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Unsloth AI Releases Unsloth Studio: A Local No-Code Interface For High-Performance LLM Fine-Tuning With 70% Less VRAM Usage

The transition from a raw dataset to a fine-tuned Large Language Model (LLM) traditionally involves significant infrastructure overhead, including CUDA environment management and high VRAM requirements. Unsloth AI, known for its high-performance training library, has released Unsloth Studio to address these friction points. The Studio is an open-source, no-code local interface designed to streamline the […]

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

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

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

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

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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NVIDIA Releases Nemotron 3 Super: A 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivering 5x Higher Throughput for Agentic AI

The gap between proprietary frontier models and highly transparent open-source models is closing faster than ever. NVIDIA has officially pulled the curtain back on Nemotron 3 Super, a staggering 120 billion parameter reasoning model engineered specifically for complex multi-agent applications. Released today, Nemotron 3 Super sits perfectly between the lightweight 30 billion parameter Nemotron 3

NVIDIA Releases Nemotron 3 Super: A 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivering 5x Higher Throughput for Agentic AI Read More »

Ai2: Building physical AI with virtual simulation data

Virtual simulation data is driving the development of physical AI across corporate environments, led by initiatives like Ai2’s MolmoBot. Instructing hardware to interact with the real world has historically relied on highly expensive and manually-collected demonstrations. Technology providers building generalist manipulation agents typically frame extensive real-world training as the basis for these systems. For some

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NVIDIA AI Releases Nemotron-Terminal: A Systematic Data Engineering Pipeline for Scaling LLM Terminal Agents

The race to build autonomous AI agents has hit a massive bottleneck: data. While frontier models like Claude Code and Codex CLI have demonstrated impressive proficiency in terminal environments, the training strategies and data mixtures behind them have remained closely guarded secrets. This lack of transparency has forced researchers and devs into a costly cycle

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ByteDance Releases DeerFlow 2.0: An Open-Source SuperAgent Harness that Orchestrates Sub-Agents, Memory, and Sandboxes to do Complex Tasks

The era of the ‘Copilot’ is officially getting an upgrade. While the tech world has spent the last two years getting comfortable with AI that suggests code or drafts emails, ByteDance team is moving the goalposts. They released DeerFlow 2.0, a newly open-sourced ‘SuperAgent’ framework that doesn’t just suggest work; it executes it. DeerFlow is

ByteDance Releases DeerFlow 2.0: An Open-Source SuperAgent Harness that Orchestrates Sub-Agents, Memory, and Sandboxes to do Complex Tasks Read More »

Andrew Ng’s Team Releases Context Hub: An Open Source Tool that Gives Your Coding Agent the Up-to-Date API Documentation It Needs

In the fast-moving world of agentic workflows, the most powerful AI model is still only as good as its documentation. Today, Andrew Ng and his team at DeepLearning.AI officially launched Context Hub, an open-source tool designed to bridge the gap between an agent’s static training data and the rapidly evolving reality of modern APIs. You

Andrew Ng’s Team Releases Context Hub: An Open Source Tool that Gives Your Coding Agent the Up-to-Date API Documentation It Needs Read More »