Thewake Systems

About Us

Thewake Systems is committed to building next-generation AI fundamental operators and models through a quantum-fused heterogeneous computing system (QHS).

Our core technology adopts quantum embedding, variational quantum circuits (VQC), and physics-aware learning. By embedding physical laws as hard constraints into models, we achieve 100% physical consistency, ultra-high Sim-to-Real transfer rates, and exponential reduction in model parameters and training requirements, breaking through the physical blind spots and dimensional disasters of traditional AI.

The company has developed a unified quantum-classical computing representation language and compilation system, enabling implicit representation VQC to effectively replace the fully connected structure of traditional transformers. Our intelligent models have been delivered to clients and serve precision manufacturing, agricultural robotics, and other real-world scenarios, securing orders from leading enterprises.

Leveraging top-tier technical teams from Tsinghua University and deep industry-academia-research accumulation, we are dedicated to building a quantum physics large model ecosystem and constructing a solid foundation for next-generation embodied intelligence and industrial intelligence.

Company Culture

Our Mission: Reconstructing intelligence with quantum computing power, empowering humanity to explore the infinite universe

Our Vision: Contribute more employment opportunities to society through continuous innovation and bring happiness to more people

Our Values: Serve the people wholeheartedly

Work Environment

Core Technology & Products

Quantum Language - Thewake-QL

Quantum Operator - Thewake-QC

Quantum Model - Thewake-QM

Research

Thewake RiverYtz Lab

Quantum-native intelligence for physical world systems

Our research explores quantum-classical computing, physics-aware learning, and next-generation AI operators for embodied intelligence, industrial intelligence, and scientific discovery.

Publications

Selected papers from the Thewake systems, with authors, venues, and links to full text and code.

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RiverONE: Generating Knowledge-Intensive VLM by Simulated Quantum Machines

Xindian Ma, Xinyu Long, Yefei Zhang, Yanchen Liu, Xianghao Li, Yufu Wen, Yike Hu, Yuedong Zhu, Zeyang Ma, Wen Qin, Yikun Wang, Peng Yang, Monan Wang, Teng Yu

Quantum computing provides a powerful paradigm for representing and transforming high-dimensional information through superposition, entanglement, and measurement-induced nonlinear features. While current quantum hardware is not yet practical for direct large-scale vision-language model (VLM) inference, simulated quantum computation can be used during model construction to generate structured parameters for compact classical AI systems. We build RiverONE, a lightweight vision-language model for quantum calibration plot understanding, using simulated quantum computation. It employs a specialized visual encoder and an InternVL-based language backbone. To compensate for compression-induced information loss, we introduce quantum-generated parameters, which are materialized as classical tensors after training. This allows RiverONE to run entirely on classical GPUs at inference time, with no quantum hardware or runtime quantum simulation. With approximately 1.9 billion parameters, RiverONE achieves at least 95% of the performance of NVIDIA Ising Calibration 1 on quantum calibration plot understanding tasks while using less than 10% of its parameter count. These results suggest that simulated quantum computation can serve as a practical construction-stage mechanism for building lightweight, knowledge-intensive scientific VLMs.

PDF Project

2024 · ASPLOS '24

Optimizing Deep Learning Inference via Global Analysis and Tensor Expressions

Chunwei Xia, Jiacheng Zhao, Qianqi Sun, Zheng Wang, Yuan Wen, Teng Yu, Xiaobing Feng, Huimin Cui

Optimizing deep neural network (DNN) execution is important but becomes increasingly difficult as DNN complexity grows. Existing DNN compilers cannot effectively exploit optimization opportunities across operator boundaries, leaving room for improvement. To address this challenge, we present Souffle, an open-source compiler that optimizes DNN inference across operator boundaries. Souffle creates a global tensor dependency graph using tensor expressions, traces data flow and tensor information, and partitions the computation graph into subprograms based on dataflow analysis and resource constraints. Within a subprogram, Souffle performs local optimization via semantic-preserving transformations, finds an optimized program schedule, and improves instruction-level parallelism and data reuse. We evaluate Souffle using six representative DNN models on an NVIDIA A100 GPU. Experimental results show that Souffle consistently outperforms six state-of-the-art DNN optimizers, delivering a geometric mean speedup of up to 3.7× over TensorRT and 7.8× over TensorFlow XLA.

PDF DOI

Supply Chain Matrix

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Arclight Quantum

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Zhixing Hey

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Supplier Recruitment

If you are interested in cooperating, please fill in the supplier intention registration form and confidentiality agreement and send it back to the email: Research@thewakesystems.com

Investor Relations

Beijing Cyberpunk Singularity Technology Center (Limited Partnership)

Ningbo Zheyi Electronics Co., Ltd.

Infinite Voyage Venture Capital (Tianjin) Partnership Enterprise (Limited Partnership)

MPlus HK I Limited

Shuimu Huaqing (Guangzhou) Venture Capital Partnership Enterprise (Limited Partnership)

Shenzhen Zhuoyuan Morning Star Seed Venture Capital Partnership Enterprise (Limited Partnership)

Shenzhen Zhuoyuan Intelligent Venture Capital Partnership Enterprise (Limited Partnership)

Beijing Zhongchuang Star No.9 Enterprise Management Center (Limited Partnership)

Invest In Us

Thewake Systems is open to cooperation with domestic and foreign insurance investment institutions, financial lending institutions, and individual investors. If you are interested in cooperation, please fill in the Investment Intention Registration Form and Non-Disclosure Agreement and send it back to the email: Research@thewakesystems.com

Join Us

Marketing Manager

AI Development Intern