Best of LinkedIn: Next-Gen Vehicle Intelligence CW 35/ 36

The past two weeks highlighted accelerating momentum in software-defined mobility, with OEMs, suppliers, and tech players sharpening focus on software platforms, AI-driven autonomy, and strategic partnerships. New benchmarks and product launches reflect a market moving rapidly from conceptual frameworks toward tangible deployments.

Date

August 27, 2025

Software-Defined & AI-Defined Vehicles

Thomas Allgeyer

Methodology: Every two weeks we collect most relevant posts on LinkedIn for selected topics and create an overall summary only based on these posts. If you´re interested in the single posts behind, you can find them here: https://linktr.ee/thomasallgeyer. Have a great read!

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Software-Defined Vehicles (SDVs)

Strong industry narrative on SDVs as the next frontier, with emphasis on integrated vehicle operating systems, closed-loop development, and AI-ready architectures driving competitive differentiation.
IBM positioned its consulting and engineering capabilities to cut innovation cycles from two years to six months through modular platforms and agile delivery.
Dassault Systèmes introduced the shift toward AI-Defined Vehicles (AIDVs), leveraging Chinese OEM momentum and highlighting synergies between high-tech and automotive sectors.

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Artificial Intelligence and ADAS

Automobility’s ADAS Guide 2025 showcased a global landscape, with Chinese OEMs (BYD, XPeng, NIO, Li Auto, Xiaomi) gaining visibility alongside global leaders such as BMW, Tesla, and Ford.
Industry experts stressed critical ADAS topics including automated emergency braking, AI-based parking, predictive maintenance, and camera technology evolution.
Insights from AI specialists reinforced that vehicle intelligence is transitioning from rule-based systems to adaptive, explainable, and ethical AI frameworks.

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Partnerships and Collaborations

Valeo and Capgemini announced a joint effort on ADAS testing and validation, signaling deeper collaboration between Tier 1 suppliers and digital engineering firms.
Broader ecosystem discussions centered on open-source versus commercial automotive stacks, with communities like Eclipse SDV and COVESA gaining traction but still facing maturity challenges.

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Benchmarks and Standards

MLCommons launched its first automotive-specific benchmark (MLPerf Automotive v0.5), providing a critical reference point for AI model performance in vehicle contexts.
This move reflects growing recognition that common standards are needed to enable industry-wide comparability and accelerate adoption of advanced vehicle intelligence.

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Product Launches and Innovations

TomTom unveiled a navigation application designed specifically for SDVs, emphasizing scalability and full-stack integration as a way to reduce automaker development costs.
Experimental projects such as AI-generated drone design frameworks highlighted the cross-sector relevance of software-defined concepts, pointing to future convergence of mobility and aerospace innovation.

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