Large Language Models (LLMs) have become pivotal in artificial intelligence, powering a variety of applications from chatbots to content generation tools. However, their deployment at scale presents notable challenges. High computational costs, latency, and energy consumption often limit their wider use. Organizations face the difficulty of balancing high throughput with reasonable operating expenses. Additionally, as…
Have you ever admired how smartphone cameras isolate the main subject from the background, adding a subtle blur to the background based on depth? This “portrait mode” effect gives photographs a professional look by simulating shallow depth-of-field similar to DSLR cameras. In this tutorial, we’ll recreate this effect programmatically using open-source computer vision models, like…
Lexicon-based embeddings are one of the good alternatives to dense embeddings, yet they face numerous challenges that restrain their wider adoption. One key problem is tokenization redundancy, whereby subword tokenization breaks semantically equivalent tokens, causing inefficiencies and inconsistencies in embeddings. The other limitation of causal LLMs is unidirectional attention; this means tokens cannot fully leverage…
Large Language Models (LLMs) have made significant progress in natural language processing, excelling in tasks like understanding, generation, and reasoning. However, challenges remain. Achieving robust reasoning often requires extensive supervised fine-tuning, which limits scalability and generalization. Furthermore, issues like poor readability and balancing computational efficiency with reasoning complexity persist, prompting researchers to explore new approaches.…
AI and ML are expanding at a remarkable rate, which is marked by the evolution of numerous specialized subdomains. Recently, two core branches that have become central in academic research and industrial applications are Generative AI and Predictive AI. While they share foundational principles of machine learning, their objectives, methodologies, and outcomes differ significantly. This…
Large language models rely heavily on open datasets to train, which poses significant legal, technical, and ethical challenges in managing such datasets. There are uncertainties around the legal implications of using data based on varying copyright laws and changing regulations regarding safe usage. The lack of global standards or centralized databases to validate and license…
Traditional psychological counseling, often conducted in person, remains limited to individuals actively seeking help for psychological concerns. In contrast, online automated counseling presents a viable option for those hesitant to pursue therapy due to stigma or shame. Cognitive Behavioral Therapy (CBT), a widely practiced approach in psychological counseling, aims to help individuals identify and correct…
The automation of radiology report generation has become one of the significant areas of focus in biomedical natural language processing. This is driven by the vast and exponentially growing medical imaging data and a dependency on highly accurate diagnostic interpretation in modern health care. Advancements in artificial intelligence make image analysis combined with natural language…
Reconstructing unmeasured causal drivers of complex time series from observed response data represents a fundamental challenge across diverse scientific domains. Latent variables, including genetic regulators or environmental factors, are essential to determining a system’s dynamics but are rarely measured. Challenges with current approaches arise from data noise, the systems’ high dimensionality, and existing algorithms’ capacities…
Generative models have revolutionized fields like language, vision, and biology through their ability to learn and sample from complex data distributions. While these models benefit from scaling up during training through increased data, computational resources, and model sizes, their inference-time scaling capabilities face significant challenges. Specifically, diffusion models, which excel in generating continuous data like…