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H Company has unveiled Holo4, a groundbreaking series of AI models that can operate interfaces by clicking and typing, generate code, and invoke tools or APIs across desktop, web and Android environments. Holo4 is offered in two configurations—Holo4 27B (dense) and Holo4 35B-A3B (Mixture of Experts with 3B active parameters)—both supporting a 256K token context

Google Cloud AI Research, in collaboration with UNC-Chapel Hill, Stanford and Washington University in St. Louis, has open-sourced RRSI (Regularized Recursive Self-Improvement). This framework enables a language model agent to iteratively refine its own harness—prompts, tools, memory, control flow and sub-agents—while keeping model weights unchanged and preventing overfitting to the evolve set. Availability: Released under

Overview of the 2026 Physical AI Awards Once your AI-infused hardware is deployed in real-world settings, computational challenges multiply: data streams arrive faster than teams can label, every retraining cycle demands strict validation before shipping, and sim-to-real transitions become formal release workflows. Nebius crafted the 2026 Physical AI Awards for startups that have launched a

Our earlier guide to Top AI Coding Agents and Development Platforms explained each agent’s capabilities and use cases. This article, however, is tailored for procurement managers, legal counsel and security teams. Before approving any implementation, these stakeholders focus on four key queries: Who covers IP claims arising from AI-generated code? Where and how long are

Our comprehensive guide to leading AI coding agents detailed each tool’s functions and ideal use cases. This article is crafted for procurement leads, general counsel, and security reviewers charged with enterprise rollouts. Key questions to address before adoption: Who indemnifies generated code if an IP infringement claim arises? Where are prompts and inputs stored, and