Raw and frequently unlabeled data can be retrieved and organized using representation learning. The ability of the model to develop a good representation depends on the quantity, quality, and diversity of the data. In doing so, the model mirrors the data’s inherent...

The challenge of efficiently searching and retrieving information in digital data has become more pronounced. Traditional search methods need help with vast amounts of unstructured data like images,  audio, videos, and text. This has led to a demand for a solution...

Neural View Synthesis (NVS) poses a complex challenge in generating realistic 3D scenes from multi-view videos, especially in diverse real-world scenarios. The limitations of current state-of-the-art (SOTA) NVS techniques become apparent when faced with variations in...

January 4, 2024: Microsoft, a big tech company, has changed its keyboards. They added a new AI key. This key lets people use Copilot, an AI tool, on new Windows 11 PCs. Copilot can do things like search, write emails, and make images. Microsoft has worked with OpenAI...

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Training these models, however, is challenging. The computational intensity required and the potential for various failures during...

Scientists traditionally examine tissues by analyzing the expression levels of genes in individual cells using a technique known as spatial transcriptomics (ST). Researchers gain insights into cells’ spatial organization and function by measuring the quantity of RNA...