The latest AI news, launches, models, companies and research — collected from official sources, research feeds and reporting, grouped into stories and ranked by the BharatHunt Trend Score.
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533 stories
Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition. It centres on Benchmarks, and also names Claude Code. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
RECAST: Learning to Compute the Right Context through Adaptive Evidence Routing. It centres on RAG, and also names Fine-tuning and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Tools — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents. It centres on Benchmarks, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Coding — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS. It centres on NVIDIA, and also names Amazon and Multimodal. Reported by AWS. Bharat Hunt files it under AI Agents and AI Hardware — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
TeamGym: A Gym for Team Decision-Making by AI Agents with Distributed Information. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Gym-Anything-RT: Scaling Real-Time Environments for Vision-Language Agents. The story centres on GPT. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
SafeDiSTL: Decomposing Joint Constraints for Safe Multi-Agent Reinforcement Learning. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Research — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration. Open the original report for the full detail.
A Baseline Assessment for the Agentic Web Technology Stack. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Regulation — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
A Multi-Agent LLM System for Automated Tuning of Specialized Neural Network Models. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Models — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Beyond hours saved: Building the business case for agentic automation. Reported by AWS. Bharat Hunt files it under AI Agents and Enterprise AI — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration. Open the original report for the full detail.
Multi-Dimensional Matching. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Research — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration. Open the original report for the full detail.
ReCite: Agentic Reasoning for Faithful Citation. The story centres on Reliance Jio. Reported by arXiv. Bharat Hunt files it under AI Agents, and tracks it as India coverage — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Bharat Hunt links to original reporting and does not republish it. Headlines and links belong to their publishers; summaries and the trend ranking are ours. All AI stories
Stories in the last 24 hours, against the 24 before it. A change is shown only where the earlier window had enough coverage to compare against.
Our own 0-100 ranking, not an industry metric and not anyone else’s “trending” number. It combines how recently a story was covered (32%), how many independent publications covered it (28%), how fast that coverage is arriving right now (20%), how reliable those sources are (12%) and how many people opened the story (8%).
A story we cannot date carries no score at all rather than a made-up one, so some cards show no badge. Summaries are written by Bharat Hunt from the headline and the coverage — the original article is always the source of truth, and every link goes to the publisher.