​[[{“value”:” Graph Neural Network (GNN)–based motion planning has emerged as a promising approach in robotic systems for its efficiency in pathfinding and navigation tasks. This approach leverages GNNs to learn the underlying graph structure of an environment, enabling it to make quick and informed decisions… Read More »An Overview of Three Prominent Systems for Graph Neural Network-based Motion Planning Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Generic transport equations, comprising time-dependent partial differential equations (PDEs), delineate the evolution of extensive properties in physical systems, encompassing mass, momentum, and energy. Derived from conservation laws, they underpin comprehension of diverse physical phenomena, from mass diffusion to Navier–Stokes equations. Widely applicable across science… Read More »CMU Researchers Propose a Distributed Data Scoping Method: Revealing the Incompatibility between the Deep Learning Architecture and the Generic Transport PDEs Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In deep learning, especially in NLP, image analysis, and biology, there is an increasing focus on developing models that offer both computational efficiency and robust expressiveness. Attention mechanisms have been revolutionary, allowing for better handling of sequence modeling tasks. However, the computational complexity associated… Read More »Researchers at the University of Waterloo Introduce Orchid: Revolutionizing Deep Learning with Data-Dependent Convolutions for Scalable Sequence Modeling Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent years, the demand for AI and Machine Learning has surged, making ML expertise increasingly vital for job seekers. Additionally, Python has emerged as the primary language for various ML tasks. This article outlines the top ML courses in Python, offering readers the… Read More »Top Courses for Machine Learning with Python Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The surge in powerful Transformer-based language models (LMs) and their widespread use highlights the need for research into their inner workings. Understanding these mechanisms in advanced AI systems is crucial for ensuring their safety, and fairness, and minimizing biases and errors, especially in critical… Read More »Deciphering Transformer Language Models: Advances in Interpretability Research Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multitask learning (MLT) involves training a single model to perform multiple tasks simultaneously, leveraging shared information to enhance performance. While beneficial, MLT poses challenges in managing large models and optimizing across tasks. Optimizing the average loss may lead to suboptimal performance if tasks progress unevenly.… Read More »FAMO: A Fast Optimization Method for Multitask Learning (MTL) that Mitigates the Conflicting Gradients using O(1) Space and Time Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Language models built on Large Language models (LLMs) have been developed for multiple applications, followed by new advancements in enhancing LLMs. However, LLMs lack adaption and personalization to a particular user and task. Users often provide feedback to LLM-based agents through user edits and… Read More »CIPHER: An Effective Retrieval-based AI Algorithm that Infers User Preference by Querying the LLMs Sajjad Ansari Artificial Intelligence Category – MarkTechPost