Time is limited, so we will be direct. Here is your AI Dev Brief from Marktechpost, covering core research, models, infrastructure tools, and applied updates for AI developers and researchers.
Meta AI Releases Segment Anything Model 3 (SAM 3) for Promptable Concept Segmentation in Images and Videos
Meta’s Segment Anything Model 3 (SAM 3) is a 848M parameter vision foundation model that upgrades Segment Anything from promptable visual segmentation to Promptable Concept Segmentation, unifying image and video detection, segmentation and tracking from text prompts, exemplars, points and boxes. Trained and evaluated on the new SA-Co stack with about 270K evaluated concepts and over 4M automatically annotated concepts, SAM 3 approaches 75–80 percent of human cgF1 and sets a new reference baseline for open vocabulary image and video segmentation. Read the full launch insights/article here.
Allen Institute for AI (AI2) Introduces Olmo 3: An Open Source 7B and 32B LLM Family Built on the Dolma 3 and Dolci Stack
Olmo 3 is AI2’s new fully open 7B and 32B language model family that exposes the entire “model flow” from Dolma 3 pre training to Dolci post training, including all datasets, checkpoints, and evaluation tools. The Base, Think, Instruct, and RL Zero variants offer 65K context, strong reasoning and tool use, and a clean RLVR pathway, giving engineers a transparent, reproducible stack that competes with Qwen and Gemma models at similar scale while remaining fully inspectable. Read the full launch insights/article here.
Germany based open-source remote access company - NetBird just built an "AI Mega Mesh". A project that started out to prove that multi-cloud networking doesn’t have to be complicated, resulted in creating a secure AI inference infrastructure that connects GPU resources across multiple cloud providers using Microk8s, vLLM, and NetBird. Read the full launch insights/article here.
No complex VPN configs.
No firewall configs.
No provider-specific networking rituals.
Google Antigravity Makes the IDE a Control Plane for Agentic Coding
Google Antigravity is Google’s new agent first IDE built on a Visual Studio Code fork that turns Gemini 3 Pro and other models into autonomous coding agents operating across the editor, terminal and browser. It introduces Editor view and Manager view for supervising single or multiple agents, and uses Artifacts, such as task lists, plans, screenshots and browser recordings, as verifiable evidence of work. The platform is in free public preview on Windows, macOS and Linux with generous Gemini 3 Pro rate limits. Read the full launch insights/article here.
Project Notebooks/Tutorials
▶ [Open Source] Rogue: An Open-Source AI Agent Evaluator worth trying Codes & Examples
▶ How to Build a Fully Offline Multi-Tool Reasoning Agent with Dynamic Planning, Error Recovery, and Intelligent Function Routing Codes Tutorial
▶ An Implementation of a Comprehensive Empirical Framework for Benchmarking Reasoning Strategies in Modern Agentic AI Systems Codes Tutorial
▶ How to Build a Model-Native Agent That Learns Internal Planning, Memory, and Multi-Tool Reasoning Through End-to-End Reinforcement Learning Codes Tutorial