Recursive Language Models aim to break the usual trade off between context length, accuracy and cost in large language models. Instead of forcing a ...

How do you convert complex, multilingual documents—dense layouts, small scripts, formulas, charts, and handwriting—into faithful structured Markdown/JSON with state-of-the-art accuracy while keeping ...

Kimi K2, launched by Moonshot AI in July 2025, is a purpose-built, open-source Mixture-of-Experts (MoE) model—1 trillion total parameters, with 32 billion active parameters per token. It’s trained ...

The year 2025 marks a turning point for Voice AI Agents, with technology reaching levels of naturalness, context-awareness, and commercial adoption that were unimaginable a decade ago. Powered by ...

Shobha is a data analyst with a proven track record of developing innovative machine-learning solutions that drive business value.

In this article we will analyze how Google, OpenAI, and Anthropic are productizing ‘agentic’ capabilities across computer-use control, tool/function calling, orchestration, governance, and enterprise ...

What is a weight sparse transformer? The models are GPT-2 style decoder only transformers trained on Python code. Sparsity is not added after training, it is enforced during optimization. After each ...

Although large language models (LLMs) have shown impressive capabilities when it comes to language processing, they are computationally expensive and require sophisticated hardware infrastructure. The ...

Agentic RAG combines the strengths of traditional RAG—where large language models (LLMs) retrieve and ground outputs in external context—with agentic decision-making and tool use. Unlike static ...

Hugging Face has just released AI Sheets, a free, open-source, and local-first no-code tool designed to radically simplify dataset creation and enrichment with AI. AI Sheets aims to democratize access ...

Orchestration Host routes across many servers/tools App-local chaining Agent/toolkit routes intents → operations ...