Data labeling involves annotating raw data, such as images, text, audio, or video, with tags or labels that convey meaningful...
AI Investing
Artificial intelligence (AI) models have made substantial progress over the last few years, but they continue to face critical challenges,...
Large-sample hydrology is a critical field that addresses pressing global challenges, such as climate change, flood prediction, and water resource...
The proliferation of websites across various domains of everyday life has led to a significant rise in cybersecurity threats. The...
Automated software engineering (ASE) has emerged as a transformative field, integrating artificial intelligence with software development processes to tackle debugging,...
The rapid expansion of data in today’s era has brought with it both possibilities and difficulties. Businesses handle and use...
Large Language Models (LLMs) have advanced exponentially since the last decade. However, LLMs still need to improve regarding deployment and...
Foundation models (FMs) and large language models (LLMs) are revolutionizing AI applications by enabling tasks such as text summarization, real-time...
Machine learning (ML) has revolutionized wireless communication systems, enhancing applications like modulation recognition, resource allocation, and signal detection. However, the...
Self-supervised learning on offline datasets has permitted large models to reach remarkable capabilities both in text and image domains. Still,...
