Author name: Isabella Agdestein

Neural chips, specialized hardware designed for AI, turbocharge processing speeds and efficiency, revolutionizing tasks like deep learning and real-time analytics. […]

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