Quantum Machine Learning (QML) is pushing the boundaries of artificial intelligence, merging quantum mechanics with advanced algorithms to tackle complex problems with unmatched efficiency. Sunny Guntuka,

FinTech Magazine looks at how generative AI and machine learning are transforming financial services as we head into

Nikhil Suryawanshi is a distinguished expert in machine learning, artificial intelligence, and data engineering. He has significantly contributed to advancing these fields. Throughout his career, Nikhil has been pivotal in the planning and design of systems that utilize machine learning algorithms and AI applications to tackle intricate challenges and enhance data processing workflows.

Combining quantum science with machine learning has led to a model that can accurately measure how surfaces feel to the touch.

For technology leaders, integrating AI copilots is an exciting opportunity, but it also needs careful planning to integrate with existing systems and tools.

AI models use deep learning techniques to analyze patterns in data and generate human-like text based on a user prompt or a given input. Key applications in text generation and understanding include the use of LLMs for translating languages, applying sentiment analysis for social media monitoring, and text summarization for document reviews.

Learn about the five key machine learning approaches outlined in the best selling AI book, The Master Algorithm, and their use cases in the field of cybersecurity. The post Machine Learning in Cyber Security: Harnessing the Power of Five AI Tribes appeared first on D3 Security.

GPUs are crucial for high-performance applications, including gaming, 3D rendering, video editing, cryptocurrency mining, artificial intelligence, and machine learning.

Machines can now beat us at chess, create art, and even diagnose diseases. Yet, for all its capabilities, artificial intelligence (AI) is not artificial humanity. It lacks our capacity for imagination, critical thinking, and emotional intelligence .

In this article, I share findings from my two decades of automation experience that landed me at the helm of the most impactful application of GenAI technologies today.

Every day, researchers at the Department of Energy's SLAC National Accelerator Laboratory tackle some of the biggest questions in science and technology—from laying the foundations for new drugs to developing new battery materials and solving big data challenges associated with particle physics and cosmology.

Learn how AI and ML will help detect, classify, and identify RF signals in an increasingly crowded EM spectrum.