View Financial HealthSoftBank 配当と自社株買い配当金 基準チェック /36SoftBank配当を支払う会社であり、現在の利回りは3.9%で、収益によって十分にカバーされています。主要情報3.9%配当利回り0.3%バイバック利回り総株主利回り4.2%将来の配当利回り4.6%配当成長4.2%次回配当支払日n/a配当落ち日n/a一株当たり配当金n/a配当性向72%最近の配当と自社株買いの更新お知らせ • Oct 23Softbank Corp. Announces Dividend on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Six Months of Fiscal Year Ending March 31, 2026, Payable on December 5, 2025; Provided Year Dividend Guidance on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Fiscal Year Ending March 31, 2026SoftBank Corp. announced dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the six months of fiscal year ending March 31, 2026 with record date is September 30, 2025. Effective Date is December 5, 2025. Total dividend is JPY 205,270 million on common shares, JPY 1,500 million on Series 1 Bond-Type Class Shares and JPY 3,200 million on Series 2 Bond-Type Class Shares. The company provided year dividend guidance for the fiscal year ending March 31, 2026. The company expected dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the second half of fiscal year ending March 31, 2026.お知らせ • May 11SoftBank Corp. (TSE:9434) announces an Equity Buyback for 56,300,000 shares, representing 1.19% for ¥100,000 million.SoftBank Corp. (TSE:9434) announces an share repurchase program. Under the program the company will repurchase 56,300,000 shares, representing 1.19% of the outstanding shares for ¥100,000 million. The purpose of the program is to enhance shareholder's value and flexibility of the capital policy. The program will run until March 31, 2024. As of March 31, 2023, the company had 4,731,548,827 shares outstanding and 55,596,343 shares in treasury.すべての更新を表示Recent updatesお知らせ • Apr 04SoftBank Corp. to Report Fiscal Year 2026 Results on May 11, 2026SoftBank Corp. announced that they will report fiscal year 2026 results at 3:30 PM, Tokyo Standard Time on May 11, 2026お知らせ • Mar 06Softbank Corp. Unveils Telco Ai Cloud and Aitras PlatformSoftBank Corp. unveiled its strategy for the next-generation of social infrastructure, marking a fundamental evolution in the role of telecommunications carriers. SoftBank announced its transition from a traditional carrier that simply moves data – raw, uninterpreted data packets – to an AI-native infrastructure provider enabling distributed AI workloads across edge and cloud environments. SoftBank's Telco AI Cloud vision evolves the network into a central nervous system: an active computation platform that operates AI models directly within the infrastructure. Through AI-RAN-based MEC (Multi-access Edge Computing), SoftBank can now orchestrate and broker AI workloads across this distributed edge, offloading GPU compute to deliver real-time, reliable inference where it is needed. By embedding this intelligence from the core to the edge, SoftBank is creating a distributed platform that delivers meaning, not just data, enabling immediate decision-making for robotics, autonomous systems, and smart cities. For Physical AI, this means resource-constrained robots can now perform complex, scalable behaviors that would otherwise be difficult to achieve independently; powered not by what they carry but by the network intelligence that surrounds them. A key highlight of the announcement was SoftBank's focus on 'Physical AI': the convergence of AI with the physical world of robotics. Unlike traditional centralized clouds, Telco AI Cloud brings intelligence to the edge, enabling robots to make split-second decisions based on sensor data, performing complex behaviors that their onboard hardware alone could not independently support. Following a collaboration with Yaskawa Electric Corporation focused on deploying robots in real-world environments, SoftBank successfully demonstrated a joint proof-of-concept with Ericsson. The demonstration showcased how AI-RAN networks can optimize connectivity for robots, ensuring the stability required to work safely alongside humans in dynamic environments. In collaboration with Mitsubishi Heavy Industries Ltd., SoftBank is deploying its 'AITRAS' platform in edge data center environments to support industrial use cases. This initiative brings secure AI inference to factory floors, promoting digital transformation in the manufacturing sector and helping to address labor shortages through automation. To foster global innovation, SoftBank has open-sourced the Dynamic Scoring Framework (DSF), a core function of the AITRAS Orchestrator, SoftBank's AI-RAN product. By sharing this technology with the open-source community, SoftBank aims to lower barriers to entry for AI-RAN adoption, inviting developers worldwide to contribute to a more efficient and accessible global infrastructure. SoftBank's Telco AI Cloud vision represents more than a technological upgrade; it is a fundamental shift from transporting data to distributing intelligence. By evolving the network into a ubiquitous AI platform, SoftBank enables the network to not just connect devices but empowers carriers with immediate, context-aware understanding, wherever they operate. Whether alleviating labor shortages through intelligent automation, enhancing industrial safety with edge AI, or enabling robots to perform beyond their own hardware limitations through network-distributed compute, SoftBank is building a central nervous system for society, one where distributed AI infrastructure serves as the catalyst for a more sustainable, productive, and connected future for all.お知らせ • Feb 27Northeastern University, SoftBank Corp., Keysight, and zTouch Networks Demonstrate LTM-Powered Autonomous Agentic AI-RAN at MWC Barcelona 2026Northeastern University's Institute for Intelligent Networked Systems (INSI), SoftBank Corp. (SoftBank), Keysight Technologies, and zTouch Networks are demonstrating Autonomous Agentic AI-RAN (AgentRAN) at Mobile World Congress (MWC) Barcelona 2026. AgentRAN is a first-of-its-kind system that coordinates a hierarchy of AI agents to translate high-level operator intents into real-time, autonomous 5G and 6G network configurations and services. The demonstration is the latest milestone in a collaboration anchored at Northeastern University, where INSI has served as a nexus for industry-ac academic partnerships at the frontier of intelligent wireless networks. Over the past few years, Northeastern has built deep research ties with SoftBank on AI-native architectures, leading to multiple publications, AI-RAN Alliance demonstrations, and innovation in next-generation wireless. INSI collaborate with Keysight on AI-RAN testing and spun off zTouch Networks to commercialize technology on open, GPU-accelerated RAN infrastructure. This demo brings those threads together for the first time around a shared vision: truly autonomous, AI-driven radio access networks. At the heart of the demo is AgentRAN, developed at Northeastern's Open6G AI-RAN Alliance Lab. Operators express goals in natural language - such as "maximize throughput while prioritizing emergency traffic" - and the AgentRAN Manager decomposes these intents into actions for specialized agents operating across the RAN stack. The agents are powered by the SoftBank's Large Telecom Model (LTM), a purpose-built foundation model trained on telecom-specific KPIs, configurations, and domain data--f further optimized with high-fidelity training data generated using Keysight's RF digital twin channel emulation solutions with real world accurate 3D ray tracing capabilities (RaySIM, PROPSIM) for more accurate decisions than generic cloud models can deliver. The Northeastern Open6G AI-Ran lab, using Keysight's PROPSIM, demonstrates multiple agentic scenarios, deployed on an end-to-end programmable private 5G AI-RAN infrastructure, managed and orchestrated by zTouch Networks' zTouch.OS. Using Keysight's AI-RAN performance scoring solution, the system shows clear performance gains linked to the use of SoftBank's LTM, high fidelity training datasets generated by Keysight RF digital twin solutions, and zTouch Networks' zTouch".OS.