Kakao Mobility Declares Autonomous Driving Innovation with E2E Technology Kakao Mobility is accelerating its transformation into a Physical AI company by recruiting talent in the End-to-End (E2E) autonomous driving sector. This move is seen as a strategic step by a domestic IT company to lead the future mobility market through core technology development, moving beyond simply providing platform services. Kakao Mobility's current initiative is part of a broader strategy to build an advanced AI system that processes and learns complex real-world data to make its own decisions and actions, going beyond mere autonomous driving technology development. E2E autonomous driving technology refers to an approach that integrates the entire autonomous driving process, from sensor data input to vehicle control output, into a single AI model. Conventional module-based development methods processed each stage—such as perception, judgment, and control—as separate software modules. In this traditional process, information loss occurred during data transfer between modules, and optimizing across modules presented a challenge. In contrast, the E2E approach processes these stages within a single, integrated AI model, enabling the construction of a more efficient and flexible system. By directly learning raw data collected from sensors and outputting final control commands, the complexity of intermediate steps is reduced, and the overall system becomes easier to optimize. Through this E2E autonomous driving technology, Kakao Mobility aims to provide safer and more efficient mobility services and, furthermore, secure a leading position in the Physical AI sector. Physical AI refers to AI systems that go beyond merely operating in digital space, interacting with the physical environment in the real world to perform actual tasks. Autonomous vehicles are a prime example of Physical AI in action, as the entire process of recognizing complex road environments, responding to real-time changes, and safely reaching a destination occurs in the physical world. This talent recruitment is a crucial step for Kakao Mobility to leap forward as a Physical AI company. It demonstrates the company's commitment to securing experts in various fields, including autonomous driving algorithms, sensor fusion, control systems, and AI model optimization. Developing E2E autonomous driving systems, in particular, requires expertise in multiple areas such as deep learning model design, large-scale data processing, real-time inference optimization, and vehicle control system integration. By recruiting talent across these diverse fields, Kakao Mobility aims to strengthen its technological development capabilities and accelerate the commercialization of E2E autonomous driving technology. Kakao Mobility has already advanced its autonomous driving technology based on its experience operating a MaaS (Mobility as a Service) platform and its vast data resources. The real-world driving data, traffic pattern information, and user movement data accumulated as a leading domestic mobility platform are invaluable assets for training E2E autonomous driving AI models. Data reflecting Korea's unique road environments, traffic culture, and driving patterns will play a crucial role in developing autonomous driving systems optimized for the local context. This can be seen as a localized strategy, distinct from how international companies develop global standard models. Physical AI and the Evolution of Korea's Mobility Market The development of E2E autonomous driving technology is expected to play a significant role not only in technological advancement but also in expanding Kakao Mobility's business scope. This transition to Physical AI is projected to be crucial for applying autonomous driving technology across all mobility services and strengthening competitiveness in future mobility markets, including robot taxis and autonomous delivery. Robot taxis are services that safely transport passengers to their destinations without a driver, offering advantages such as reduced labor costs and 24-hour operation. Autonomous delivery involves autonomous vehicles or robots delivering goods from logistics centers to final destinations, which can increase delivery efficiency and reduce costs. Kakao Mobility's Physical AI transformation strategy is also expected to create synergy with its existing mobility platform businesses. The accumulated user needs and operational know-how from currently operating services like taxi hailing, designated driver services, and parking can be integrated into autonomous driving service design. For instance, data on preferred routes, pick-up/drop-off locations, and service usage patterns will serve as crucial references when designing robot taxi services. Furthermore, the existing platform's vast user base can be advantageous for securing an early market share for autonomous driving services. The core of E2E autonomous driving technology lies in the AI model d
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