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I discovered the Himalayan Database a few weeks ago and decided to create a few “whimsical” visualizations based on this dataset. In two previous articles I…
Large language models (LLMs) have become a prominent force in the rapidly evolving landscape of artificial intelligence. These models, built primarily on Transformer architectures, have expanded…
With the growth of AI, large language models also began to be studied and used in all fields. These models are trained on vast amounts of…
Enhancing the receptive field of models is crucial for effective 3D medical image segmentation. Traditional convolutional neural networks (CNNs) often struggle to capture global information from…
On a scale from 1 to 10 how good are your data ingestion skills?Photo by Blake Connally on UnsplashData ingestion is a crucial step in data…
Numerous challenges underlying human-robot interaction exist. One such challenge is enabling robots to display human-like expressive behaviors. Traditional rule-based methods need more scalability in new social…
In the world of data and computer programs, the concept of Machine Learning might sound like a tough nut to crack, full of tricky math and…
In the dynamic field of Artificial Intelligence (AI), the trajectory from one foundational model to another has represented an amazing paradigm shift. The escalating series of…
Large-scale pre-trained vision-language models, exemplified by CLIP (Radford et al., 2021), exhibit remarkable generalizability across diverse visual domains and real-world tasks. However, their zero-shot in-distribution (ID)…
Large language models (LLMs) like GPT-4 require substantial computational power and memory, posing challenges for their efficient deployment. While sparsification methods have been developed to mitigate…