お知らせ • Jan 21Softbank Corp. Announces "Infrinia AI Cloud OS," a Software Stack for AI Data CentersSoftBank Corp. announced that its Infrinia Team, which works on the development of next-generation AI infrastructure architecture and systems, has developed "Infrinia AI Cloud OS," a software stack designed for AI data centers. In addition, the software stack is expected to reduce total cost of ownership (TCO) as well as operational burden compared with bespoke solutions or in-house development. This will enable the rapid delivery of GPU cloud services that efficiently and flexibly support the full AI lifecycle--from AI model training to inference. SoftBank plans to deploy 'Infrinia AI Cloud OS' initially within its own GPU cloud services. Furthermore, the Infrinia Team aims to expand deployment to overseas data centers and cloud environments with a view to global adoption. As a result, user needs and usage patterns for AI computing are becoming increasingly diverse and sophisticated, and requirements including the following have emerging: Access to infrastructure that is fully managed by GPU cloud service providers, abstracted GPU bare-metal servers; Cost-optimized, highly abstracted inference services without concerning with GPU management; Advanced operations in which AI models are trained and optimized on centralized servers and deployed for inference at the edge. Building and operating GPU cloud services that meet these requirements requires highly specialized expertise and involves complex operational tasks, placing a significant burden on GPU cloud service providers. To address these challenges, the Infrinia Team developed "Infrinia AI cloud OS," a software stack that maximizes GPU performance while enabling the easy and rapid deployment and operation of advanced GPU cloud services. Key Features of "Infrinia AI CloudOS" Kubernetes as a Service: Reduces the operational burden of managing the physical infrastructure and the Kubernetes software layer by automating the entire stack (from BIOS and RAID settings to the OS, GPU Drivers, networking, Kubernetes Controllers and Storage) on GPU Platforms such as NVIDIA GB200 NVL72; Software-defined dynamic, on-the-fly physical connectivity (NVIDIA NVLink) and memory (Inter-Node Memory Exchange) reconfiguration, as the customers create, update and delete their clusters to suit their AI workload needs; Automatic node allocation based on GPU proximity and NVIDIA NVLink domain to reduce latency and maximize GPU-to-GPU bandwidth for highly distributed jobs; Enables users to deploy inference services simply by selecting Large Language Models, without working with Kubernetes or the underlying infrastructure; OpenAI-compatible APIs, enabling drop-in integration with existing AI applications; Seamless scaling across multiple nodes in core and edge platforms such as NVIDIA GB200 NV L72 and other platforms; Secure Multi-tenancy and High Operability; Tenant isolation through encrypted cluster communications and separation; Automation of operational maintenance, including system monitoring and failover; API environment for connecting to the AI data center's portal, customer management systems, and billing systems. These key features allow AI data center operators with customer management systems, as well as enterprises offering GPU cloud services, to add advanced capabilities that enable efficient AI model training and inference while flexibly utilizing GPU resources, to their own GPU service offerings.お知らせ • Jan 07SoftBank Corp. to Report Q3, 2026 Results on Feb 09, 2026SoftBank Corp. announced that they will report Q3, 2026 results at 3:30 PM, Tokyo Standard Time on Feb 09, 2026お知らせ • Nov 26LevelBlue, LLC completed the acquisition of Cybereason Inc.LevelBlue, LLC signed a definitive agreement to acquire Cybereason Inc. on October 14, 2025. As part of the transaction, SoftBank Corp., SoftBank Vision Fund 2, and Liberty Strategic Capital, known for investing in disruptive and innovative technology, will become investors in LevelBlue, LLC. Steven T. Mnuchin, former U.S. Treasury Secretary and Managing Partner of Liberty 77 Capital L.P., will join LevelBlue’s Board of Directors. The transaction is subject to customary closing conditions and regulatory approvals. Banco Santander, S.A. acted as financial advisor for LevelBlue, LLC. Adam Kool, Steven Cantor, Maureen Dixon, John Kaercher, Jeremy Mandell, Corey Fox, and Jacob Klapholz of Kirkland & Ellis LLP acted as legal advisor for LevelBlue, LLC. J.P. Morgan Securities LLC acted as financial advisor for Cybereason Inc. Goodwin Procter LLP acted as legal advisor for Cybereason Inc. Michael Vogel of Paul, Weiss, Rifkind, Wharton & Garrison LLP acted as legal advisor for Liberty 77 Capital L.P. LevelBlue, LLC completed the acquisition of Cybereason Inc. on November 25, 2025. Steven T. Mnuchin has joined LevelBlue’s Board of Directors. As part of the completed transaction, SoftBank Corp., SoftBank Vision Fund 2, and Liberty Strategic Capital have become investors in LevelBlue.お知らせ • Oct 23Softbank Corp. Announces Dividend on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Six Months of Fiscal Year Ending March 31, 2026, Payable on December 5, 2025; Provided Year Dividend Guidance on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Fiscal Year Ending March 31, 2026SoftBank Corp. announced dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the six months of fiscal year ending March 31, 2026 with record date is September 30, 2025. Effective Date is December 5, 2025. Total dividend is JPY 205,270 million on common shares, JPY 1,500 million on Series 1 Bond-Type Class Shares and JPY 3,200 million on Series 2 Bond-Type Class Shares. The company provided year dividend guidance for the fiscal year ending March 31, 2026. The company expected dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the second half of fiscal year ending March 31, 2026.お知らせ • Oct 03SoftBank Corp. to Report Q2, 2026 Results on Nov 05, 2025SoftBank Corp. announced that they will report Q2, 2026 results at 3:30 PM, Tokyo Standard Time on Nov 05, 2025お知らせ • Jul 02SoftBank Corp. to Report Q1, 2026 Results on Aug 05, 2025SoftBank Corp. announced that they will report Q1, 2026 results on Aug 05, 2025お知らせ • May 08SoftBank Corp., Annual General Meeting, Jun 26, 2025SoftBank Corp., Annual General Meeting, Jun 26, 2025.お知らせ • Apr 03SoftBank Corp. to Report Fiscal Year 2025 Results on May 08, 2025SoftBank Corp. announced that they will report fiscal year 2025 results at 3:30 PM, Tokyo Standard Time on May 08, 2025お知らせ • Mar 26SoftBank Corp. (TSE:9434) acquired an unknown minority stake in SB Energy DevCo (US), LLC.SoftBank Corp. (TSE:9434) acquired an unknown minority stake in SB Energy DevCo (US), LLC on June 30, 2024. Chris McKinnon and Ken Siegel of Morrison & Foerster LLP acted as legal advisors for SoftBank Corp. SoftBank Corp. (TSE:9434) completed the acquisition of an unknown minority stake in SB Energy DevCo (US), LLC on June 30, 2024.