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An Internet of AI Agents? Coral Protocol Introduces Coral v1: An MCP-Native Runtime and Registry for Cross-Framework AI Agents Coral Protocol has launched Coral v1, an agent stack designed to standardize the discovery, composition, and operation of AI agents across various frameworks. This release focuses on a Model Context Protocol (MCP)-based runtime, known as Coral…
«`html A Coding Guide to End-to-End Robotics Learning with LeRobot: Training, Evaluating, and Visualizing Behavior Cloning Policies on PushT Understanding the Target Audience The audience for this tutorial primarily includes data scientists, machine learning engineers, and robotics developers who are looking to implement behavior cloning policies within their robotic systems. Their pain points often revolve…
xAI Launches Grok-4-Fast: Unified Reasoning and Non-Reasoning Model with 2M-Token Context xAI has introduced Grok-4-Fast, a cost-optimized successor to Grok-4 that integrates “reasoning” and “non-reasoning” behaviors into a single model. This model is designed to enhance high-throughput search, coding, and Q&A applications, featuring a 2M-token context window and native tool-use reinforcement learning (RL) that determines…
Xiaomi Released MiMo-Audio, a 7B Speech Language Model Trained on 100M+ Hours with High-Fidelity Discrete Tokens Understanding the Target Audience The target audience for Xiaomi’s MiMo-Audio includes AI researchers, developers, and business leaders in the tech industry. These individuals are typically engaged in the fields of machine learning, natural language processing, and audio technology. Their…
Run MATLAB-Style Code Inside Python by Connecting Octave with the oct2py Library In this tutorial, we explore how to seamlessly run MATLAB-style code inside Python by connecting Octave with the oct2py library. We will set up the environment on Google Colab, exchange data between NumPy and Octave, write and call .m files, visualize plots generated…
Google’s Sensible Agent: Reframing Augmented Reality (AR) Assistance Understanding the Target Audience The target audience for Google’s Sensible Agent includes business professionals, developers, and researchers interested in augmented reality (AR) and artificial intelligence (AI). Their pain points often revolve around inefficient interaction modalities in AR environments, particularly in scenarios where hands and eyes are occupied.…
«`html Top Computer Vision CV Blogs & News Websites (2025) In 2025, computer vision technology has evolved significantly, spurred on by new multimodal backbones, larger open datasets, and tighter model-systems integration. This progress necessitates reliable sources that publish rigorously and provide practical resources such as reproducible code paths and deployment patterns. Here’s a curated list…
«`html Understanding the Target Audience for Qwen3-ASR-Toolkit The target audience for the Qwen3-ASR-Toolkit primarily consists of software developers, data scientists, and business analysts who require efficient audio transcription solutions. These professionals often work in industries such as media, education, and corporate communications, where accurate and timely transcription of long audio files is critical. Pain Points…
«`html Physical AI: Bridging Robotics, Material Science, and Artificial Intelligence for Next-Gen Embodied Systems What Do We Mean by “Physical AI”? Artificial intelligence in robotics is not just a matter of clever algorithms. Robots operate in the physical world, and their intelligence emerges from the co-design of body and brain. Physical AI describes this integration,…
«`html Building AI Agents: 5% AI and 100% Software Engineering The development of production-grade AI agents hinges more on software engineering than on the AI models themselves. Key aspects such as data plumbing, controls, and observability are critical for success. This article explores the essential components of a doc-to-chat pipeline and how to integrate AI…