How it work
1. Data Collection and Preprocessing
Assemble AI systematically builds data sources to gather vast datasets from the complex cryptocurrency market. These datasets enable LLM (large language model) to provide insights based on the latest information. The real-time data collection process includes inputs from cryptocurrency exchanges, on-chain analytics, chain explorers, news media, forums, communities, and cryptocurrency data analysis firms. This raw data is highly refined using NLP techniques and TF-IDF analysis to be processed by the AI engine.
2. AI Data Search Engine
In the news analysis process, Assemble AI's data search engine utilizes advanced Natural Language Processing (NLP) techniques to extract key features from content and select appropriate data sources. It comprehensively queries and analyzes various types of data (e.g., natural language data, time-series data) to derive the optimal essential data. Additionally, it employs advanced approaches to incorporate supplementary data for areas not recognized by the LLM.
3. Insight Generation
Assemble AI uses the inference capabilities of trained models to provide highly customized insights. This includes news summaries, key content extraction, sentiment analysis, past case analysis and market predictions, ripple effect, and investment strategies. Insights are optimized by considering the latest market conditions to support decision-making in the complex cryptocurrency market.
4. Continuous Learning and Model Optimization
Assemble AI keeps its models up-to-date through continuous training and learning from new data, enabling rapid response to market changes. Regular performance evaluations and reliability reassessments of data sources are conducted to enhance insight accuracy and efficiency. Various optimization tasks are performed, ensuring the models remain well-tuned. This intelligent iterative learning process allows Assemble AI to generate adaptive insights that evolve with market conditions.
5. GPT-4o Integration
Assemble AI uses OpenAI's most advanced model, GPT-4o, as its core engine. GPT-4o has multimodal capabilities, allowing it to accept various inputs such as text, audio, images, and video, and generate outputs in multiple formats. This model can respond to audio inputs within 232 milliseconds, providing human-like interactions with an average response time of 320 milliseconds. Notably, its enhanced ability to process non-English text significantly contributes to Assemble AI's multilingual news services.
The integration of GPT-4o ensures the accuracy and reliability of the insights provided by Assemble AI. It reflects the rapid volatility of the cryptocurrency market in real-time, performing predictions and analyses based on the latest information, thereby helping market participants make quick and accurate decisions.
Conclusion
The operating principles of Assemble AI utilize GPT-4o as the core engine, encompassing stages of large-scale data set collection and preprocessing, AI data search engine, insight generation, and continuous learning and model optimization to provide insights to crypto market participants. In the complex and dynamic crypto market, Assemble AI breaks down information barriers and enhances the quality of decision-making for users by delivering the latest information and in-depth insights.
The core of this system is the real-time collection and analysis of reliable data by trained artificial intelligence. Continuous model optimization and user experience improvements ensure the sustainable development of the news agent, enhancing the future of the crypto market.
Assemble AI’s unique operation allows it to adapt to market changes and consistently offer valuable insights and services to all market participants. This ultimately improves information accessibility, and transparency, and enables more informed and effective decision-making in the cryptocurrency market.
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