AI Agents

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How This Agentic Memory Research Unifies Long Term and Short Term Memory for LLM Agents

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How do you design an LLM agent that decides for itself what to store in long term memory, what to keep in short term context and what to discard, without hand tuned heuristics or extra controllers? Can a single policy learn to manage both memory types through the same action space as text generation? Researchers […]

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Meet SETA: Open Source Training Reinforcement Learning Environments for Terminal Agents with 400 Tasks and CAMEL Toolkit

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What does an end to end stack for terminal agents look like when you combine structured toolkits, synthetic RL environments, and benchmark aligned evaluation? A team of researchers from CAMEL AI, Eigent AI and other collaborators have released SETA, a toolkit and environment stack that focuses on reinforcement learning for terminal agents. The project targets

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Agentic AI Learning Path 2026

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If you’re curious about trending terms like AI Agents or Agentic AI, you’re in the right place. Agentic AI is rapidly moving from experimentation to enterprise adoption. According to Gartner, over 60% of enterprise AI applications are expected to include agentic components by 2026, while more than 40% of early agentic AI projects are projected to be abandoned due to poor architecture, cost overruns, and lack of

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Meta and Harvard Researchers Introduce the Confucius Code Agent (CCA): A Software Engineering Agent that can Operate at Large-Scale Codebases

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How far can a mid sized language model go if the real innovation moves from the backbone into the agent scaffold and tool stack? Meta and Harvard researchers have released the Confucius Code Agent, an open sourced AI software engineer built on the Confucius SDK that is designed for industrial scale software repositories and long

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NVIDIA AI Released Nemotron Speech ASR: A New Open Source Transcription Model Designed from the Ground Up for Low-Latency Use Cases like Voice Agents

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NVIDIA has just released its new streaming English transcription model (Nemotron Speech ASR) built specifically for low latency voice agents and live captioning. The checkpoint nvidia/nemotron-speech-streaming-en-0.6b on Hugging Face combines a cache aware FastConformer encoder with an RNNT decoder, and is tuned for both streaming and batch workloads on modern NVIDIA GPUs. Model design, architecture

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How to Design an Agentic AI Architecture with LangGraph and OpenAI Using Adaptive Deliberation, Memory Graphs, and Reflexion Loops

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In this tutorial, we build a genuinely advanced Agentic AI system using LangGraph and OpenAI models by going beyond simple planner, executor loops. We implement adaptive deliberation, where the agent dynamically decides between fast and deep reasoning; a Zettelkasten-style agentic memory graph that stores atomic knowledge and automatically links related experiences; and a governed tool-use

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Marktechpost Releases ‘AI2025Dev’: A Structured Intelligence Layer for AI Models, Benchmarks, and Ecosystem Signals

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Marktechpost has released AI2025Dev, its 2025 analytics platform (available to AI Devs and Researchers without any signup or login) designed to convert the year’s AI activity into a queryable dataset spanning model releases, openness, training scale, benchmark performance, and ecosystem participants. Marktechpost is a California based AI news platform covering machine learning, deep learning, and

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How to Use Gemini 3 Pro in CLI?

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AI-based coding agents are changing developer workflows. Proof – the arrival of Gemini 3 Pro in the Gemini CLI. It shows a significant advancement. For instance, it provides advanced reasoning, enhanced tool usage, and natural-language coding right in the terminal. Developers will be able to generate, fix, and refactor code without needing to break their flow by

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A Coding Guide to Design and Orchestrate Advanced ReAct-Based Multi-Agent Workflows with AgentScope and OpenAI

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In this tutorial, we build an advanced multi-agent incident response system using AgentScope. We orchestrate multiple ReAct agents, each with a clearly defined role such as routing, triage, analysis, writing, and review, and connect them through structured routing and a shared message hub. By integrating OpenAI models, lightweight tool calling, and a simple internal runbook,

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How to Build a Production-Ready Multi-Agent Incident Response System Using OpenAI Swarm and Tool-Augmented Agents

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In this tutorial, we build an advanced yet practical multi-agent system using OpenAI Swarm that runs in Colab. We demonstrate how we can orchestrate specialized agents, such as a triage agent, an SRE agent, a communications agent, and a critic, to collaboratively handle a real-world production incident scenario. By structuring agent handoffs, integrating lightweight tools

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