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Since 2017, Uniquify's Video Display Technology has been integral to Tier-1 4K and 8K UHD TV manufacturers. This technology offers a multitude of image enhancement algorithms aimed at improving visual quality at a reduced cost of implementation. It includes AI-enabled super resolution for scaling images, dynamic color and capacitance compensation, and advanced compression techniques. These features contribute to delivering high-definition visuals with accurate color representation and reduced motion blur, essential for high-performance display systems in consumer entertainment.
Renowned as the only DDR system incorporating patented technologies that adjust to environmental and system variations, the High Speed Adaptive DDR Interface addresses the dual demands of high performance and low power. It effectively meets the technological needs of diverse markets like data centers, 5G, and AI/ML, while maintaining compatibility with DDR3/4/5, LPDDR3/4/5, and HBM standards. By leveraging over 24 US patents, Uniquify achieves high performance with reduced power, area, and latency costs, setting it apart as a leader in DDR interface technology.
Uniquify's High-Speed SerDes Technology supports a wide range of SerDes standards, essential for high-speed data transfer across modern communication systems. Designed by an experienced and versatile engineering team, this technology provides configurations with bit rates ranging from 4 Gbps for video display processor applications to 56 Gbps for photonics optical transceivers. This adaptability makes it a critical component in server and network backbone infrastructure. Built on process nodes like TSMC 28HPM+ and TSMC 7FFC, these SerDes modules ensure high-performance data transmission across various applications.
Uniquify's Edge AI Neural Network Fabric 2.0 is specifically designed for the next generation of neural networks, supporting a wide range of architectures including CNN, RNN, FNN, and GAN. This innovative framework is notable for its smaller area, reduced cost, and decreased power consumption, making it an ideal solution for AI applications. It provides robust support for batch normalization and autoencoders, enhancing both performance and efficiency in AI processing tasks. This architecture is pivotal in driving advancements in edge computing, where computational efficiency and reduced energy usage are critical.
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