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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200 stories
Optimizing cost and latency with Amazon Bedrock prompt caching. It centres on Amazon, and also names LangChain. Reported by AWS. Bharat Hunt files it under AI Tools — the section covering applications people use — assistants, editors, search, productivity.
Anthropic’s IPO filing reveals its strategy for keeping enterprise customers hooked. It centres on Anthropic, and also names Claude and Amazon. Reported by TechCrunch. Bharat Hunt files it under Enterprise AI and AI Funding — the section covering deployment inside businesses — platforms, adoption, cost, integration.
Announcing new ways to customize models with SageMaker AI, without managing GPUs. The story centres on 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.
Anthropic eyes $518 billion AI buildout; backed by 80% non-cancellable deals. It centres on Anthropic, and also names Google and Amazon. Reported by The Economic Times. Bharat Hunt files it under AI Funding and AI Startups — the section covering rounds, valuations, acquisitions and investor moves in AI.
How uniopen customized Amazon Nova to their retail moderation policies for production deployment. It centres on Amazon, and also names Nova and Fine-tuning. Reported by AWS. Bharat Hunt files it under Enterprise AI — the section covering deployment inside businesses — platforms, adoption, cost, integration.
CORDIAL: Calibrating Ordinal LLM Outputs from Few Labels. The story centres on Amazon. 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.
Beyond the KV cache: Training and serving i14’s Laplace 3B linear attention model on AWS Trainium2 with native PyTorch. It centres on Amazon, and also names PyTorch. Reported by AWS. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.
Google has joined Amazon in attacking Nvidia’s stronghold with AI app developers. It centres on Google, and also names Amazon and NVIDIA. Reported by TechCrunch. Bharat Hunt files it under AI Hardware and AI Coding — the section covering chips, accelerators, data centres, on-device inference and supply.
Configure the ChatGPT desktop app with Amazon Bedrock in AWS GovCloud (US). It centres on GPT, and also names Amazon and Inference. Reported by AWS. Bharat Hunt files it under AI Tools and AI Regulation — the section covering applications people use — assistants, editors, search, productivity.
How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway. It centres on Amazon, and also names Model Context Protocol. Reported by AWS. Bharat Hunt files it under AI Tools and AI Agents — the section covering applications people use — assistants, editors, search, productivity.
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.
How Eon built multi-cloud investigation with an MCP Gateway on Amazon Bedrock AgentCore. It centres on Model Context Protocol, and also names Amazon. Reported by AWS. Bharat Hunt files it under AI Agents and AI Coding — 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.