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Can a fully sovereign open reasoning model match state of the art systems when every part of its training pipeline is transparent. Researchers from Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) release K2 Think V2, a fully sovereign reasoning model designed to test how far open and fully documented pipelines can push long horizon […]
On Wednesday, China approved imports of Nvidia’s H200 artificial intelligence chips for three of its largest technology companies, Reuters reported. ByteDance, Alibaba, and Tencent received approval to purchase more than 400,000 H200 chips in total, marking a shift in Beijing’s stance after weeks of holding up shipments despite US export clearance. The move follows Beijing’s
Report: China approves import of high-end Nvidia AI chips after weeks of uncertainty Read More »
Python dominates AI and machine learning for one simple reason: its ecosystem is amazing. Most projects are built on a small set of libraries that handle everything from data loading to deep learning at scale. Knowing these libraries makes the entire development process fast and easy. Let’s break them down in a practical order. Starting
Top 10 Python Libraries for AI and Machine Learning Read More »
An open source AI assistant called Moltbot (formerly “Clawdbot”) recently crossed 69,000 stars on GitHub after a month, making it one of the fastest-growing AI projects of 2026. Created by Austrian developer Peter Steinberger, the tool lets users run a personal AI assistant and control it through messaging apps they already use. While some say
Users flock to open source Moltbot for always-on AI, despite major risks Read More »
Moonshot AI has released Kimi K2.5 as an open source visual agentic intelligence model. It combines a large Mixture of Experts language backbone, a native vision encoder, and a parallel multi agent system called Agent Swarm. The model targets coding, multimodal reasoning, and deep web research with strong benchmark results on agentic, vision, and coding
Data science agents should inspect datasets, design workflows, run code, and return verifiable answers, not just autocomplete Pandas code. DSGym, introduced by researchers from Stanford University, Together AI, Duke University, and Harvard University, is a framework that evaluates and trains such agents across more than 1,000 data science challenges with expert curated ground truth and
In this tutorial, we implement Tree-KG, an advanced hierarchical knowledge graph system that goes beyond traditional retrieval-augmented generation by combining semantic embeddings with explicit graph structure. We show how we can organize knowledge in a tree-like hierarchy that mirrors how humans learn, from broad domains to fine-grained concepts, and then reason across this structure using
Abhijit Nayak, Senior Data Scientist at Cognizant and IEEE conference speaker, discusses building production-grade information extraction systems for cancer research and why domain expertise matters more than model size. A July survey in Artificial Intelligence Review analyzed 156 NLP studies in oncology and identified a pattern: transformer models perform impressively on research benchmarks, then collapse
How Automated NLP Pipelines Cut Oncology Data Abstraction from Weeks to Hours Read More »
For decades, predicting the weather has been the exclusive domain of massive government supercomputers running complex physics-based equations. NVIDIA has shattered that barrier with the release of the Earth-2 family of open models and tools for AI weather and climate prediction accessible to virtually anyone, from tech startups to national meteorological agencies. In a move
StepFun has introduced Step-DeepResearch, a 32B parameter end to end deep research agent that aims to turn web search into actual research workflows with long horizon reasoning, tool use and structured reporting. The model is built on Qwen2.5 32B-Base and is trained to act as a single agent that plans, explores sources, verifies evidence and
