AI in Embedded Systems: How AI Runs on Low-Power Devices
AI in embedded systems brings intelligence to low-power devices like wearables and IoT sensors, using optimized algorithms and hardware to […]
AI in embedded systems brings intelligence to low-power devices like wearables and IoT sensors, using optimized algorithms and hardware to […]
Multi-agent systems (MAS) leverage AI to enable autonomous agents to interact, collaborate, and solve complex problems, from traffic management to
Adversarial attacks exploit vulnerabilities in AI systems by introducing subtle manipulations, like altered images or data, to trick models into
Unsupervised learning enables AI to uncover hidden patterns in data without human guidance, using techniques like clustering and dimensionality reduction.
TL;DR Uncertainty in AI is a critical challenge – AI models often make confident predictions even when they could be
As Artificial Intelligence (AI) models grow in complexity, ensuring their accuracy and reliability becomes increasingly challenging. AI debugging is the
As Artificial Intelligence (AI) models grow in complexity and scale, their energy consumption has become a significant concern. Training and
Real-time AI processing is revolutionizing industries by enabling instant decision-making and responsiveness in applications like autonomous vehicles, healthcare, and customer
As Artificial Intelligence (AI) continues to evolve, the need for efficient and scalable training methods has become increasingly important. Self-supervised
Introduction Federated Learning (FL) represents a transformative approach to machine learning, enabling collaborative model training across decentralized data sources while