​[[{“value”:” The development of effective AI models is crucial in deep learning research, but finding optimal model architectures remains challenging and costly. Traditional manual and automated approaches often fail to expand design possibilities beyond basic architectures like Transformers or hybrids, and the high cost of… Read More »Liquid AI Introduces STAR: An AI Framework for the Automated Evolution of Tailored Architectures Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In today’s world, large language models have shown great performance on various tasks and demonstrated different reasoning capabilities. This is important for advancing Artificial General Intelligence (AGI) and its use in robotics and navigation. Spatial reasoning includes quantitative aspects (e.g., distances, angles) and qualitative… Read More »This AI Paper Proposes a Novel Neural-Symbolic Framework that Enhances LLMs’ Spatial Reasoning Abilities Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Artificial intelligence has been progressively transforming with domain-specific models that excel in handling tasks within specialized fields such as mathematics, healthcare, and coding. These models are designed to enhance task performance and resource efficiency. However, integrating such specialized models into a cohesive and versatile… Read More »MoDEM (Mixture of Domain Expert Models): A Paradigm Shift in AI Combining Specialized Models and Intelligent Routing for Enhanced Efficiency and Precision Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Universities face intense global competition in the contemporary academic landscape, with institutional rankings increasingly tied to the United Nations’ Sustainable Development Goals (SDGs) as a critical social impact assessment benchmark. These rankings significantly influence crucial institutional parameters such as funding opportunities, international reputation, and… Read More »Contextual SDG Research Identification: An AI Evaluation Agent Methodology Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Building large language model (LLM)-powered applications for real-world production scenarios is challenging. Developers often face issues such as inconsistent responses from models, difficulties in ensuring robustness, and a lack of strong type safety. When building applications that leverage LLMs, the goal is to provide… Read More »Meet PydanticAI: A New Python-based Agent Framework to Build Production-Grade LLM-Powered Applications Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The static knowledge base and hallucination-creating inaccuracy or fabrication of information are two common issues with large language models (LLMs). The parametric knowledge within LLMs is inherently static, making it challenging to provide up-to-date information in real-time scenarios. Retrieval-augmented generation (RAG) addresses the problem… Read More »DMQR-RAG: A Diverse Multi-Query Rewriting Framework Designed to Improve the Performance of Both Document Retrieval and Final Responses in RAG Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The development of machine learning (ML) models for scientific applications has long been hindered by the lack of suitable datasets that capture the complexity and diversity of physical systems. Many existing datasets are limited, often covering only small classes of physical behaviors. This lack… Read More »Polymathic AI Releases ‘The Well’: 15TB of Machine Learning Datasets Containing Numerical Simulations of a Wide Variety of Spatiotemporal Physical Systems Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post is co-written with Abhishek Sawarkar, Eliuth Triana, Jiahong Liu and Kshitiz Gupta from NVIDIA.  At re:Invent 2024, we are excited to announce new capabilities to speed up your AI inference workloads with NVIDIA accelerated computing and software offerings on Amazon SageMaker. These… Read More »Speed up your AI inference workloads with new NVIDIA-powered capabilities in Amazon SageMaker Abhishek Sawarkar AWS Machine Learning Blog

​[[{“value”:” Today at AWS re:Invent 2024, we are excited to announce a new feature for Amazon SageMaker inference endpoints: the ability to scale SageMaker inference endpoints to zero instances. This long-awaited capability is a game changer for our customers using the power of AI and… Read More »Unlock cost savings with the new scale down to zero feature in SageMaker Inference Marc Karp AWS Machine Learning Blog

​[[{“value”:” Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI  models for inference. This innovation allows you to scale your models faster, observing up to 56%… Read More »Supercharge your auto scaling for generative AI inference – Introducing Container Caching in SageMaker Inference Wenzhao Sun AWS Machine Learning Blog