Anthropic today released Claude Sonnet 5, a new AI model that the company says delivers near-flagship performance at mid-tier prices — a move designed to give cost-conscious enterprise developers access to powerful agentic capabilities just as the San Francisco-based AI lab barrels toward an initial public offering that will test whether the private market’s staggering […]
A few hours ago, Chinese delivery app company Meituan officially unveiled LongCat-2.0 on GitHub, Hugging Face, and its native platform, unmasking the model as the computational engine behind “Owl Alpha,” the anonymous stealth model that has spent the last two months commanding global developer charts on OpenRouter. Developed to fundamentally disrupt closed-source enterprise dominance in
OpenClaw just released native companion apps for iOS and Android. The iOS app is listed as ‘OpenClaw – AI that does things.’ Both apps are free to download. They are not standalone chatbots. Each phone becomes a node in a self-hosted agent network. The assistant itself runs on a separate Gateway. That separation is the
In this tutorial, we build an advanced, Colab-ready workflow around PyGraphistry for interactive graph analytics and visualization. We start by creating a realistic enterprise-style access dataset, transforming it into nodes and edges, and enriching the graph with risk scores, anomaly indicators, centrality metrics, community detection, and layout embeddings. We then use PyGraphistry to bind graph
Even as the geopolitical conversation around AI continues to grow more fraught following the U.S. government’s actions to limit the new models from Anthropic and OpenAI, Chinese open source darling DeepSeek is back with yet another open release that could once again change AI development around the globe. Over the weekend, the firm released DSpark,
DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85% Read More »
AI scientists are becoming a new interface for scientific computing. These agents read papers, write code, generate hypotheses, call APIs, and inspect files. But science is not software engineering. No test suite turns green when a hypothesis is correct. Discovery stays iterative, uncertain, and grounded in the physical world. That gap is what NVIDIA is
In the past two years, businesses have been trying to fit large language models (LLMs) into support, analytics, development, and internal automation like never before. Along with the increasing adoption of AI technology, another trend is gaining momentum — cybercriminals are taking advantage of the disconnect between assumptions about LLMs and their actual characteristics. In
In this tutorial, we build an advanced, self-contained OCRmyPDF workflow. We start by installing the required system and Python dependencies, then create a synthetic image-only PDF for scanning so we can test OCR without relying on external files. From there, we use OCRmyPDF’s real public API to convert scanned documents into searchable PDFs, generate PDF/A
In this tutorial, we work with the Fable 5 Traces dataset from Hugging Face and build a complete workflow around real coding-agent trace data. We start by setting up a lightweight environment that avoids fragile dependencies such as datasets, scikit-learn, and scipy. Then we manually download and parse the merged JSONL file to keep the
Liquid AI shipped LFM2.5-230M, it’s the company’s smallest model to date. The release targets a specific job: running agentic tasks on phones, robots, and automation devices. Both the base and instruction-tuned checkpoints are open-weight on Hugging Face. The pitch is narrow on purpose. This is not a general reasoning model. It is built for data