お知らせ • Mar 20SoftBank Corp. Develops Foundational Large Telecom ModelSoftBank Corp. announced that it has developed a new Large Telecom Model (LTM), a generative AI foundation for the telecom industry. The LTM is trained on diverse datasets--ranging from SoftBank's huge network data to the design, management, and operational know-how the company has accumulated over many years. SoftBank has also developed specialized AI models by fine-tuning the LTM, which is specifically designed to optimize base station configurations that enable advanced cellular network operations. The fine-tuned models were tasked with predicting configurations for actual base stations that had been excluded from the training phase, and their predictions were later verified by in-house experts to have over 90% accuracy. Compared to manual or partially automated workflows, the LTM-led approach reduces the time to make these changes from days to minutes, and with similar accuracy, indicating the potential for huge operational time and cost savings, in addition to reducing human error. These results demonstrate that by fine-tuning theLTM for specific use cases, it will become easier to develop dedicated AI models tailored to various operational scenarios in cellular networks. The LTM also functions as a foundation for the "AI for RAN" initiative, which aims to enhance RAN (Radio Access Network) performance through AI. In the future, the LTM is expected to serve as a blueprint for network design and support the development of network optimization AI agents. SoftBank RIAT has proposed two approaches for utilizing AI in mobile networks, "Human AI" and "Machine AI," and has now successfully realized its vision of "Human AI". SoftBank aims to integrate various AI models developed based on the LTM with the orchestrator of "AITRAS"3, an AI-RAN integrated solution currently under development by SoftBank. Main features of LTM: The LTM combines advanced inference capabilities leveraging large-scale data to solve network operational issues with flexible responsiveness enabled by natural language processing. It reflects SoftBank's extensive network and data, along with in-depth network information annotated by in-house experts skilled in network design, management, and operation. Realizing use cases specific AI models through fine-tuning: By fine-tuning models based on the LTM, it is possible to develop AI models specialized for various use cases in mobile network operations. As the first implementation, SoftBank developed models specialized in generating optimal base station configurations. Its effectiveness has been verified in scenarios including generating optimal configurations for newly deployed base stations and modifying existing base station settings to accommodate sudden traffic increases expected during events. New base station deployment: Focusing on Tokyo, a high-density urban area, the model generates optimal configurations for new base station deployments. The model receives requests to deploy a new base station in a specific area, along with additional information such as existing base station configurations and network performance, and outputs a list of configurations recommended for the new base station. Existing base station reconfiguration: Assuming a special event is taking place, the model generates configuration changes for existing base stations in the surrounding area. As SoftBank moves forward towards the deployment of the LTM, SoftBank will continue collaborating with NVIDIA on NIM Microservices Optimization for Inferencing and Aerial Omniverse Digital Twin (AODT) for simulating and validating the LTM configuration changes prior to taking actions. SoftBank will explore utilizing the LTM in its own operations, aiming to enhance mobile network efficiency, create new services, and deliver higher-quality network experiences. SoftBank will also continue to advance its research and development efforts and strengthen collaborations with partners both in Japan and abroad, thereby contributing to the further evolution of next-generation networks. In particular, the SoftBank RIAT Silicon Valley Office, which led the development of LTM in collaboration with the Japan team, will continue to grow and develop its portfolio in the USA.お知らせ • Feb 12PayPay Bank Corporation agreed to acquire an additional 31% stake in PayPay Securities Co., Ltd from SoftBank Corp. (TSE:9434) and Ly Corporation.PayPay Bank Corporation agreed to acquire an additional 31% stake in PayPay Securities Co., Ltd from SoftBank Corp. (TSE:9434) and Ly Corporation on February 10, 2025. Upon completion, PayPay Bank Corporation will own 66% stake in PayPay Securities Co., Ltd.お知らせ • Jan 08SoftBank Corp. to Report Q3, 2025 Results on Feb 10, 2025SoftBank Corp. announced that they will report Q3, 2025 results on Feb 10, 2025お知らせ • Nov 14SoftBank Corp. Develops 5G L1 Software, Achieving Carrier-grade High Performance and Quality vRAN on NVIDIA Grace Hopper PlatformSoftBank Corp. announced it developed 5G L1 software based on the NVIDIA AI Aerial platform, delivering the high stability and high performance essential for a carrier-grade RAN through parallel signal processing and the optimization of task initiation timing. With this newly developed L1 software, carrier-grade stability has been achieved. In addition to realizing high stability, SoftBank will develop L1 software that can achieve maximized RAN capacity and reduced power consumption. SoftBank constructed the world’s first high-quality 5G vRAN (virtual Radio Access Network) outdoor testing environment, utilizing its newly developed L1 software running on the NVIDIA GH200 Grace Hopper Superchip platform. NVIDIA Grace Hopper Superchip architecture brings together the accelerated performance of the NVIDIA Hopper architecture with the versatility of the Arm® Neoverse™ V2 - based NVIDIA Grace CPU in a single superchip. SoftBank built the world’s first outdoor testing environment that enables the baseband processing of 20 5G cells with a bandwidth of 100 MHz on a single server featuring the NVIDIA GH200 Grace Hopper Superchip in Fujisawa City, Kanagawa Prefecture. The 4.9 GHz frequency band was used for this outdoor test and a maximum communication capacity of approximately 1.3 Gbps per cell through a maximum of 4-layer MIMO (Multi-Input Multi-Output) was achieved. The high-speed processing capabilities of NVIDIA’s accelerated computing platform are highly compatible with high-frequency bands that can be allocated to a wide frequency bandwidth per cell, and these capabilities are expected to be applied to future 6G applications such as centimeter waves. Furthermore, since such high-frequency cells are expected to be deployed in high-traffic urban areas, this AI-RAN outdoor test simulates an urban environment, creating a dense configuration with a high-interference area and a mobility area for test drives. For mobile phones, it is necessary to have stability and high connectivity that will minimize the time the cell stops functioning due to failures or malfunctions during long-term operations, as well as network outages due to deterioration of radio wave quality. To achieve these at a high level, it is required to make verifications not only in a controlled radio environment like a laboratory, but also in an irregular radio environment that is situated outdoors. In this test, SoftBank is conducting various trials using more than 100 terminals to confirm the RAN’s stability and high connectivity, which are necessary for a carrier-grade service. Going forward, SoftBank plans to evaluate spatial multiplexing technologies, such as Massive MIMO, and AI for RAN, a technology that enables the enhancement of RAN performance with AI.お知らせ • Nov 13+ 1 more updateSoftBank Corp. Develops Orchestrator to Operate AI and vRAN on the Same Virtualized InfrastructureSoftBank Corp. announced it developed the orchestrator that enables AI applications and vRAN (virtualized Radio Access Network) applications to operate on the same virtualized infrastructure, a key concept of AI-RAN. This advancement enables the deployment of high-capacity, high-performance, and high-quality vRAN at a carrier-grade level on virtualized infrastructure running on GPU (Graphics Processing Unit) computing, including the NVIDIA GH200 Grace Hopper Superchip platform. Additionally, the orchestrator enables the integration and provision of various AI applications, such asgenerative AI, on the same platform. There are challenges in operating AI and vRAN on the same infrastructure, as service level agreements (SLAs) and server configurations differ depending on the type of workload. To address these challenges, SoftBank developed the orchestrator that enables control over infrastructure settings to meet the specific kernel and requirements of each workload. This solution is expected to deliver a highly operational and cost-effective platform. In addition to AI applications developed by SoftBank, the serverless API powered by NVIDIA AI Enterprise is also integrated with the orchestrator, enabling users to run their own AI applications on the AI-RAN virtualized infrastructure. AI and vRAN applications have distinct characteristics, requiring simultaneous optimization. For example, vRAN must control radio functions, which demands ultra-low-latency processing, whereas AI applications require efficient memory management for large data volumes and the ability to handle multiple workloads with optimal placement. To operate such diverse applications on a unified computing platform, SoftBank developed the orchestrator by building a virtualized infrastructure using Red Hat OpenShift. This orchestrator efficiently manages resources, allowing AI and vRAN applications, as well as the orchestrator itself, to run seamlessly on Red Hat OpenShift. As a result, the platform can optimize performance based on real-time resource availability within the virtualized infrastructure. Key Features of the Orchestrator: Optimal matching algorithm that considers deployment requests from users, demand forecasts, and resource availability on the supply side; Dynamic infrastructure resource adjustments based on the above algorithm; Centralized management of multi-cluster environments to support a distributed AI data center concept; Comprehensive management of configuration and resource status for all clusters and servers distributed across Japan.