Background
While the QLLM technology introduced by SECQAI is promising, the high cost of quantum infrastructures and large data requirements pose significant challenges for resource-limited organizations.
Core Solutions
- Cloud Quantum Computing Service: On-demand access to quantum resources via AWS Braket, Azure Quantum, and more, without the need to build your own infrastructure
- hybrid computing model: Combine classical computing with quantum computing, using quantum resources only for critical links
- Data Optimization Strategy: Reduce the amount of data using feature selection and dimensionality reduction techniques, e.g., using PCA or quantum-inspired classical algorithms
- Alliance Learning: Join industry consortium to share quantum computing resources and share costs
Implementation of recommendations
It is recommended to implement in phases: 1) test the core functions through API access first; 2) evaluate the ROI of key business scenarios; 3) gradually establish internal quantum-ready data pipelines.
This answer comes from the articleWorld's First Quantum AI Model! SECQAI Releases QLLM for Beta Testing!The
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