Autonomous agents have emerged as a critical focus in machine learning research, especially in reinforcement learning (RL), as researchers work to develop systems that can handle diverse challenges independently. The core challenge lies in creating agents that show three key characteristics: generality in tackling various tasks, capability in achieving high performance, and autonomy in learning… →

Ischemic stroke (IS) is one of the leading causes of disability and mortality in the world. It is caused by blood clotting in the arteries leading to the brain. It is crucial to dissolve the clot within a specific period of about 4.5 hours to prevent it from reaching the brain and causing brain cell… →

Contrastive image and text models face significant challenges in optimizing retrieval accuracy despite their crucial role in large-scale text-to-image and image-to-text retrieval systems. While these models effectively learn joint embeddings through contrastive loss functions to align matching text-image pairs and separate non-matching pairs, they primarily optimize pretraining objectives like InfoNCE rather than downstream retrieval performance.… →

The landscape of AI research is experiencing significant challenges due to the immense computational requirements of large pre-trained language and vision models. Training even relatively modest models demand substantial resources; for instance, Pythia-1B requires 64 GPUs for three days, while RoBERTa needs 1,000 GPUs for a single day. This computational barrier affects academic laboratories, limiting… →

The advent of AI has revolutionized the landscape of graphic design. AI graphic design tools are reshaping the way designers work, offering unprecedented efficiency, creativity, and innovation. These tools can automate repetitive tasks, generate fresh ideas, and accelerate the design process, empowering designers to focus on higher-level creative endeavors. As the graphic design industry continues… →

Recurrent Neural Networks were the trailblazers in natural language processing and set the cornerstone for future advances. RNNs were simple in structure with their contextual memory and constant state size, which promised the capacity to handle long sequence tasks. While theoretically, the design of RNNS pledged to a great future in long context tasks, practically,… →

Foundation models show impressive capabilities across tasks and modalities, outperforming traditional AI approaches often task-specific and limited by modality. In medicine, however, developing such models faces challenges due to restricted access to diverse data and strict privacy laws. While capable in specific areas, existing medical foundation models need to be improved by their focus on… →

In today’s data-driven world, data analysts play a crucial role in various domains. Businesses use data extensively to inform strategy, enhance operations, and obtain a competitive edge. Professionals known as data analysts enable this by turning complicated raw data into understandable, useful insights that help in decision-making. They navigate the whole data analysis cycle, from… →