お知らせ • Oct 03SoftBank Corp. to Report Q2, 2025 Results on Nov 08, 2024SoftBank Corp. announced that they will report Q2, 2025 results on Nov 08, 2024お知らせ • Jul 04SoftBank Corp. to Report Q1, 2025 Results on Aug 06, 2024SoftBank Corp. announced that they will report Q1, 2025 results on Aug 06, 2024お知らせ • Jun 13SoftBank Corp. (TSE:9434) completed the acquisition of 35.3% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥21.2 billion.SoftBank Corp. (TSE:9434) made an offer to acquire remaining 47.19% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥28.3 billion on April 23, 2024. Under the terms SoftBank made ¥2,950 per share for the acquisition of 9.590933 million shares and ¥1 for 424 200 shares under stock acquisition rights. If SoftBank Corp. is able to tender 90% shares then SoftBank will cash-out the remaining shares. The minimum limit for shares to be tendered is set at 2,815,600 shares(13.85%). The tender offer period is April 26, 2024 to June 11, 2024. Nishimura & Asahi and Blakemore & Mitsuki acted as legal advisor and Daiwa Securities Co. Ltd. and Nomura Securities Co., Ltd. acted as financial advisor to SB Technology. Plutus Consulting Co., Ltd. acted as fairness opinion provider and financial advisor and Kensei Law Offices acted as legal advisor to special committee of SB Technology. SoftBank Corp. (TSE:9434) completed the acquisition of 35.3% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥21.2 billion on April 23, 2024. SoftBank intends to carry out a set of procedures of the “Squeeze-Out Process” for making the SoftBank the only shareholder of SB Technology.お知らせ • May 10SoftBank Corp. Reportedly Back At Deal Counter with Icertis Deal TalksSoftBank Corp. (TSE:9434) is looking to return to the deal counter in India after largely focusing on exits from listed bets last year. The Tokyo-based investment firm has begun early-stage talks to double down on existing software portfolio firm Icertis Solutions Private Limited, which is stitching up a new funding round of about $150 million (about INR 12,520 million), in a secondary share sale, said people familiar with the development. The talks would progress depending on valuation to a large extent, they said. The new funding round may see other existing backers also invest more in Icertis, they said, as some early shareholders are looking to make an exit from the 15-year-old firm. Icertis was last valued at $5 billion. SoftBank’s Vision Fund has also finalised plans for investing in ecommerce firm Meesho as part of a broader funding round. With several unicorns under its portfolio, the Japanese investor is actively reviewing potential new firms as well after a lull of more than a year – when SoftBank and Tiger Global didn’t make any deals. “The talks are in early stages and the key to the deal would be the valuation and the price discovery is yet to be finalised,” said one of the persons, who did not wish to be identified. A spokesperson for Icertis said it remains well capitalised and that it is common for new investors to seek shares in businesses like Icertis. "Icertis is not directly involved in any such secondary transactions and remains focused on empowering our customers to realise the full potential of their business relationships through contract intelligence," the spokesperson added. A spokesperson for SoftBank India declined to comment on the matter.お知らせ • Apr 28+ 1 more updateSoftBank Corp., Annual General Meeting, Jun 20, 2024SoftBank Corp., Annual General Meeting, Jun 20, 2024, at 10:00 Tokyo Standard Time.お知らせ • Apr 04SoftBank Corp. to Report Fiscal Year 2024 Results on May 09, 2024SoftBank Corp. announced that they will report fiscal year 2024 results on May 09, 2024お知らせ • Jan 13SoftBank Corp. to Report Q3, 2024 Results on Feb 07, 2024SoftBank Corp. announced that they will report Q3, 2024 results on Feb 07, 2024お知らせ • Oct 05SoftBank Corp. to Report Q2, 2024 Results on Nov 08, 2023SoftBank Corp. announced that they will report Q2, 2024 results on Nov 08, 2023お知らせ • Jun 20SoftBank Corp. Announces Executive ChangesSoftBank Corp. announced that Kimihiko Kaneko as Member of the Board, Position at the parent companies, etc: General Manager, Technological Planning & Management Division, Technology Unit, SoftBank Corp. Takashi Naito as Audit & Supervisory Board Member. Position at the parent companies, etc: Vice President and General Manager, Finance & Accounting Division, Finance Unit, SoftBank Corp., Audit & Supervisory Board Member, SB Players Corp., Audit & Supervisory Board Member, A Holdings Corporation. As of June 19, 2023, Mr. Kunihiro Fujinaga (Senior Vice President, Deputy Head of Enterprise Business Unit, SoftBank Corp.) was appointed as a director of SoftBank Corp. with the aim of enhancing mutual synergies with the parent company and collaboration in the corporate business field.お知らせ • May 11SoftBank Corp. (TSE:9434) announces an Equity Buyback for 56,300,000 shares, representing 1.19% for ¥100,000 million.SoftBank Corp. (TSE:9434) announces an share repurchase program. Under the program the company will repurchase 56,300,000 shares, representing 1.19% of the outstanding shares for ¥100,000 million. The purpose of the program is to enhance shareholder's value and flexibility of the capital policy. The program will run until March 31, 2024. As of March 31, 2023, the company had 4,731,548,827 shares outstanding and 55,596,343 shares in treasury.お知らせ • Jan 07SoftBank Corp. to Report Q3, 2023 Results on Feb 03, 2023SoftBank Corp. announced that they will report Q3, 2023 results on Feb 03, 2023決済の安定と成長配当データの取得安定した配当: 配当金の支払いは安定していますが、 SOBK.Yが配当金を支払っている期間は 10 年未満です。増加する配当: SOBK.Yの配当金は増加していますが、同社は7年間しか配当金を支払っていません。配当利回り対市場SoftBank 配当利回り対市場SOBK.Y 配当利回りは市場と比べてどうか？セグメント配当利回り会社 (SOBK.Y)3.9%市場下位25% (US)1.4%市場トップ25% (US)4.2%業界平均 (Wireless Telecom)3.4%アナリスト予想 (SOBK.Y) (最長3年)4.6%注目すべき配当: SOBK.Yの配当金 ( 3.9% ) はUS市場の配当金支払者の下位 25% ( 1.39% ) よりも高くなっています。高配当: SOBK.Yの配当金 ( 3.9% ) はUS市場の配当金支払者の上位 25% ( 4.21% ) と比較すると低いです。株主への利益配当収益カバレッジ: SOBK.Yの配当金は、合理的な 配当性向 ( 72.4% ) により、利益によって賄われています。株主配当金キャッシュフローカバレッジ: 現在の現金配当性向（ 76.4% ）では、 SOBK.Yの配当金はキャッシュフローによって賄われています。高配当企業の発掘7D1Y7D1Y7D1YUS 市場の強力な配当支払い企業。View Management企業分析と財務データの現状データ最終更新日（UTC時間）企業分析2026/05/06 05:38終値2026/05/06 00:00収益2025/12/31年間収益2025/03/31データソース企業分析に使用したデータはS&P Global Market Intelligence LLC のものです。本レポートを作成するための分析モデルでは、以下のデータを使用しています。データは正規化されているため、ソースが利用可能になるまでに時間がかかる場合があります。パッケージデータタイムフレーム米国ソース例会社財務10年損益計算書キャッシュ・フロー計算書貸借対照表SECフォーム10-KSECフォーム10-Qアナリストのコンセンサス予想+プラス3年予想財務アナリストの目標株価アナリストリサーチレポートBlue Matrix市場価格30年株価配当、分割、措置ICEマーケットデータSECフォームS-1所有権10年トップ株主インサイダー取引SECフォーム4SECフォーム13Dマネジメント10年リーダーシップ・チーム取締役会SECフォーム10-KSECフォームDEF 14A主な進展10年会社からのお知らせSECフォーム8-K* 米国証券を対象とした例であり、非米国証券については、同等の規制書式および情報源を使用。特に断りのない限り、すべての財務データは1年ごとの期間に基づいていますが、四半期ごとに更新されます。これは、TTM（Trailing Twelve Month）またはLTM（Last Twelve Month）データとして知られています。詳細はこちら。分析モデルとスノーフレーク本レポートを生成するために使用した分析モデルの詳細は当社のGithubページでご覧いただけます。また、レポートの使用方法に関するガイドやYoutubeのチュートリアルも掲載しています。シンプリー・ウォールストリート分析モデルを設計・構築した世界トップクラスのチームについてご紹介します。業界およびセクターの指標私たちの業界とセクションの指標は、Simply Wall Stによって6時間ごとに計算されます。アナリスト筋SoftBank Corp. 14 これらのアナリストのうち、弊社レポートのインプットとして使用した売上高または利益の予想を提出したのは、 。アナリストの投稿は一日中更新されます。21 アナリスト機関Kirk BoodryAstris Advisory Japan, K.K.Yuki KanekoBofA Global ResearchKeiichi YoneshimaCitigroup Inc18 その他のアナリストを表示
