​[[{“value”:” AI agents are transforming enterprise applications across industries, from customer service to complex decision workflows. As organizations scale these deployments, they face a fundamental question: how can you improve trust in an AI application? The challenge is transparency. AI agents can make decisions on… Read More »Build trustworthy AI agents with Amazon Bedrock AgentCore Observability Ishan Singh Artificial Intelligence

​Large language models (LLMs) have rapidly integrated into our daily workflows. Large language models (LLMs) have rapidly integrated into our daily workflows.  Read More  

​[[{“value”:” Anyone who’s used AI to generate code has seen it make mistakes. But the real danger isn’t the occasional wrong answer; it’s in what happens when those errors pile up across a codebase. Issues that seem small at first can compound quickly, making code… Read More »Building AI-Resistant Technical Debt Andrew Stellman AI & ML – Radar

​[[{“value”:” Baidu AI Research team has just released ERNIE-4.5-21B-A3B-Thinking, a new reasoning-focused large language model designed around efficiency, long-context reasoning, and tool integration. Being part of the ERNIE-4.5 family, this model is a Mixture-of-Experts (MoE) architecture with 21B total parameters but only 3B active parameters… Read More »Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A team of researchers from MBZUAI’s Institute of Foundation Models and G42 released K2 Think, is a 32B-parameter open reasoning system for advanced AI reasoning. It pairs long chain-of-thought supervised fine-tuning with reinforcement learning from verifiable rewards, agentic planning, test-time scaling, and inference optimizations… Read More »MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” As generative AI continues to transform how enterprises operate—and develop net new innovations—the infrastructure demands for training and deploying AI models have grown exponentially. Traditional infrastructure approaches are struggling to keep pace with today’s computational requirements, network demands, and resilience needs of modern AI… Read More »Powering innovation at scale: How AWS is tackling AI infrastructure challenges Barry Cooks Artificial Intelligence

​[[{“value”:” As organizations scale their AI infrastructure to support trillion-parameter models, they face a difficult trade-off: reduced training time with lower cost or faster training time with a higher cost. When they checkpoint frequently to speed up recovery time and minimize lost training time, they… Read More »Accelerate your model training with managed tiered checkpointing on Amazon SageMaker HyperPod Paulo Aragão Artificial Intelligence

​The increasing sophistication of cyber threats calls for a systemic change in the way we defend ourselves against them. The increasing sophistication of cyber threats calls for a systemic change in the way we defend ourselves against them.  Read More  

​When building machine learning models to classify imbalanced data — i. When building machine learning models to classify imbalanced data — i.  Read More