AI DataMind

After the involvement of numerous experts, scholars, and technologists, under the leadership of Dexter Quisenberry, SW Alliance developed AI DataMind 1.0, which significantly improved the shortcomings of previous quantitative trading models. The system is more efficient, faster, and intelligent.

AI DataMind 1.0 is primarily based on rule and pattern matching, incorporating knowledge-based reasoning, expert systems, and more. However, it still has limitations in handling complex and ambiguous problems. To overcome these limitations, the team of experts at SW Alliance sought new approaches to develop a more advanced AI system.

AI DataMind 2.0 was built upon version 1.0, integrating machine learning technologies. Machine learning enables AI systems to learn and improve their performance based on large datasets. Deep learning, in particular, allows the system to construct multi-layered neural networks that can extract higher-level features from data, leading to significant breakthroughs.

Building on version 2.0, AI DataMind 3.0 introduced more perceptive and adaptive capabilities. The system can now collect environmental data through data sensors and adjust its behavior and decisions based on this information. This feature makes AI DataMind more adaptable to different environments and tasks, positioning it as a real-world intelligent assistant.

AI DataMind 4.0, the latest development stage, focuses on the application of AI in the full spectrum of financial markets. Version 4.0 emphasizes the integration of artificial intelligence with technologies like the Internet of Things (IoT), cloud computing, and big data to create intelligent solutions.

The AI DataMind investment system comprises four major trading and investment frameworks:

1.Trading Signal Decision System: This system helps make subjective judgments by providing real-time buy and sell signals with an accuracy rate of over 90%.

2.AI Programmatic Trading System: This AI-driven system performs automated trades once parameters are set manually, ensuring stable and consistent profits.

3.Investment Strategy Decision System: This system uses big data analytics to assess mainstream investment projects across major markets and provide rating and decision-making analyses, particularly offering accurate investment strategies for emerging projects.

4.Expert and Investment Advisory System: A powerful investment advisory system composed of renowned experts, assisting premium users and future funds in making informed investment decisions and plans.

The future development aims to enhance these four systems to achieve the following investment outcomes:

Trading Signal Decision System: Improve subjective judgment and provide real-time buy/sell signals with an accuracy rate above 90%.

AI Programmatic Trading System: Enable automated trading that ensures stable profits after adjusting the parameters.

Investment Strategy Decision System: Provide big data analysis and rating decisions for key investment projects, especially for emerging sectors.

Expert and Investment Advisory System: Empower users with top-tier investment advice from a network of leading experts, enhancing decision-making and strategic planning.