agentic ai

Auto Added by WPeMatico

Qwen Team Releases Qwen3-Coder-Next: An Open-Weight Language Model Designed Specifically for Coding Agents and Local Development

Qwen team has just released Qwen3-Coder-Next, an open-weight language model designed for coding agents and local development. It sits on top of the Qwen3-Next-80B-A3B backbone. The model uses a sparse Mixture-of-Experts (MoE) architecture with hybrid attention. It has 80B total parameters, but only 3B parameters are activated per token. The goal is to match the […]

Qwen Team Releases Qwen3-Coder-Next: An Open-Weight Language Model Designed Specifically for Coding Agents and Local Development Read More »

The rise of Moltbook suggests viral AI prompts may be the next big security threat

On November 2, 1988, graduate student Robert Morris released a self-replicating program into the early Internet. Within 24 hours, the Morris worm had infected roughly 10 percent of all connected computers, crashing systems at Harvard, Stanford, NASA, and Lawrence Livermore National Laboratory. The worm exploited security flaws in Unix systems that administrators knew existed but

The rise of Moltbook suggests viral AI prompts may be the next big security threat Read More »

Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflows

Google has introduced Conductor, an open source preview extension for Gemini CLI that turns AI code generation into a structured, context driven workflow. Conductor stores product knowledge, technical decisions, and work plans as versioned Markdown inside the repository, then drives Gemini agents from those files instead of ad hoc chat prompts. From chat based coding

Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflows Read More »

OpenAI picks up pace against Claude Code with new Codex desktop app

Today, OpenAI launched a macOS desktop app for Codex, its large language model-based coding tool that was previously used through a command line interface (CLI) on the web or inside an integrated development environment (IDE) via extensions. By launching a desktop app, OpenAI is catching up to Anthropic’s popular Claude Code, which already offered a

OpenAI picks up pace against Claude Code with new Codex desktop app Read More »

Klarna backs Google UCP to power AI agent payments

Klarna aims to address the lack of interoperability between conversational AI agents and backend payment systems by backing Google’s Universal Commerce Protocol (UCP), an open standard designed to unify how AI agents discover products and execute transactions. The partnership, which also sees Klarna supporting Google’s Agent Payments Protocol (AP2), places the Swedish fintech firm among

Klarna backs Google UCP to power AI agent payments Read More »

NVIDIA AI Brings Nemotron-3-Nano-30B to NVFP4 with Quantization Aware Distillation (QAD) for Efficient Reasoning Inference

NVIDIA has released Nemotron-Nano-3-30B-A3B-NVFP4, a production checkpoint that runs a 30B parameter reasoning model in 4 bit NVFP4 format while keeping accuracy close to its BF16 baseline. The model combines a hybrid Mamba2 Transformer Mixture of Experts architecture with a Quantization Aware Distillation (QAD) recipe designed specifically for NVFP4 deployment. Overall, it is an ultra-efficient

NVIDIA AI Brings Nemotron-3-Nano-30B to NVFP4 with Quantization Aware Distillation (QAD) for Efficient Reasoning Inference Read More »

How to Build Memory-Driven AI Agents with Short-Term, Long-Term, and Episodic Memory

In this tutorial, we build a memory-engineering layer for an AI agent that separates short-term working context from long-term vector memory and episodic traces. We implement semantic storage using embeddings and FAISS for fast similarity search, and we add episodic memory that captures what worked, what failed, and why, so the agent can reuse successful

How to Build Memory-Driven AI Agents with Short-Term, Long-Term, and Episodic Memory Read More »

The Rise of Multimodal AI Agents: Smarter Systems or a Bigger Risk?

Artificial intelligence is quietly undergoing one of its most important shifts yet. For years, AI agents were largely confined to text—answering questions, generating content, or automating simple, rule-based tasks. Useful, yes—but limited. That limitation is now disappearing. We’re entering the era of Multimodal AI Agents—systems that can see, hear, read, reason, and act across multiple

The Rise of Multimodal AI Agents: Smarter Systems or a Bigger Risk? Read More »

Robbyant Open Sources LingBot World: a Real Time World Model for Interactive Simulation and Embodied AI

Robbyant, the embodied AI unit inside Ant Group, has open sourced LingBot-World, a large scale world model that turns video generation into an interactive simulator for embodied agents, autonomous driving and games. The system is designed to render controllable environments with high visual fidelity, strong dynamics and long temporal horizons, while staying responsive enough for

Robbyant Open Sources LingBot World: a Real Time World Model for Interactive Simulation and Embodied AI Read More »

AI2 Releases SERA, Soft Verified Coding Agents Built with Supervised Training Only for Practical Repository Level Automation Workflows

Allen Institute for AI (AI2) Researchers introduce SERA, Soft Verified Efficient Repository Agents, as a coding agent family that aims to match much larger closed systems using only supervised training and synthetic trajectories. What is SERA? SERA is the first release in AI2’s Open Coding Agents series. The flagship model, SERA-32B, is built on the

AI2 Releases SERA, Soft Verified Coding Agents Built with Supervised Training Only for Practical Repository Level Automation Workflows Read More »