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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

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

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

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?

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

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

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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Recursive Language Models (RLMs): From MIT’s Blueprint to Prime Intellect’s RLMEnv for Long Horizon LLM Agents

Recursive Language Models aim to break the usual trade off between context length, accuracy and cost in large language models. Instead of forcing a model to read a giant prompt in one pass, RLMs treat the prompt as an external environment and let the model decide how to inspect it with code, then recursively call

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agentic AI in digital banking

The Dark Side of Agentic AI: What Moneybot Signals About the Future of Digital Banking

This winter, Cash App is preparing to roll out something quietly revolutionary: Moneybot, a financial chatbot designed not just to answer questions, but to take action. It’s a subtle shift in description, but a monumental shift in capability. For decades, banking chatbots have been reactive tools. They checked balances, fetched statements, and maybe helped reset

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How to Design Transactional Agentic AI Systems with LangGraph Using Two-Phase Commit, Human Interrupts, and Safe Rollbacks

In this tutorial, we implement an agentic AI pattern using LangGraph that treats reasoning and action as a transactional workflow rather than a single-shot decision. We model a two-phase commit system in which an agent stages reversible changes, validates strict invariants, pauses for human approval via graph interrupts, and commits or rolls back only then.

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