WiMi Hologram Cloud announced a new quantum convolutional neural network (MC‑QCNN) designed for multi‑channel supervised learning, enabling the processing of RGB images, medical scans, and video streams directly on quantum hardware.
The MC‑QCNN architecture incorporates single‑bit rotation gates, controlled parameterized gates, SWAP interleaving, weak entanglement layers, and channel‑interaction gates to form a convolution operator that captures high‑order cross‑channel features. A learnable quantum pooling circuit further compresses feature maps while preserving key information, addressing the measurement‑induced loss that has limited earlier quantum CNNs.
This launch marks a strategic pivot for WiMi toward high‑margin quantum‑enabled products. By extending its portfolio beyond AR holographic services and semiconductor algorithm offerings, the company positions itself to capture new revenue streams in image classification, medical imaging, and multimodal monitoring, all of which rely on multi‑channel data processing.
The announcement was well received by investors, reflecting confidence in WiMi’s quantum AI strategy and the potential for commercial deployment of the technology.
While WiMi has not yet reported revenue from MC‑QCNN, the technology is expected to strengthen the company’s quantum AI segment, which has been growing as part of its broader R&D investment. The launch signals a move toward higher‑margin offerings that could offset the company’s historically volatile earnings and support future growth.
WiMi continues to invest in quantum computing and AI, and the MC‑QCNN launch underscores its commitment to translating laboratory breakthroughs into marketable solutions. The company will likely pursue partnerships and commercial pilots to bring the technology to customers in the near term.
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