​[[{“value”:” The growing reliance on video data in machine learning applications has exposed several challenges in video decoding. Extracting meaningful frames or sequences efficiently and in formats suitable for model training often requires complex workflows. Traditional pipelines can be slow, resource-intensive, and cumbersome to integrate… Read More »PyTorch Introduces torchcodec: A Machine Learning Library for Decoding Videos into PyTorch Tensors Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” As artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) become central to innovation across industries, they also bring challenges that cannot be ignored. These workloads demand powerful computing resources, efficient memory management, and well-optimized software to make the most of the hardware.… Read More »AMD Releases AMD ROCm 6.3: An Open-Source Platform with Advanced Tools and Optimizations to Enhance AI, ML, and HPC Workloads Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models have made impressive strides in understanding natural language, solving programming tasks, and tackling reasoning challenges. However, their high computational costs and dependence on large-scale datasets bring their own set of problems. Many of these datasets lack the variety and depth needed… Read More »Microsoft AI Introduces Phi-4: A New 14 Billion Parameter Small Language Model Specializing in Complex Reasoning Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Diffusion models are closely linked to imitation learning because they generate samples by gradually refining random noise into meaningful data. This process is guided by behavioral cloning, a common imitation learning approach where the model learns to copy an expert’s actions step by step.… Read More »This AI Paper Introduces A Maximum Entropy Inverse Reinforcement Learning (IRL) Approach for Improving the Sample Quality of Diffusion Generative Models Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Drug-induced toxicity is a major challenge in drug development, contributing significantly to the failure of clinical trials. While efficacy issues account for most failures, safety concerns are the second leading cause, at 24%. Toxicities can affect various organ systems, including the heart, liver, kidneys,… Read More »Researchers at Stanford Introduce UniTox: A Unified Dataset of 2,418 FDA-Approved Drugs with Drug-Induced Toxicity Summaries and Ratings Created by Using GPT-4o to Process FDA Drug Labels Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The ongoing advancement in artificial intelligence highlights a persistent challenge: balancing model size, efficiency, and performance. Larger models often deliver superior capabilities but require extensive computational resources, which can limit accessibility and practicality. For organizations and individuals without access to high-end infrastructure, deploying multimodal… Read More »Meet Ivy-VL: A Lightweight Multimodal Model with Only 3 Billion Parameters for Edge Devices Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In Part 1 of this series, we introduced the newly launched ModelTrainer class on the Amazon SageMaker Python SDK and its benefits, and showed you how to fine-tune a Meta Llama 3.1 8B model on a custom dataset. In this post, we look at… Read More »Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 2: ModelBuilder Durga Sury AWS Machine Learning Blog

​[[{“value”:” Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK (SageMaker Core) provides access to… Read More »Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 1: ModelTrainer Durga Sury AWS Machine Learning Blog

​[[{“value”:” We are excited to announce new features that allow creation of more powerful apps, while giving more governance control using Amazon Q Apps, a capability within Amazon Q Business that allows you to create generative AI-powered apps based on your organization’s data. These features… Read More »Amazon Q Apps supports customization and governance of generative AI-powered apps Tiffany Myers AWS Machine Learning Blog

​[[{“value”:” Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. A large portion of that information is found in text narratives stored in various document… Read More »Answer questions from tables embedded in documents with Amazon Q Business Jiten Dedhia AWS Machine Learning Blog