Latest news with #Software-DefinedVehicles
Business Standard
21 hours ago
- Automotive
- Business Standard
Tata Technologies partners with DIYguru to empower students & professionals with iGETIT-led industry relevant E-Mobility hybrid learning programs
VMPL Pune (Maharashtra) [India], August 11: Tata Technologies, a global product engineering and digital services company through its globally acclaimed iGETIT platform, has signed a strategic Memorandum of Understanding (MoU) with DIYguru, India's leading online education provider for electric vehicle (EV), Embedded Systems and future mobility upskilling. The partnership aims to jointly empower engineers and professionals with iGETIT-led industry-aligned skills in Product Design and Development, Electric Vehicle technologies, Software-Defined Vehicles (SDVs), Advanced Driver Assistance Systems (ADAS) & AUTOSAR, aligning with India's fast-evolving mobility landscape. The MoU was formalized between Mr. Manish Kohli, Global Head & Vice President - EdTech, Tata Technologies, and Mr. Avinash Singh, CEO of DIYguru. Tata Technologies, iGETIT platform, provides world-class learning solutions designed for engineers working in automotive product development, embedded systems, and manufacturing transformation. With DIYguru's hands-on EV and hardware-focused training ecosystem, this collaboration will create a future-ready engineering talent pool to meet India's growing need for advanced mobility solutions. "Tata Technologies has always been at the forefront of preparing engineering talent for the next era of product development. Through this collaboration with DIYguru, we aim to provide real-world EV and SDV expertise through our iGETIT platform and enable professionals to contribute to the future of mobility," said Manish Kohli, Global Head & VP - EdTech, Tata Technologies. Key Focus Areas of the MoU Support specialized upskilling programs in EV, ADAS, SDV, and AUTOSAR run by DIYguru. Leveraging iGETIT's global content library with DIYguru's project-based EV and Embedded hardware training Enabling job-ready engineers for OEMs and Tier-1 automotive suppliers Bridging the industry-academia gap through real-world automotive use cases and capstone projects Under this collaboration, DIYguru students enrolling in various certification and postgraduate programs will receive an exclusive one-year access to curated iGET IT e-learning paths in domains such as Electric Vehicles, Product Design and Development, Embedded Systems and other automotive technologies. Tata Technologies' iGETIT platform will own and deliver the digital curriculum, pedagogy, global certification, and quality assurance. Participants will also be awarded digital certificates, adding strong industry recognition to their skill development journey. DIYguru will provide practical instructor led training, hardware-intensive training labs, project supervision and electric vehicle prototyping. Together, the collaboration ensures engineers gain both conceptual mastery and real-world application capability. "Collaborating with Tata Technologies and their iGETIT platform is a milestone for DIYguru. This partnership allows us to integrate our EV-centric expertise with Tata's global upskilling ecosystem, building the engineering workforce that India's future mobility sector requires," said Avinash Singh, CEO, DIYguru. This initiative supports India's Atmanirbhar Bharat and Skill India goals, by developing a homegrown engineering talent ecosystem aligned with EV adoption, autonomous mobility and smart manufacturing About DIYguru Mobility DIYguru ( is India's leading edtech platform for Electric Vehicles (EV) and future mobility, with a global learner base of over 85,000 professionals and students. Focused on bridging the industry-academia gap, DIYguru offers hands-on, application-oriented training programs in EV technology, sustainable mobility, IoT, and renewable energy. DIYguru works in close collaboration with leading automotive OEMs, emerging startups, and top academic institutions to deliver certified up-skilling programs aligned with the evolving needs of the mobility sector. Through its unique blend of online learning, practical labs, and real-world projects, DIYguru is empowering a new generation of engineers and technicians to drive India's green mobility revolution. About Tata Technologies Tata Technologies (BSE: 544028, NSE: TATATECH) is a global product engineering and digital services company focused on fulfilling Its mission of helping the world drive, fly, build, and farm by enabling Its customers to realize better products and deliver better experiences. iGETIT ( is Tata Technologies' premier e-learning platform designed to equip engineers with cutting-edge skills in product design, embedded systems, and advanced automotive technologies. Tata Technologies is the strategic engineering partner businesses turn to when they aspire to be better. Manufacturing companies rely on Tata Technologies to enable them to conceptualize, develop and realize better products that are safer, cleaner, and improve the quality of life for all the stakeholders, helping us achieve our vision of #EngineeringABetterWorld.