お知らせ • Oct 23Softbank Corp. Announces Dividend on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Six Months of Fiscal Year Ending March 31, 2026, Payable on December 5, 2025; Provided Year Dividend Guidance on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Fiscal Year Ending March 31, 2026SoftBank Corp. announced dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the six months of fiscal year ending March 31, 2026 with record date is September 30, 2025. Effective Date is December 5, 2025. Total dividend is JPY 205,270 million on common shares, JPY 1,500 million on Series 1 Bond-Type Class Shares and JPY 3,200 million on Series 2 Bond-Type Class Shares. The company provided year dividend guidance for the fiscal year ending March 31, 2026. The company expected dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the second half of fiscal year ending March 31, 2026.
お知らせ • May 11SoftBank Corp. (TSE:9434) announces an Equity Buyback for 56,300,000 shares, representing 1.19% for ¥100,000 million.SoftBank Corp. (TSE:9434) announces an share repurchase program. Under the program the company will repurchase 56,300,000 shares, representing 1.19% of the outstanding shares for ¥100,000 million. The purpose of the program is to enhance shareholder's value and flexibility of the capital policy. The program will run until March 31, 2024. As of March 31, 2023, the company had 4,731,548,827 shares outstanding and 55,596,343 shares in treasury.
お知らせ • Apr 04SoftBank Corp. to Report Fiscal Year 2026 Results on May 11, 2026SoftBank Corp. announced that they will report fiscal year 2026 results at 3:30 PM, Tokyo Standard Time on May 11, 2026
お知らせ • Mar 06Softbank Corp. Unveils Telco Ai Cloud and Aitras PlatformSoftBank Corp. unveiled its strategy for the next-generation of social infrastructure, marking a fundamental evolution in the role of telecommunications carriers. SoftBank announced its transition from a traditional carrier that simply moves data – raw, uninterpreted data packets – to an AI-native infrastructure provider enabling distributed AI workloads across edge and cloud environments. SoftBank's Telco AI Cloud vision evolves the network into a central nervous system: an active computation platform that operates AI models directly within the infrastructure. Through AI-RAN-based MEC (Multi-access Edge Computing), SoftBank can now orchestrate and broker AI workloads across this distributed edge, offloading GPU compute to deliver real-time, reliable inference where it is needed. By embedding this intelligence from the core to the edge, SoftBank is creating a distributed platform that delivers meaning, not just data, enabling immediate decision-making for robotics, autonomous systems, and smart cities. For Physical AI, this means resource-constrained robots can now perform complex, scalable behaviors that would otherwise be difficult to achieve independently; powered not by what they carry but by the network intelligence that surrounds them. A key highlight of the announcement was SoftBank's focus on 'Physical AI': the convergence of AI with the physical world of robotics. Unlike traditional centralized clouds, Telco AI Cloud brings intelligence to the edge, enabling robots to make split-second decisions based on sensor data, performing complex behaviors that their onboard hardware alone could not independently support. Following a collaboration with Yaskawa Electric Corporation focused on deploying robots in real-world environments, SoftBank successfully demonstrated a joint proof-of-concept with Ericsson. The demonstration showcased how AI-RAN networks can optimize connectivity for robots, ensuring the stability required to work safely alongside humans in dynamic environments. In collaboration with Mitsubishi Heavy Industries Ltd., SoftBank is deploying its 'AITRAS' platform in edge data center environments to support industrial use cases. This initiative brings secure AI inference to factory floors, promoting digital transformation in the manufacturing sector and helping to address labor shortages through automation. To foster global innovation, SoftBank has open-sourced the Dynamic Scoring Framework (DSF), a core function of the AITRAS Orchestrator, SoftBank's AI-RAN product. By sharing this technology with the open-source community, SoftBank aims to lower barriers to entry for AI-RAN adoption, inviting developers worldwide to contribute to a more efficient and accessible global infrastructure. SoftBank's Telco AI Cloud vision represents more than a technological upgrade; it is a fundamental shift from transporting data to distributing intelligence. By evolving the network into a ubiquitous AI platform, SoftBank enables the network to not just connect devices but empowers carriers with immediate, context-aware understanding, wherever they operate. Whether alleviating labor shortages through intelligent automation, enhancing industrial safety with edge AI, or enabling robots to perform beyond their own hardware limitations through network-distributed compute, SoftBank is building a central nervous system for society, one where distributed AI infrastructure serves as the catalyst for a more sustainable, productive, and connected future for all.
お知らせ • Feb 27Northeastern University, SoftBank Corp., Keysight, and zTouch Networks Demonstrate LTM-Powered Autonomous Agentic AI-RAN at MWC Barcelona 2026Northeastern University's Institute for Intelligent Networked Systems (INSI), SoftBank Corp. (SoftBank), Keysight Technologies, and zTouch Networks are demonstrating Autonomous Agentic AI-RAN (AgentRAN) at Mobile World Congress (MWC) Barcelona 2026. AgentRAN is a first-of-its-kind system that coordinates a hierarchy of AI agents to translate high-level operator intents into real-time, autonomous 5G and 6G network configurations and services. The demonstration is the latest milestone in a collaboration anchored at Northeastern University, where INSI has served as a nexus for industry-ac academic partnerships at the frontier of intelligent wireless networks. Over the past few years, Northeastern has built deep research ties with SoftBank on AI-native architectures, leading to multiple publications, AI-RAN Alliance demonstrations, and innovation in next-generation wireless. INSI collaborate with Keysight on AI-RAN testing and spun off zTouch Networks to commercialize technology on open, GPU-accelerated RAN infrastructure. This demo brings those threads together for the first time around a shared vision: truly autonomous, AI-driven radio access networks. At the heart of the demo is AgentRAN, developed at Northeastern's Open6G AI-RAN Alliance Lab. Operators express goals in natural language - such as "maximize throughput while prioritizing emergency traffic" - and the AgentRAN Manager decomposes these intents into actions for specialized agents operating across the RAN stack. The agents are powered by the SoftBank's Large Telecom Model (LTM), a purpose-built foundation model trained on telecom-specific KPIs, configurations, and domain data--f further optimized with high-fidelity training data generated using Keysight's RF digital twin channel emulation solutions with real world accurate 3D ray tracing capabilities (RaySIM, PROPSIM) for more accurate decisions than generic cloud models can deliver. The Northeastern Open6G AI-Ran lab, using Keysight's PROPSIM, demonstrates multiple agentic scenarios, deployed on an end-to-end programmable private 5G AI-RAN infrastructure, managed and orchestrated by zTouch Networks' zTouch.OS. Using Keysight's AI-RAN performance scoring solution, the system shows clear performance gains linked to the use of SoftBank's LTM, high fidelity training datasets generated by Keysight RF digital twin solutions, and zTouch Networks' zTouch".OS.
