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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710 stories
One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars. It centres on Inference, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
TACO: Ternary Absolute-max Column-wise One-sparse Optimizer for LLM Fine-Tuning. The story centres on Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Hardware and AI Models — the section covering chips, accelerators, data centres, on-device inference and supply.
Comparison of techniques for fine-tuning open-weight models for entity extraction from radiology reports. It centres on Fine-tuning, and also names Gemma and GPT. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Models — the section covering open-weight models, permissive licences and community releases.
HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment. It centres on Inference, and also names Reasoning Models. Reported by arXiv. Bharat Hunt files it under Enterprise AI and AI Models — the section covering deployment inside businesses — platforms, adoption, cost, integration.
Telescopic Language Models. It centres on Nothing, and also names Inference and Perplexity. Reported by arXiv. 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.
Less Sycophancy, Stronger Refusal? Lessons for AI Safety from Mechanistic Interpretability. It centres on AI Safety, and also names Inference and Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Research and AI Funding — the section covering papers, benchmarks, evaluations, interpretability and safety results.
How Reproducible Are Evaluation Conclusions? A Self-Audit of LLM-Inferred Prompt Structure. It centres on Benchmarks, and also names Inference. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
PISCES: Physics-Informed Solar-wind Convolutional autoEncoder for Space-weather Anomaly Detection and Early Warning. The story centres on Inference. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Automattic’s 33-Hour Coup, and can AI labs police themselves? It centres on Anthropic, and also names Dario Amodei and NVIDIA. Reported by TechCrunch. Bharat Hunt files it under AI Hardware — the section covering chips, accelerators, data centres, on-device inference and supply.
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning. It centres on Reasoning Models, and also names Benchmarks and Inference. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Models — the section covering open-weight models, permissive licences and community releases.
Build a Physical AI model factory with NVIDIA Cosmos 3 on SageMaker HyperPod. It centres on NVIDIA, and also names Benchmarks and Amazon. Reported by AWS. Bharat Hunt files it under AI Hardware and AI Models — the section covering chips, accelerators, data centres, on-device inference and supply.
TextSeal2: Distortion-Free LLM Watermarking with Copula Mixing and Memoryless Races. The story centres on Inference. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
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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.