Edge AI refers to the deployment of artificial intelligence models directly on edge devices such as sensors, cameras, mobile devices, or embedded systems, rather than relying on centralized cloud infrastructure. It enables local data processing, reducing latency, bandwidth usage, and privacy risks. Edge AI systems often use optimized models and hardware accelerators to operate under constraints of power, memory, and compute, supporting real-time applications in areas such as autonomous systems, industrial monitoring, and smart environments.
Mix-CLAP from NEC Laboratories America delivers near-Transformer accuracy for sound event classification at a fraction of the compute cost, using dual lightweight encoders and adaptive, noise-aware inference for real-world edge deployment.
Machine learning is shifting from learning from data alone to learning from both data and teacher models. Beta-KD uses uncertainty-aware Bayesian weighting to train compact multimodal AI without blindly trusting every teacher signal.
Eric C. Blow of NEC Laboratories America presents a keynote at COOL Chips 29 in Tokyo, exploring multi-modal photonic computing for real-time, ultra-efficient inference. This work highlights how photonics is reshaping AI performance, enabling faster and more energy-efficient processing across next-generation systems.
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NEC Laboratories America, Inc. (NEC Labs) is the US-based center for NEC Corporation’s global network of corporate research laboratories. Our diverse research groups collaborate with industry, academia and governments to provide disruptive solutions to complex problems. A leader in the integration of IT and network technologies with more than 100 years of expertise, NEC provides a combination of products and solutions that cross-utilize the company’s experience and global resources to meet the complex and ever-changing needs of its customers.