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 ago115 stories in the last 24 hours
171 stories
Code Comprehensor: Hierarchical Documentation and Cross-Modal Retrieval for Large Repositories. It centres on Model Context Protocol, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Agents — the section covering code generation, developer agents, IDEs and software engineering.
FrugalEvo: Towards Cost-Aware LLM-Guided Program Evolution. It centres on Benchmarks, and also names GPT. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
AutoCompact: Learning When to Compact Context in Long-Horizon Coding Agents. It centres on Fine-tuning, and also names Inference. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Turbo Harness: Instance-Adaptive Harness Optimization. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding — the section covering code generation, developer agents, IDEs and software engineering. Open the original report for the full detail.
Compact Documentation for Coding Agents: A Benchmark, an Optimizer, and Why It Does Not Transfer. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Research — the section covering code generation, developer agents, IDEs and software engineering.
AI coding startup ByteAsk raises $1 million from YC, Entrepreneur First. The story centres on ByteAsk. Reported by The Economic Times. Bharat Hunt files it under AI Coding and AI Startups, and tracks it as India coverage — the section covering code generation, developer agents, IDEs and software engineering.
Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark. It centres on Benchmarks, and also names Flux. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Research — the section covering code generation, developer agents, IDEs and software engineering.
RoboArchitect: Automating the Design of Robotic Agents with Persistent Memory. It centres on Benchmarks, and also names Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Green Code or Costly Code? Evaluating the Energy Costs of Iterative LLM-Based Code Optimizations. It centres on Benchmarks, and also names Inference and GPT. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Models — the section covering code generation, developer agents, IDEs and software engineering.
Meta now lets AI agents handle the boring parts of WhatsApp Business setup. It centres on Meta, and also names Model Context Protocol and Claude. Reported by TechCrunch. Bharat Hunt files it under AI Coding and AI Agents — the section covering code generation, developer agents, IDEs and software engineering.
Adaptive Skill Granularity for Coding Agents: Runtime Routing and Macro-to-Micro Recovery. Reported by arXiv. Bharat Hunt files it under AI Coding and AI Tools — the section covering code generation, developer agents, IDEs and software engineering. 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.