お知らせ • Jan 21Softbank Corp. Announces "Infrinia AI Cloud OS," a Software Stack for AI Data CentersSoftBank Corp. announced that its Infrinia Team, which works on the development of next-generation AI infrastructure architecture and systems, has developed "Infrinia AI Cloud OS," a software stack designed for AI data centers. In addition, the software stack is expected to reduce total cost of ownership (TCO) as well as operational burden compared with bespoke solutions or in-house development. This will enable the rapid delivery of GPU cloud services that efficiently and flexibly support the full AI lifecycle--from AI model training to inference. SoftBank plans to deploy 'Infrinia AI Cloud OS' initially within its own GPU cloud services. Furthermore, the Infrinia Team aims to expand deployment to overseas data centers and cloud environments with a view to global adoption. As a result, user needs and usage patterns for AI computing are becoming increasingly diverse and sophisticated, and requirements including the following have emerging: Access to infrastructure that is fully managed by GPU cloud service providers, abstracted GPU bare-metal servers; Cost-optimized, highly abstracted inference services without concerning with GPU management; Advanced operations in which AI models are trained and optimized on centralized servers and deployed for inference at the edge. Building and operating GPU cloud services that meet these requirements requires highly specialized expertise and involves complex operational tasks, placing a significant burden on GPU cloud service providers. To address these challenges, the Infrinia Team developed "Infrinia AI cloud OS," a software stack that maximizes GPU performance while enabling the easy and rapid deployment and operation of advanced GPU cloud services. Key Features of "Infrinia AI CloudOS" Kubernetes as a Service: Reduces the operational burden of managing the physical infrastructure and the Kubernetes software layer by automating the entire stack (from BIOS and RAID settings to the OS, GPU Drivers, networking, Kubernetes Controllers and Storage) on GPU Platforms such as NVIDIA GB200 NVL72; Software-defined dynamic, on-the-fly physical connectivity (NVIDIA NVLink) and memory (Inter-Node Memory Exchange) reconfiguration, as the customers create, update and delete their clusters to suit their AI workload needs; Automatic node allocation based on GPU proximity and NVIDIA NVLink domain to reduce latency and maximize GPU-to-GPU bandwidth for highly distributed jobs; Enables users to deploy inference services simply by selecting Large Language Models, without working with Kubernetes or the underlying infrastructure; OpenAI-compatible APIs, enabling drop-in integration with existing AI applications; Seamless scaling across multiple nodes in core and edge platforms such as NVIDIA GB200 NV L72 and other platforms; Secure Multi-tenancy and High Operability; Tenant isolation through encrypted cluster communications and separation; Automation of operational maintenance, including system monitoring and failover; API environment for connecting to the AI data center's portal, customer management systems, and billing systems. These key features allow AI data center operators with customer management systems, as well as enterprises offering GPU cloud services, to add advanced capabilities that enable efficient AI model training and inference while flexibly utilizing GPU resources, to their own GPU service offerings.
お知らせ • Jan 07SoftBank Corp. to Report Q3, 2026 Results on Feb 09, 2026SoftBank Corp. announced that they will report Q3, 2026 results at 3:30 PM, Tokyo Standard Time on Feb 09, 2026
お知らせ • Nov 26LevelBlue, LLC completed the acquisition of Cybereason Inc.LevelBlue, LLC signed a definitive agreement to acquire Cybereason Inc. on October 14, 2025. As part of the transaction, SoftBank Corp., SoftBank Vision Fund 2, and Liberty Strategic Capital, known for investing in disruptive and innovative technology, will become investors in LevelBlue, LLC. Steven T. Mnuchin, former U.S. Treasury Secretary and Managing Partner of Liberty 77 Capital L.P., will join LevelBlue’s Board of Directors. The transaction is subject to customary closing conditions and regulatory approvals. Banco Santander, S.A. acted as financial advisor for LevelBlue, LLC. Adam Kool, Steven Cantor, Maureen Dixon, John Kaercher, Jeremy Mandell, Corey Fox, and Jacob Klapholz of Kirkland & Ellis LLP acted as legal advisor for LevelBlue, LLC. J.P. Morgan Securities LLC acted as financial advisor for Cybereason Inc. Goodwin Procter LLP acted as legal advisor for Cybereason Inc. Michael Vogel of Paul, Weiss, Rifkind, Wharton & Garrison LLP acted as legal advisor for Liberty 77 Capital L.P. LevelBlue, LLC completed the acquisition of Cybereason Inc. on November 25, 2025. Steven T. Mnuchin has joined LevelBlue’s Board of Directors. As part of the completed transaction, SoftBank Corp., SoftBank Vision Fund 2, and Liberty Strategic Capital have become investors in LevelBlue.
お知らせ • Oct 23Softbank Corp. Announces Dividend on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Six Months of Fiscal Year Ending March 31, 2026, Payable on December 5, 2025; Provided Year Dividend Guidance on Common Stock, Series 1 Bond-Type Class Shares and Series 2 Bond-Type Class Shares for the Fiscal Year Ending March 31, 2026SoftBank Corp. announced dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the six months of fiscal year ending March 31, 2026 with record date is September 30, 2025. Effective Date is December 5, 2025. Total dividend is JPY 205,270 million on common shares, JPY 1,500 million on Series 1 Bond-Type Class Shares and JPY 3,200 million on Series 2 Bond-Type Class Shares. The company provided year dividend guidance for the fiscal year ending March 31, 2026. The company expected dividend of JPY 4.30 per share on common stock, JPY 50 per share on series 1 Bond-Type Class Shares and JPY 128 per share on Series 2 Bond-Type Class Shares for the second half of fiscal year ending March 31, 2026.
お知らせ • Oct 03SoftBank Corp. to Report Q2, 2026 Results on Nov 05, 2025SoftBank Corp. announced that they will report Q2, 2026 results at 3:30 PM, Tokyo Standard Time on Nov 05, 2025
お知らせ • Jul 02SoftBank Corp. to Report Q1, 2026 Results on Aug 05, 2025SoftBank Corp. announced that they will report Q1, 2026 results on Aug 05, 2025
お知らせ • May 08SoftBank Corp., Annual General Meeting, Jun 26, 2025SoftBank Corp., Annual General Meeting, Jun 26, 2025.