Business Standard
23-07-2025
- Automotive
- Business Standard
Minda Corporation announces strategic collaboration with Qualcomm
To develop smart cockpit solutions for the Indian automotive market Minda Corporation announced its strategic collaboration with Qualcomm Technologies, Inc. to develop smart and advanced cockpit solutions for the Indian automotive market. As part of their collaboration, Minda Corporation is designing a next-generation cockpit platform powered by the Snapdragon Cockpit Platform from Qualcomm Technologies. A key element of the Snapdragon Digital Chassis Solution, the Snapdragon Cockpit Platform enhances in-car experiences by delivering sophisticated displays, audio, computing and connectivity, making them more responsive and enjoyable. With these next generation Snapdragon Digital Chassis solutions, Minda's new cockpit domain controllers will be equipped to support rich multimedia experiences, AI-driven interfaces and seamless cloud integration enhancing the cockpit performance, digital user interface and vehicle connectivity for Software-Defined Vehicles (SDVs).
Yahoo
12-06-2025
- Automotive
- Yahoo
Global and China SDV, OEM Software Development and Supply Chain Deployment Strategy Research Report 2025: Toolchain Framework from 13 Subsystems and 48 Dimensions
Discover insights into OEM software for software-defined vehicles from 48 dimensions. Explore comprehensive layers, development strategies, and toolchain frameworks, featuring Li Auto's AI-driven autonomous driving system and Xiaomi's real-time data integration. Learn about Geely's AI Cloud Power for energy and motion control, and Xpeng's AI Chassis Active Perception enhancing driving comfort. Dublin, June 12, 2025 (GLOBE NEWSWIRE) -- The "Software-Defined Vehicles in 2025: OEM Software Development and Supply Chain Deployment Strategy Research Report" report has been added to Research: OEM software development and supply chain deployment strategies from 48 dimensions The overall framework of software-defined vehicles: (1) Application software layer: cockpit software, intelligent driving software, vehicle control software, and AI empowerment, etc.; (2) Functional software layer: cloud services, security services, etc.; (3) System software layer: vehicle OS, middleware and SOA, etc.; (4) R&D tools: process and systematization tools, data closed loop, development toolchains, this report, we specifically expound the OEM vehicle software development and toolchain framework from 13 subsystems and 48 dimensions in order to analyze the R&D focus, development strategies and supply models of OEMsAutonomous driving software algorithm: Compare automotive VLMs and VLA models with cloud world models, and fully mobilize supply chain resources to assist developmentFor example, Li Auto uses multimodal foundation models and generative AI technology to enable autonomous driving. The key technical architecture includes: an end-to-end intelligent driving model, VLM, VLA, cloud-based reconstruction and an generative world Auto fully integrates academic and supply chain resources to accelerate the development of its autonomous driving system: Li Auto has proposed an advanced hybrid BEV algorithm framework with Tsinghua University and MIT, and cooperated with Tsinghua MARS Lab to develop the DriveVLM model; The next-generation architecture MindVLA released in 2025 and the GaussianAD from the University of California, Berkeley optimize scenario modeling and trajectory prediction; Li Auto cooperates with GigaStudio to explore the construction of 4D world models, introduce the DriveDreamer4D framework, and use world models to enhance the reconstruction effect of 4D driving scenarios; Keleyuan operates Li Auto's 4D BEV data collection project and is responsible for the annotation, analysis and processing of automotive sensor (such as LiDAR) data to generate high-precision road information data. Its services cover road data collection in multiple cities across the country, supporting the optimization of dynamic perception and prediction capabilities of Li Auto's intelligent driving platform; Singstor provides a massive data collection and storage solution for autonomous driving with the core being customized automotive high-performance optical fiber high-speed storage devices, supporting real-time data recording and synchronization across regions; 4D automatic annotation system: Li Auto has built a full-process system covering dynamic obstacle detection and tracking, laser/visual SLAM reconstruction, static element annotation and OCC (common obstacle) annotation. The physical world model framework built by Xiaomi Automobile consists of a data observation layer (Ot), an implicit feature layer (Zt), and a display symbol layer (St):The data observation layer (Ot) is the input layer of the neural network. The sensor input includes images, LiDAR point cloud, and navigation information required by the implicit feature layer (Zt), the information of the input layer in the previous step is expressed as a private feature through the BEV coding network. Through different decoders, dynamic elements, static elements, and the future trajectory of the vehicle can be obtained the display symbol layer (St), in order to facilitate human understanding and connect with manual rule codes, the model will decode the displayed symbolic expressions, such as static lane lines, zebra crossings, etc., dynamic pedestrians, vehicles, etc., which are also the expression forms of manual or automatic value-added annotation in supervised architecture breaks through the fragmentation of traditional