The field of AI involves the development of systems that can do tasks requiring human intelligence. These tasks encompass a broad range, including language translation, speech recognition, and decision-making processes. Researchers in this domain are dedicated to creating advanced models and tools to process and analyze vast datasets efficiently. A significant challenge in AI is…
CRISPR-based genome editing technologies have revolutionized gene study and medical treatment by enabling precise DNA alterations. AI integration has enhanced these technologies’ precision, efficiency, and affordability, particularly for diseases like Sickle Cell Anemia and Thalassemia. AI models such as DeepCRISPR, CRISTA, and DeepHF optimize guide RNA (gRNA) design for CRISPR-Cas systems by considering factors like…
Learning in simulation and applying the learned policy to the real world is a potential approach to enable generalist robots, and solve complex decision-making tasks. However, the challenge to this approach is to address simulation-to-reality (sim-to-real) gaps. Also, a huge amount of data is needed while learning to solve these tasks, and the load of…
Reinforcement Learning (RL) has gained substantial traction over recent years, driven by its successes in complex tasks such as game playing, robotics, & autonomous systems. However, deploying RL in real-world applications necessitates addressing safety concerns, which has led to the emergence of Safe Reinforcement Learning (Safe RL). Safe RL aims to ensure that RL algorithms…
In recent years, computer vision has made significant strides by leveraging advanced neural network architectures to tackle complex tasks such as image classification, object detection, and semantic segmentation. Transformative models like Transformers and Convolutional Neural Networks (CNNs) have become fundamental tools, driving substantial improvements in visual recognition performance. These advancements have paved the way for…
Large language models (LLMs), particularly Generative Pre-trained Transformer (GPT) models, have demonstrated strong performance across various language tasks. However, challenges persist in their decoder architecture, Specifically in time-to-first-token (TTFT) and time-per-output token (TPOT). TTFT, reliant on extensive user context, and TPOT, for rapid subsequent token generation, have spurred research into memory-bound solutions like sparsification and…
Hugging Face has recently introduced LeRobot, a machine learning (ML) model created especially for practical robotics use. LeRobot provides an adaptable platform with an extensive library for advanced model training, data visualization, and sharing. This release represents a major advancement in the goal of increasing robots’ usability and accessibility for a broad spectrum of users.…
In natural language processing (NLP), researchers constantly strive to enhance language models’ capabilities, which play a crucial role in text generation, translation, and sentiment analysis. These advancements necessitate sophisticated tools and methods for evaluating these models effectively. One such innovative tool is Prometheus-Eval. Prometheus-Eval is a repository that provides tools for training, evaluating, and using…
Leveraging advanced computational techniques in physical sciences has become vital for accelerating scientific discovery. This involves integrating large language models (LLMs) and simulations to enhance hypothesis generation, experimental design, and data analysis. Automating these processes aims to streamline and democratize access to cutting-edge research tools, pushing the boundaries of scientific knowledge and improving efficiency across…
While significant strides have been made in predicting static protein structures, understanding protein dynamics, influenced by ligands, is essential for grasping protein function and advancing drug discovery. Traditional docking methods often treat proteins as rigid, limiting their accuracy. Although molecular dynamics simulations can suggest relevant protein conformations, they are computationally intensive. Recent advances, such as…