A Fresh Perspective on Silicon-Based Intelligence
Modern AI is fraught with fundamental issues regarding transparency, traceability, resource The discussion highlights prevailing challenges in modern AI, encompassing transparency, traceability, resource allocation, and development expenses. Notably, approximately 70% of AI workflows involve data manipulation, aimed at refining the training process. This presentation introduces a unique data handling model that diminishes the need for extensive data cleaning and handling, leading to improved inference capabilities. Employing a proprietary equation-oriented and physics-based methodology, this model operates within data constraints rather than rigid dataset adaptations, ensuring data integrity and mitigating biases. It also offers enhanced traceability and transparency compared to existing AI models. The session encourages discourse on novel data approaches, contemporary AI concerns, and alternative viewpoints in data processing and analytics.