by a diverse array of investors ranging from venture capitalists to angel investors dedicated to fostering innovation in the crypto sector. The focus of these investors generally aligns with SPERO's mission—prioritising projects that promise societal technological advancement, financial inclusivity, and decentralised governance. These investor foundations are typically interested in projects that not only offer innovative products but also contribute positively to the blockchain community and its ecosystems. The backing from these investors reinforces SPERO,$$s$ as a noteworthy contender in the rapidly evolving domain of crypto projects. How Does SPERO,$$s$ Work? SPERO,$$s$ employs a multi-faceted framework that distinguishes it from conventional cryptocurrency projects. Here are some of the key features that underline its uniqueness and innovation: Decentralised Governance: SPERO,$$s$ integrates decentralised governance models, empowering users to participate actively in decision-making processes regarding the project’s future. This approach fosters a sense of ownership and accountability among community members. Token Utility: SPERO,$$s$ utilises its own cryptocurrency token, designed to serve various functions within the ecosystem. These tokens enable transactions, rewards, and the facilitation of services offered on the platform, enhancing overall engagement and utility. Layered Architecture: The technical architecture of SPERO,$$s$ supports modularity and scalability, allowing for seamless integration of additional features and applications as the project evolves. 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.

63 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.

738 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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