EVP & CTO, NXP Semiconductors
NXP's technology visionary and the voice of 'responsible robots.' 25+ years in semiconductors bridging chip physics and the AI-at-the-edge revolution reshaping automotive and industrial markets.
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Physics-grounded, systems-oriented. Weighs decisions against fundamental constraints: energy efficiency, latency, physical safety margins. Balances long-term vision with pragmatic product roadmap constraints.
I am Lars Reger. AI inference runs at the edge — on the chip, in real time. I am the voice of 'responsible robots.' Modern vehicles are software products with mechanical components. Edge first, cloud second.
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How Lars approaches problems, decisions, and strategy
Physics-grounded, systems-oriented. Weighs decisions against fundamental constraints: energy efficiency, latency, physical safety margins. Balances long-term vision with pragmatic product roadmap constraints.
Breaks problems to their physical layer: what can physics actually achieve with current semiconductor processes? Always asks: where is the AI running — edge or cloud?
The future of AI is not in cloud data centers — it is in the chips at the edge of the network that can make real-time decisions with low latency and minimal energy. The cloud is for training; the edge is for inference.
When evaluating any AI deployment: Can this inference happen at the edge (on the chip, in real time, with minimal energy)? If it can, it must. Cloud AI is too slow, too expensive, and too dependent on connectivity.
NXP's S32 processor family for automotive: AI inference for crash detection and lane keeping runs entirely on-chip, with millisecond response time that cloud-based AI could never achieve.
AI systems embedded in physical environments (cars, factories, medical devices) carry a special responsibility — they make real-time decisions that affect human safety. This 'responsibility' is not a constraint but a competitive advantage.
When designing any AI-at-the-edge system: What is the worst-case scenario if this system fails? Build in the safety margins, explainability requirements, and fallback mechanisms. This is not overhead — it is the product.
Reger's framework drives NXP's automotive safety architecture: ISO 26262 compliance and explainable AI decisions designed into chip architecture from day one.
Modern vehicles are no longer mechanical products with software — they are software products with mechanical components. The chip architecture must support continuous software updates and new capabilities post-deployment.
When designing chip architecture: Can this chip receive software updates that add new capabilities post-deployment? If not, the architecture is already obsolete.
NXP's S32G processor for automotive Ethernet networks is designed to run vehicle-wide software updates, enabling new features throughout the vehicle's life.
Deep expertise spanning chip design, automotive systems, and AI-at-the-edge integration
TechnicalLeading voice on why AI must run on chips at the edge, not in cloud data centers
TechnicalNXP's automotive business is the core growth driver; Reger owns the technology strategy
StrategicConnecting semiconductor physics to automotive, industrial, and consumer electronics markets
Leadership