Traditional approaches to training language models heavily rely on supervised fine-tuning, where models learn by imitating correct responses. While effective for basic tasks, this method limits a model’s ability to develop deep reasoning skills. As artificial intelligence applications continue to evolve, there is a growing demand for models that can generate responses and critically evaluate… →

The fast development of wireless communication technologies has increased the application of automatic modulation recognition (AMR) in sectors such as cognitive radio and electronic countermeasures. With their various modulation types and signal changes, modern communication systems provide significant obstacles to preserving AMR performance in dynamic contexts.  Deep learning-based AMR algorithms have emerged as the leading… →

Modeling biological and chemical sequences is extremely difficult mainly due to the need to handle long-range dependencies and efficient processing of large sequential data. Classical methods, particularly Transformer-based architectures, are limited by quadratic scaling in sequence length and are computationally expensive for processing long genomic sequences and protein modeling. Moreover, most existing models have in-context… →

Artificial Neural Networks (ANNs) have their roots established in the inspiration developed from biological neural networks. Although highly efficient, ANNs fail to embody the neuronal structures in their architects truly. ANNs rely on vast training parameters, which lead to their high performance, but they consume a lot of energy and are prone to overfitting. Due… →

In this tutorial, we’ll build a powerful, PDF-based question-answering chatbot tailored for medical or health-related content. We’ll leveRAGe the open-source BioMistral LLM and LangChain’s flexible data orchestration capabilities to process PDF documents into manageable text chunks. We’ll then encode these chunks using Hugging Face embeddings, capturing deep semantic relationships and storing them in a Chroma… →

Protecting user data while enabling advanced analytics and machine learning is a critical challenge. Organizations must process and analyze data without compromising privacy, but existing solutions often struggle to balance security with functionality. This creates barriers to innovation, limiting collaboration and the development of privacy-conscious technologies. A solution that ensures transparency minimizes data exposure, preserves… →