🤖AI Predictions

QuickPrediction integrates an AI-powered prediction tool using TensorFlow.js to assist users with market analysis. By analyzing historical price data, the AI predicts the likelihood of MATIC prices going UP or DOWN in the following round. These insights can be used to enhance decision-making.

How the AI Works

1. Training Process

• The AI uses TensorFlow.js, a machine learning library, running entirely in the browser.

• It analyzes the most recent 20 rounds of price data points to identify historical trends and patterns.

• Based on these patterns, the AI computes probabilities for whether the price of MATIC will move UP or DOWN during the next round.

2. Displaying Probabilities

• The AI outputs probabilities in a user-friendly format, such as “65% UP, 35% DOWN.”

• These probabilities are displayed on the platform dashboard, providing users with a quick and easy way to gauge potential outcomes.

• While helpful, these probabilities are not guarantees and should be considered as advisory tools rather than definitive answers.

3. Local Execution for Transparency

• The AI model runs entirely on the user’s browser using client-side TensorFlow.js, meaning no data is processed or stored on external servers.

• This approach ensures user privacy while allowing the predictive algorithms to execute directly on the user's device.

4. Inspecting the AI Process

• Users can view the learning process and the AI model's operations in real time using the browser’s developer console.

• This provides technically curious users with full visibility into how the AI computes its predictions, adding a layer of transparency.

Important Notes on AI Predictions

• The AI is designed to offer supplementary guidance and is not guaranteed to be fully accurate. Users should rely on their analysis as well.

• While the AI updates predictions in real time with the latest price data, it may not account for unexpected market volatility or external macroeconomic factors.