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Meet OpenViking: An Open-Source Context Database that Brings Filesystem-Based Memory and Retrieval to AI Agent Systems like OpenClaw

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Databases, Editors Pick, New Releases, Open Source, Staff, Tech News, Technology

OpenViking is an open-source Context Database for AI Agents from Volcengine. The project is built around a simple architectural concept: agent systems should not treat context as a flat collection of text chunks. Instead, OpenViking organizes context through a file system paradigm, with the goal of making memory, resources, and skills manageable through a unified […]

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LangChain Releases Deep Agents: A Structured Runtime for Planning, Memory, and Context Isolation in Multi-Step AI Agents

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Most LLM agents work well for short tool-calling loops but start to break down when the task becomes multi-step, stateful, and artifact-heavy. LangChain’s Deep Agents is designed for that gap. The project is described by LangChain as an ‘agent harness‘: a standalone library built on top of LangChain’s agent building blocks and powered by the

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Zhipu AI Introduces GLM-OCR: A 0.9B Multimodal OCR Model for Document Parsing and Key Information Extraction (KIE)

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Language Model, New Releases, OCR, Technology, Uncategorized

Why Document OCR Still Remains a Hard Engineering Problem? What does it take to make OCR useful for real documents instead of clean demo images? And can a compact multimodal model handle parsing, tables, formulas, and structured extraction without turning inference into a resource bonfire? That is the problem targeted by GLM-OCR, introduced by researchers

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How to Build Type-Safe, Schema-Constrained, and Function-Driven LLM Pipelines Using Outlines and Pydantic

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Large Language Model, Staff, Technology, Tutorials

In this tutorial, we build a workflow using Outlines to generate structured and type-safe outputs from language models. We work with typed constraints like Literal, int, and bool, and design prompt templates using outlines.Template, and enforce strict schema validation with Pydantic models. We also implement robust JSON recovery and a function-calling style that generates validated

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Garry Tan Releases gstack: An Open-Source Claude Code System for Planning, Code Review, QA, and Shipping

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What if AI-assisted coding became more reliable by separating product planning, engineering review, release, and QA into distinct operating modes? That is the idea behind Garry Tan’s gstack, an open-source toolkit that packages Claude Code into 8 opinionated workflow skills backed by a persistent browser runtime. The tookit describes itself as ‘Eight opinionated workflow skills

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Google DeepMind Introduces Aletheia: The AI Agent Moving from Math Competitions to Fully Autonomous Professional Research Discoveries

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Google DeepMind team has introduced Aletheia, a specialized AI agent designed to bridge the gap between competition-level math and professional research. While models achieved gold-medal standards at the 2025 International Mathematical Olympiad (IMO), research requires navigating vast literature and constructing long-horizon proofs. Aletheia solves this by iteratively generating, verifying, and revising solutions in natural language.

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Model Context Protocol (MCP) vs. AI Agent Skills: A Deep Dive into Structured Tools and Behavioral Guidance for LLMs

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In recent times, many developments in the agent ecosystem have focused on enabling AI agents to interact with external tools and access domain-specific knowledge more effectively. Two common approaches that have emerged are skills and MCPs. While they may appear similar at first, they differ in how they are set up, how they execute tasks,

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Google AI Introduces ‘Groundsource’: A New Methodology that Uses Gemini Model to Transform Unstructured Global News into Actionable, Historical Data

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Google AI Research team recently released Groundsource, a new methodology that uses Gemini model to extract structured historical data from unstructured public news reports. The project addresses the lack of historical data for rapid-onset natural disasters. Its first output is an open-source dataset containing 2.6 million historical urban flash flood events across more than 150

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How to Build an Autonomous Machine Learning Research Loop in Google Colab Using Andrej Karpathy’s AutoResearch Framework for Hyperparameter Discovery and Experiment Tracking

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we implement a Colab-ready version of the AutoResearch framework originally proposed by Andrej Karpathy. We build an automated experimentation pipeline that clones the AutoResearch repository, prepares a lightweight training environment, and runs a baseline experiment to establish initial performance metrics. We then create an automated research loop that programmatically edits the hyperparameters

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Stanford Researchers Release OpenJarvis: A Local-First Framework for Building On-Device Personal AI Agents with Tools, Memory, and Learning

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Stanford researchers have introduced OpenJarvis, an open-source framework for building personal AI agents that run entirely on-device. The project comes from Stanford’s Scaling Intelligence Lab and is presented as both a research platform and deployment-ready infrastructure for local-first AI systems. Its focus is not only model execution, but also the broader software stack required to

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