modular systems and integrates perception, planning, and control into a single end-to-end model, significantly improving system the model architecture is set up, it is necessary to open up data-driven channels so that the model can automatically output the real required conclusions driven by data to form a data-driven flywheel. The technical iteration of Xiaomi SU7 leverages the closed loop of "production vehicle data - simulation training - OTA updates" to deliver vehicles running on roads and quickly accumulate a complete database of Chinese road terms of toolchains, Xiaomi has conducted in-depth cooperation with NVIDIA to optimize cloud training and automotive inference:Cloud: By reconstructing the inference pipeline based on Triton, the efficiency of automatic annotation is improved by 100%; by optimizing the training process through DALI and CV-CUDA, the GPU utilization rate is increased by 30%.Vehicle: The Thor platform accelerates model reasoning, doubling performance compared to the initial version; it offloads tasks such as image processing and point cloud compression to heterogeneous computing units (VIC, ISP) to alleviate pressure on the main computing control software algorithm: Make full use of AI empowermentThe empowerment of AI technology in the development of automotive motion control software is mainly reflected in algorithm optimization, development process innovation, and improvement of system integration capabilities, spurring the industry towards a more intelligent, efficient and safe Xingrui AI Cloud PowerGeely has developed the Xingrui AI Cloud Power. The Xingrui AI Cloud Power 1.0 mainly realizes AI empowerment in smart energy management, smart motion control, and smart cloud smart motion control: Based on the real-time perception of the drive motor, vehicle posture, camera vision, weather and other information, AI intelligent recognition of driving style, road terrain, and environmental conditions is achieved, and the drive system is dynamically adjusted to perform precise real-time control "according to local conditions", reducing slippage by 50% and improving tracking stability by 15%;AI smart energy management: Integrating the Xingrui AI cloud power model, AI realizes intelligent decision-making for global optimization, evolving the previous rule control into one that can perceive external temperature, humidity, altitude, slope and other road conditions in real time through AI, and can intelligently adjust the energy management strategy at any time, thereby reducing the fuel consumption of electric hybrid sedans to 2L and electric hybrid SUVs to smart cloud diagnosis: Based on digital twin technology, power systems, "electric drive, battery and electric control" components and thermal management systems are fully monitored, and automatic repair and proactive maintenance are plans to further launch Xingrui AI Cloud Power 2.0 in 2025, which extends battery life by 15% and reduce energy consumption by 5% through model compression AI Chassis Active Perception Xpeng has added AI chassis active perception and automatic chassis adjustment to its two flagship models - X9 and G9:The vehicle's sensors preview the road surface and the chassis suspension is adjusted accordingly. The standard intelligent dual-chamber air suspension of Xpeng X9 includes intelligent dual-chamber air springs and intelligent variable damping shock absorbers. It can efficiently filter road vibrations, effectively isolate minor bumps, and offer a gentle and smooth driving experience, taking into account both comfort and utilizes automotive sensors and cloud AI technology. When it determines that the vehicle passed a bumpy point, it immediately uploads relevant information to the cloud. A new bumpy layer is formed on the cloud, allowing the vehicle to detect bumps and potholes ahead earlier, giving the driver more time to operate. At the same time, the stiffness of the suspension will be adjusted before the bump to improve Topics Covered: 1 Software Development and Supply Chain Deployment Strategies of Emerging OEMs in China Xpeng Motors NIO Li Auto Xiaomi Automobile ZEEKR Leapmotor IM Voyah ARCFOX Avatr 2 Software Development and Supply Chain Deployment Strategies of Independent Brand OEMs in China BYD Changan Automobile Geely GAC Motor FAW Hongqi Chery Great Wall Motor 3 Software Development and Supply Chain Deployment Strategies of Foreign OEMs Volkswagen Audi Mercedes-Benz BMW Ford SAIC-GM Volvo Tesla Dongfeng Nissan Toyota Motor Honda Motor 4 OEM Software Development Strategies and Application Trends OEM Vehicle Control Software: Development Strategies and Application Trends OEM Vehicle Control Software Solution Development Strategies and Supply Chain OEM Vehicle Control Software Application Trends OEM Cockpit Software: Development Strategies and Application Trends OEM Cockpit Software Application Trends OEM Autonomous Driving Software: Development Strategies and Application Trends OEM Autonomous Driving Software Application Trends OEM AI Software Empowerment: Development Strategies and Application Trends OEM AI Software Solution Development Strategies and Supply Chain - OEM AI Software Application Trends OEM Functional Software: Development Strategies and Application Trends OEM Functional Software Application Trends OEM Software Toolchain: Development Strategies and Application Trends OEM Software Toolchain Application Trends For more information about this report visit About is the world's leading source for international market research reports and market data. 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