お知らせ • Apr 03SoftBank Corp. to Report Fiscal Year 2025 Results on May 08, 2025SoftBank Corp. announced that they will report fiscal year 2025 results at 3:30 PM, Tokyo Standard Time on May 08, 2025
お知らせ • Mar 26SoftBank Corp. (TSE:9434) acquired an unknown minority stake in SB Energy DevCo (US), LLC.SoftBank Corp. (TSE:9434) acquired an unknown minority stake in SB Energy DevCo (US), LLC on June 30, 2024. Chris McKinnon and Ken Siegel of Morrison & Foerster LLP acted as legal advisors for SoftBank Corp. SoftBank Corp. (TSE:9434) completed the acquisition of an unknown minority stake in SB Energy DevCo (US), LLC on June 30, 2024.
お知らせ • Mar 20SoftBank Corp. Develops Foundational Large Telecom ModelSoftBank Corp. announced that it has developed a new Large Telecom Model (LTM), a generative AI foundation for the telecom industry. The LTM is trained on diverse datasets--ranging from SoftBank's huge network data to the design, management, and operational know-how the company has accumulated over many years. SoftBank has also developed specialized AI models by fine-tuning the LTM, which is specifically designed to optimize base station configurations that enable advanced cellular network operations. The fine-tuned models were tasked with predicting configurations for actual base stations that had been excluded from the training phase, and their predictions were later verified by in-house experts to have over 90% accuracy. Compared to manual or partially automated workflows, the LTM-led approach reduces the time to make these changes from days to minutes, and with similar accuracy, indicating the potential for huge operational time and cost savings, in addition to reducing human error. These results demonstrate that by fine-tuning theLTM for specific use cases, it will become easier to develop dedicated AI models tailored to various operational scenarios in cellular networks. The LTM also functions as a foundation for the "AI for RAN" initiative, which aims to enhance RAN (Radio Access Network) performance through AI. In the future, the LTM is expected to serve as a blueprint for network design and support the development of network optimization AI agents. SoftBank RIAT has proposed two approaches for utilizing AI in mobile networks, "Human AI" and "Machine AI," and has now successfully realized its vision of "Human AI". SoftBank aims to integrate various AI models developed based on the LTM with the orchestrator of "AITRAS"3, an AI-RAN integrated solution currently under development by SoftBank. Main features of LTM: The LTM combines advanced inference capabilities leveraging large-scale data to solve network operational issues with flexible responsiveness enabled by natural language processing. It reflects SoftBank's extensive network and data, along with in-depth network information annotated by in-house experts skilled in network design, management, and operation. Realizing use cases specific AI models through fine-tuning: By fine-tuning models based on the LTM, it is possible to develop AI models specialized for various use cases in mobile network operations. As the first implementation, SoftBank developed models specialized in generating optimal base station configurations. Its effectiveness has been verified in scenarios including generating optimal configurations for newly deployed base stations and modifying existing base station settings to accommodate sudden traffic increases expected during events. New base station deployment: Focusing on Tokyo, a high-density urban area, the model generates optimal configurations for new base station deployments. The model receives requests to deploy a new base station in a specific area, along with additional information such as existing base station configurations and network performance, and outputs a list of configurations recommended for the new base station. Existing base station reconfiguration: Assuming a special event is taking place, the model generates configuration changes for existing base stations in the surrounding area. As SoftBank moves forward towards the deployment of the LTM, SoftBank will continue collaborating with NVIDIA on NIM Microservices Optimization for Inferencing and Aerial Omniverse Digital Twin (AODT) for simulating and validating the LTM configuration changes prior to taking actions. SoftBank will explore utilizing the LTM in its own operations, aiming to enhance mobile network efficiency, create new services, and deliver higher-quality network experiences. SoftBank will also continue to advance its research and development efforts and strengthen collaborations with partners both in Japan and abroad, thereby contributing to the further evolution of next-generation networks. In particular, the SoftBank RIAT Silicon Valley Office, which led the development of LTM in collaboration with the Japan team, will continue to grow and develop its portfolio in the USA.
お知らせ • Feb 12PayPay Bank Corporation agreed to acquire an additional 31% stake in PayPay Securities Co., Ltd from SoftBank Corp. (TSE:9434) and Ly Corporation.PayPay Bank Corporation agreed to acquire an additional 31% stake in PayPay Securities Co., Ltd from SoftBank Corp. (TSE:9434) and Ly Corporation on February 10, 2025. Upon completion, PayPay Bank Corporation will own 66% stake in PayPay Securities Co., Ltd.
お知らせ • Jan 08SoftBank Corp. to Report Q3, 2025 Results on Feb 10, 2025SoftBank Corp. announced that they will report Q3, 2025 results on Feb 10, 2025
お知らせ • Nov 14SoftBank Corp. Develops 5G L1 Software, Achieving Carrier-grade High Performance and Quality vRAN on NVIDIA Grace Hopper PlatformSoftBank Corp. announced it developed 5G L1 software based on the NVIDIA AI Aerial platform, delivering the high stability and high performance essential for a carrier-grade RAN through parallel signal processing and the optimization of task initiation timing. With this newly developed L1 software, carrier-grade stability has been achieved. In addition to realizing high stability, SoftBank will develop L1 software that can achieve maximized RAN capacity and reduced power consumption. SoftBank constructed the world’s first high-quality 5G vRAN (virtual Radio Access Network) outdoor testing environment, utilizing its newly developed L1 software running on the NVIDIA GH200 Grace Hopper Superchip platform. NVIDIA Grace Hopper Superchip architecture brings together the accelerated performance of the NVIDIA Hopper architecture with the versatility of the Arm® Neoverse™ V2 - based NVIDIA Grace CPU in a single superchip. SoftBank built the world’s first outdoor testing environment that enables the baseband processing of 20 5G cells with a bandwidth of 100 MHz on a single server featuring the NVIDIA GH200 Grace Hopper Superchip in Fujisawa City, Kanagawa Prefecture. The 4.9 GHz frequency band was used for this outdoor test and a maximum communication capacity of approximately 1.3 Gbps per cell through a maximum of 4-layer MIMO (Multi-Input Multi-Output) was achieved. The high-speed processing capabilities of NVIDIA’s accelerated computing platform are highly compatible with high-frequency bands that can be allocated to a wide frequency bandwidth per cell, and these capabilities are expected to be applied to future 6G applications such as centimeter waves. Furthermore, since such high-frequency cells are expected to be deployed in high-traffic urban areas, this AI-RAN outdoor test simulates an urban environment, creating a dense configuration with a high-interference area and a mobility area for test drives. For mobile phones, it is necessary to have stability and high connectivity that will minimize the time the cell stops functioning due to failures or malfunctions during long-term operations, as well as network outages due to deterioration of radio wave quality. To achieve these at a high level, it is required to make verifications not only in a controlled radio environment like a laboratory, but also in an irregular radio environment that is situated outdoors. In this test, SoftBank is conducting various trials using more than 100 terminals to confirm the RAN’s stability and high connectivity, which are necessary for a carrier-grade service. Going forward, SoftBank plans to evaluate spatial multiplexing technologies, such as Massive MIMO, and AI for RAN, a technology that enables the enhancement of RAN performance with AI.
