Artificial intelligence and machine learning are fields focused on creating algorithms to enable machines to understand data, make decisions, and solve problems. Researchers in this domain seek to design models that can process vast amounts of information efficiently and accurately, a crucial aspect in advancing automation and predictive analysis. This focus on the efficiency and… →
Neuro-Symbolic Artificial Intelligence (AI) represents an exciting frontier in the field. It merges the robustness of symbolic reasoning with the adaptive learning capabilities of neural networks. This integration aims to harness the strong points of symbolic and neural approaches to create more versatile and reliable AI systems. Below, Let’s explore key insights and developments from… →
Free LLM Playgrounds and Their Comparative Analysis As the landscape of AI technology advances, the proliferation of free platforms to test large language models (LLMs) online has greatly increased. These ‘playgrounds’ offer a valuable resource for developers, researchers, and enthusiasts to experiment with different models without requiring extensive setup or investment. Let’s explore a comparative… →
BACKGROUND: Pulmonary hypertension (PH) is a leading cause of death in patients with systemic sclerosis (SSc). An important component of SSc patient management is early detection and treatment of PH. Recently the threshold for the diagnosis of PH has been lowered to a mean pulmonary artery pressure (mPAP) threshold of > 20 mmHg on right… →
CONCLUSIONS: In non-diabetic early RA patients, the use of prednisone was not associated with developing hyperglycaemia or diabetes. However, high DAS increased the risk of diabetes. Potential risks associated with prednisone use may have been mitigated by its effect on DAS. →
Large language models (LLMs) are expanding in usage, posing new cybersecurity risks. These risks emerge from their core traits: heightened capability in code generation, heightened deployment for real-time code generation, automated execution within code interpreters, and integration into applications handling untrusted data. This poses the need for a robust mechanism for cybersecurity evaluations. Prior works… →
The advent of generative artificial intelligence (AI) marks a significant technological leap, enabling the creation of new text, images, videos, and other media by learning from vast datasets. However, this innovative capability brings forth substantial copyright concerns, as it may utilize and repurpose the creative works of original authors without consent. This research addresses the… →
Charts have become indispensable tools for visualizing data in information dissemination, business decision-making, and academic research. As the volume of multimodal data grows, a critical need arises for automated chart comprehension, which has garnered increasing attention from the research community. Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in comprehending images… →
Large Language Models (LLMs) signify a revolutionary leap in numerous application domains, facilitating impressive accomplishments in diverse tasks. Yet, their immense size incurs substantial computational expenses. With billions of parameters, these models demand extensive computational resources for operation. Adapting them to specific downstream tasks becomes particularly challenging due to their vast scale and computational requirements,… →