Statistics has become increasingly vital in today’s data-driven world. With the growth of big data and advanced computing, statistics has evolved to tackle complex problems across various fields, including healthcare, finance, and technology. Modern statistical methods, coupled with machine learning and artificial intelligence, enable deeper insights and more accurate predictions, driving decision-making and innovation. This… →

The rapid advancement of AI has revolutionized various industries, from healthcare to finance, by enabling sophisticated data analysis and predictive modeling. However, the traditional approach to AI, which involves centralizing vast amounts of data for training models, raises significant privacy and security concerns. Federated learning has emerged as a promising field that addresses these issues… →

Artificial Intelligence is undergoing rapid evolution, especially regarding the training of massive language models (LLMs) with parameters exceeding 70 billion. These models have become indispensable for various tasks, including creative text generation, translation, and content creation. However, effectively harnessing the power of such advanced LLMs requires human input through a technique known as Reinforcement Learning… →

Large language models (LLMs) have recently become highly valuable tools in complicated reasoning tasks, language production, and human language interpretation. Since then, there has been a dramatic increase in funding for studies in this area, and both the number of models used and the amount of data used for training have grown substantially. This also… →

Vision-language models (VLMs), capable of processing both images and text, have gained immense popularity due to their versatility in solving a wide range of tasks, from information retrieval in scanned documents to code generation from screenshots. However, the development of these powerful models has been hindered by a lack of understanding regarding the critical design… →

The field of AI involves the development of systems that can do tasks requiring human intelligence. These tasks encompass a broad range, including language translation, speech recognition, and decision-making processes. Researchers in this domain are dedicated to creating advanced models and tools to process and analyze vast datasets efficiently.  A significant challenge in AI is… →

CRISPR-based genome editing technologies have revolutionized gene study and medical treatment by enabling precise DNA alterations. AI integration has enhanced these technologies’ precision, efficiency, and affordability, particularly for diseases like Sickle Cell Anemia and Thalassemia. AI models such as DeepCRISPR, CRISTA, and DeepHF optimize guide RNA (gRNA) design for CRISPR-Cas systems by considering factors like… →

Learning in simulation and applying the learned policy to the real world is a potential approach to enable generalist robots, and solve complex decision-making tasks. However, the challenge to this approach is to address simulation-to-reality (sim-to-real) gaps. Also, a huge amount of data is needed while learning to solve these tasks, and the load of… →