お知らせ • Nov 13+ 1 more updateSoftBank Corp. Develops Orchestrator to Operate AI and vRAN on the Same Virtualized InfrastructureSoftBank Corp. announced it developed the orchestrator that enables AI applications and vRAN (virtualized Radio Access Network) applications to operate on the same virtualized infrastructure, a key concept of AI-RAN. This advancement enables the deployment of high-capacity, high-performance, and high-quality vRAN at a carrier-grade level on virtualized infrastructure running on GPU (Graphics Processing Unit) computing, including the NVIDIA GH200 Grace Hopper Superchip platform. Additionally, the orchestrator enables the integration and provision of various AI applications, such asgenerative AI, on the same platform. There are challenges in operating AI and vRAN on the same infrastructure, as service level agreements (SLAs) and server configurations differ depending on the type of workload. To address these challenges, SoftBank developed the orchestrator that enables control over infrastructure settings to meet the specific kernel and requirements of each workload. This solution is expected to deliver a highly operational and cost-effective platform. In addition to AI applications developed by SoftBank, the serverless API powered by NVIDIA AI Enterprise is also integrated with the orchestrator, enabling users to run their own AI applications on the AI-RAN virtualized infrastructure. AI and vRAN applications have distinct characteristics, requiring simultaneous optimization. For example, vRAN must control radio functions, which demands ultra-low-latency processing, whereas AI applications require efficient memory management for large data volumes and the ability to handle multiple workloads with optimal placement. To operate such diverse applications on a unified computing platform, SoftBank developed the orchestrator by building a virtualized infrastructure using Red Hat OpenShift. This orchestrator efficiently manages resources, allowing AI and vRAN applications, as well as the orchestrator itself, to run seamlessly on Red Hat OpenShift. As a result, the platform can optimize performance based on real-time resource availability within the virtualized infrastructure. Key Features of the Orchestrator: Optimal matching algorithm that considers deployment requests from users, demand forecasts, and resource availability on the supply side; Dynamic infrastructure resource adjustments based on the above algorithm; Centralized management of multi-cluster environments to support a distributed AI data center concept; Comprehensive management of configuration and resource status for all clusters and servers distributed across Japan.
お知らせ • Oct 03SoftBank Corp. to Report Q2, 2025 Results on Nov 08, 2024SoftBank Corp. announced that they will report Q2, 2025 results on Nov 08, 2024
お知らせ • Jul 04SoftBank Corp. to Report Q1, 2025 Results on Aug 06, 2024SoftBank Corp. announced that they will report Q1, 2025 results on Aug 06, 2024
お知らせ • Jun 13SoftBank Corp. (TSE:9434) completed the acquisition of 35.3% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥21.2 billion.SoftBank Corp. (TSE:9434) made an offer to acquire remaining 47.19% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥28.3 billion on April 23, 2024. Under the terms SoftBank made ¥2,950 per share for the acquisition of 9.590933 million shares and ¥1 for 424 200 shares under stock acquisition rights. If SoftBank Corp. is able to tender 90% shares then SoftBank will cash-out the remaining shares. The minimum limit for shares to be tendered is set at 2,815,600 shares(13.85%). The tender offer period is April 26, 2024 to June 11, 2024. Nishimura & Asahi and Blakemore & Mitsuki acted as legal advisor and Daiwa Securities Co. Ltd. and Nomura Securities Co., Ltd. acted as financial advisor to SB Technology. Plutus Consulting Co., Ltd. acted as fairness opinion provider and financial advisor and Kensei Law Offices acted as legal advisor to special committee of SB Technology. SoftBank Corp. (TSE:9434) completed the acquisition of 35.3% stake in SB Technology Corp. (TSE:4726) from a group of shareholders for ¥21.2 billion on April 23, 2024. SoftBank intends to carry out a set of procedures of the “Squeeze-Out Process” for making the SoftBank the only shareholder of SB Technology.
お知らせ • May 10SoftBank Corp. Reportedly Back At Deal Counter with Icertis Deal TalksSoftBank Corp. (TSE:9434) is looking to return to the deal counter in India after largely focusing on exits from listed bets last year. The Tokyo-based investment firm has begun early-stage talks to double down on existing software portfolio firm Icertis Solutions Private Limited, which is stitching up a new funding round of about $150 million (about INR 12,520 million), in a secondary share sale, said people familiar with the development. The talks would progress depending on valuation to a large extent, they said. The new funding round may see other existing backers also invest more in Icertis, they said, as some early shareholders are looking to make an exit from the 15-year-old firm. Icertis was last valued at $5 billion. SoftBank’s Vision Fund has also finalised plans for investing in ecommerce firm Meesho as part of a broader funding round. With several unicorns under its portfolio, the Japanese investor is actively reviewing potential new firms as well after a lull of more than a year – when SoftBank and Tiger Global didn’t make any deals. “The talks are in early stages and the key to the deal would be the valuation and the price discovery is yet to be finalised,” said one of the persons, who did not wish to be identified. A spokesperson for Icertis said it remains well capitalised and that it is common for new investors to seek shares in businesses like Icertis. "Icertis is not directly involved in any such secondary transactions and remains focused on empowering our customers to realise the full potential of their business relationships through contract intelligence," the spokesperson added. A spokesperson for SoftBank India declined to comment on the matter.
お知らせ • Apr 28+ 1 more updateSoftBank Corp., Annual General Meeting, Jun 20, 2024SoftBank Corp., Annual General Meeting, Jun 20, 2024, at 10:00 Tokyo Standard Time.
お知らせ • Apr 04SoftBank Corp. to Report Fiscal Year 2024 Results on May 09, 2024SoftBank Corp. announced that they will report fiscal year 2024 results on May 09, 2024
お知らせ • Jan 13SoftBank Corp. to Report Q3, 2024 Results on Feb 07, 2024SoftBank Corp. announced that they will report Q3, 2024 results on Feb 07, 2024
お知らせ • Oct 05SoftBank Corp. to Report Q2, 2024 Results on Nov 08, 2023SoftBank Corp. announced that they will report Q2, 2024 results on Nov 08, 2023
お知らせ • Jun 20SoftBank Corp. Announces Executive ChangesSoftBank Corp. announced that Kimihiko Kaneko as Member of the Board, Position at the parent companies, etc: General Manager, Technological Planning & Management Division, Technology Unit, SoftBank Corp. Takashi Naito as Audit & Supervisory Board Member. Position at the parent companies, etc: Vice President and General Manager, Finance & Accounting Division, Finance Unit, SoftBank Corp., Audit & Supervisory Board Member, SB Players Corp., Audit & Supervisory Board Member, A Holdings Corporation. As of June 19, 2023, Mr. Kunihiro Fujinaga (Senior Vice President, Deputy Head of Enterprise Business Unit, SoftBank Corp.) was appointed as a director of SoftBank Corp. with the aim of enhancing mutual synergies with the parent company and collaboration in the corporate business field.
お知らせ • May 11SoftBank Corp. (TSE:9434) announces an Equity Buyback for 56,300,000 shares, representing 1.19% for ¥100,000 million.SoftBank Corp. (TSE:9434) announces an share repurchase program. Under the program the company will repurchase 56,300,000 shares, representing 1.19% of the outstanding shares for ¥100,000 million. The purpose of the program is to enhance shareholder's value and flexibility of the capital policy. The program will run until March 31, 2024. As of March 31, 2023, the company had 4,731,548,827 shares outstanding and 55,596,343 shares in treasury.
お知らせ • Jan 07SoftBank Corp. to Report Q3, 2023 Results on Feb 03, 2023SoftBank Corp. announced that they will report Q3, 2023 results on Feb 03, 2023