Dedicated for Video Intelligence

[INQ. NO. 2601E01] DEEPX Co., Ltd., an on-device artificial intelligence (AI) semiconductor company, recently launched its dedicated video intelligence chipset, DX-H1 V-NPU, which processes hundreds of channels of video AI analysis with as little as 30 watts (W).
This product integrates video input, compression, and AI inference processes, which previously separated across graphics processing unit (GPU) servers and separate codec equipment, into a single card — thereby reducing the power consumption, cost, and complexity of large-scale video AI processing.

By processing hundreds of channels at 30 watts (W), it reduces costs by approximately 80% and power consumption by approximately 85% compared to GPUs. It is considered an alternative to addressing the issues of data-center power shortages and the uncertainties of GPU supply and demand.
DEEPX emphasized that the DX-H1 V-NPU marks a turning point in shifting the basic unit of video AI infrastructure from GPUs to V-NPUs (Vision Neural Processing Units).
It is designed to integrate multi-channel decoding, encoding, and transcoding with a dedicated NPU on a single chip ― to seamlessly process real-time streams. It aims to be a platform that transforms large-scale video AI infrastructure ― such as smart cities, transportation, and industrial control ― into a V-NPU-centric structure.
This product maintains real-time inference performance around the clock, while reducing hardware costs by approximately 80% and power costs by approximately 85% compared to GPUs based on the same number of channels.
While GPUs boast general-purpose computing capabilities, they are not optimized for multi-channel video input/output and real-time streaming.

A spokesperson for the company explained, “Large-scale video AI will no longer rely on the spare computing power of general-purpose GPUs, but will instead operate on dedicated chipsets,” predicting “It will become an integral part of industries such as smart cities, traffic control centers, and national infrastructure.”

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