In large language models (LLMs), the landscape of pretraining data is a rich blend of diverse sources. It spans from common English to less common languages, including casual conversations and scholarly texts, and even extends to modalities like images and speeches....

Developing and optimizing AI models requires significant work since developers frequently need help identifying the appropriate models for their particular requirements. Developing these AI solutions may be challenging and drawn out for open-source projects. Many...

From the transformative potential of Multimodal AI, which goes beyond traditional single-mode data processing to encompass multiple input types like text, images, and sound, to the emergence of Quantum AI, the trends shaping the future of AI are both exciting and...

Researchers from Lehigh University and Microsoft introduced a new multi-agent framework, Mora, to address the challenge of advancing video generation technology. While in recent years, there has been significant progress in image and text synthesis, video generation...

In an era where generative artificial intelligence (GenAI) is rapidly transforming the landscape of business and technology, the specter of misinformation—unintentionally generated by these powerful tools—looms large. Recognizing the critical need for reliability and...

Deep Neural Networks (DNNs) demonstrated tremendous improvement in numerous difficult activities, matching or even outperforming human ability. As a result of this accomplishment, DNNs were widely used in many safety- and security-critical applications, including...