👉 Stroke computing is an innovative approach to artificial intelligence and machine learning that focuses on processing information in discrete, time-based "strokes" rather than continuous data streams. This method mimics the way the human brain processes sensory information, where neurons fire in bursts or "strokes" rather than constantly. In stroke computing, computations are performed at these discrete time intervals, allowing for efficient and parallel processing of data. This approach can significantly reduce computational complexity and energy consumption, making it particularly suitable for edge devices with limited resources. By aligning computation more closely with the natural timing of neural activity, stroke computing enhances real-time processing capabilities and improves the efficiency of AI models in applications like robotics, autonomous vehicles, and wearable technology.
