AI Technology & Industry Review
A research team from Samsung makes a first attempt to facilitate LLM deployment on edge devices using integer-only quantization. The proposed MobileQuant, is a post-training quantization technique that reduces both inference latency and energy consumption while preserving accuracy comparable to those achieved with 16-bit activations.
A Google research team unveils the latest iteration of MobileNets: MobileNetV4 (MNv4). This cutting-edge model boasts an impressive 87% ImageNet-1K accuracy, coupled with an astonishingly low Pixel 8 EdgeTPU runtime of merely 3.8ms.
In the new paper Face Deblurring Using Dual Camera Fusion on Mobile Phones, a Google team proposes a novel dual camera fusion technique that achieves robust face deblurring in diverse motion and lighting conditions.
A research team from Hotg.ai and Ghent University explores current challenges facing TinyML and techniques to reduce the compute, memory, and energy costs of ML models, providing insights for the large-scale deployment of edge AI.
On October 6, Sony Group announced that the company will launch its edge AI platform service Aitrios AI sensing platform in Japan, the U.S. and Europe starting late this year.
A research team from ETH Zurich leverages existing spike-based learning circuits to propose a biologically plausible architecture that is highly successful in classifying distinct and complex spatio-temporal spike patterns. The work contributes to the design of ultra-low-power mixed-signal neuromorphic processing systems capable of distinguishing spatio-temporal patterns in spiking activity.
Dell Technologies has opened a new innovation facility in Singapore, to focus on R&D for edge computing, data analytics and augmented reality.
The GTC kicked off with the release of nine Nvidia keynote video with major announcements in data centers, edge AI, collaboration tools and healthcare.