Search results for: 'Computing Power'

This study focuses on heterogeneous computing architectures for automotive and robotics applications, examining how centralized and zonal compute architectures, heterogeneous SoCs integrating CPUs, GPUs, NPUs, DSPs, FPGAs, and dedicated safety islands, as well as robotics edge-AI controllers and mixed-criticality computing platforms, are enabling t...

The study evaluates photonic and optical computing technologies as critical enablers of next-generation AI infrastructure, addressing growing bandwidth, latency, power consumption, and scalability constraints associated with copper-based interconnects. The analysis covers photonic integrated circuits (PICs), optical I/O chiplets, co-packaged optics...

This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...

The rapid push toward e-mobility is accelerating adoption of advanced power electronics by major OEMs. Power electronics underpin electric vehicle reliability, efficiency, and performance. Core systems, including traction inverters, onboard chargers, and DC-DC converters, are gaining strategic importance, prompting automakers to seek compact, high-...

This study examines the technology landscape, commercialization progress, and future growth opportunities of wide-bandgap (WBG) semiconductor materials, with a primary focus on silicon carbide (SiC), gallium nitride (GaN), and gallium oxide (Ga₂O₃) for power and RF electronics. It evaluates how these materials enable higher efficiency, greater powe...

This study evaluates NVIDIA's strategic position within the global automotive industry, examining the key growth drivers, competitive dynamics, and market developments shaping its automotive business. It explores NVIDIA's evolution from a semiconductor company to a full-stack AI platform provider, with a focus on autonomous driving, software-define...

Chiplet-based compute architectures for vehicles are entering a new phase, reshaping SDV hardware roadmaps by enabling modular multi-die platforms that scale performance, improve yield, and accelerate refresh cycles while meeting long lifecycles, safety, and cybersecurity requirements. This Frost & Sullivan study examines how automakers, Tier 1s, s...

This Frost Radar™ benchmarks the leading companies in the AI-powered in-car assistant market. They are spearheading the development of advanced conversational, personalized, and context-aware in-vehicle experiences for original equipment manufacturers and Tier I suppliers. The analysis included a review of each company's AI assistant portfolio, res...

The Mobility Technology Opportunity Engine (TOE) provides profiles of innovations related to Next-generation Anti-friction Coating, Augmented Reality (AR) Platform, Vehicle-to-everything (V2X)-based Connected Vehicle Solutions, High-performance Electric Drive Technology, Remote-controlled Vehicle Platform, AI-driven Connected Mobility Platform and ...