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.
Updated 2 hours ago31 stories in the last 24 hours
9 stories
MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet. The story centres on Meta. Reported by Meta. Bharat Hunt files it under AI Hardware and AI Regulation — the section covering chips, accelerators, data centres, on-device inference and supply.
AI agents meant to replace Meta workers made “large-scale, disruptive actions”. The story centres on Meta. Reported by Ars Technica. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model. The story centres on Meta. Reported by Meta. Bharat Hunt files it under AI Models and AI Hardware — the section covering a new or updated model, its capabilities, benchmarks or availability.
How XPUs Meet a World-Class AI Factory. The story centres on Scale AI. Reported by NVIDIA. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models. The story centres on Microsoft. Reported by Microsoft Research. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
Q2D-Web: A Large-Scale Benchmark for Retrieval in Agentic RAG Systems. It centres on Benchmarks, and also names RAG and Hugging Face. 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.
How law firm Gilbert + Tobin governs and scales AI with OpenAI. It centres on OpenAI, and also names GPT. Reported by OpenAI. Bharat Hunt files it under Enterprise AI and AI Regulation — the section covering deployment inside businesses — platforms, adoption, cost, integration.
When Does Scale-Invariant Optimization Become Unstable? An Exact Schedule Law with Weight Decay. The story centres on GitHub. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Agents — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration. Open the original report for the full detail.
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.