The digital age constantly demands faster and more efficient computing models. As silicon-based technology nears its physical limits, researchers are avidly exploring new materials and methods. A groundbreaking discovery in the field of 2D magnets paves the way for miniaturized, high-performance
Artificial Intelligence (AI) has become the cornerstone of innovation across the technology sector. However, the rapid expansion of AI capabilities comes with a steep increase in energy consumption and carbon emissions, posing a substantial challenge for tech companies striving to meet their
Artificial intelligence (AI) offers significant advancements in healthcare, but its environmental impact cannot be ignored. The combination of massive data processing and intensive computational needs can lead to a considerable carbon footprint within the healthcare industry. The urgency to address
The discussion anchored by Rob Nelson and Rahul Mewawalla, CEO and President of Mawson Infrastructure Group, on the complexities of artificial intelligence (AI) sheds light on its significant impact and energy demands. Nelson clarifies that AI, which mimics human intelligence, extends beyond
Advancements in artificial intelligence (AI) and machine learning continue to push the boundaries of what's possible, but traditional artificial neural networks (ANNs) are hitting a wall when it comes to energy efficiency and mimicking complex human brain mechanisms. Neuromorphic computing,
China has made a monumental leap in AI chip technology with the development of the Taichi-II optical AI chip, designed by scientists from Beijing. This groundbreaking chip, which relies entirely on light for its computations, has significantly outperformed Nvidia's #00 GPU in energy
