In a revolutionary development set to transform artificial intelligence (AI), researchers at the Technical University of Munich (TU Munich) have pioneered a method that drastically accelerates the training of neural networks. Traditional neural network training is both time-consuming and
On April 14, 2025, an international drone racing event in Abu Dhabi marked a groundbreaking achievement in the field of artificial intelligence (AI) and robotics. For the first time, an autonomous drone decisively outperformed human pilots in a high-speed competitive race, heralding a new era in
Inephany, a promising AI startup based in London, has made significant strides with its innovative platform aimed at optimizing neural network training, particularly for large language models (LLMs). With a recent pre-seed funding round of $2.2 million led by Amadeus Capital Partners, alongside
AI is evolving rapidly and challenging long-held beliefs about the nature of intelligence. This progression necessitates a reexamination of human cognitive capabilities and their interplay with machine intelligence. As artificial intelligence continues to develop, its advancements compel both
Artificial Intelligence (AI) has transitioned from a mere concept in science fiction to a potent force reshaping present-day reality. At the heart of this transformation is Deep Learning, a sophisticated subset of AI that autonomously learns from data to improve its performance over time. This
In the rapidly evolving landscape of technology, MicroAlgo Inc. has made a remarkable breakthrough that promises to transform the way we handle and analyze vast amounts of data. By leveraging quantum neural networks and integrating them with Grover's algorithm, the company has achieved a
