agentic ai

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GitHub Releases Copilot-SDK to Embed Its Agentic Runtime in Any App

GitHub has opened up the internal agent runtime that powers GitHub Copilot CLI and exposed it as a programmable SDK. The GitHub Copilot-SDK, now in technical preview, lets you embed the same agentic execution loop into any application so the agent can plan, invoke tools, edit files, and run commands as part of your own […]

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How an AI Agent Chooses What to Do Under Tokens, Latency, and Tool-Call Budget Constraints?

In this tutorial, we build a cost-aware planning agent that deliberately balances output quality against real-world constraints such as token usage, latency, and tool-call budgets. We design the agent to generate multiple candidate actions, estimate their expected costs and benefits, and then select an execution plan that maximizes value while staying within strict budgets. With

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Microsoft Releases VibeVoice-ASR: A Unified Speech-to-Text Model Designed to Handle 60-Minute Long-Form Audio in a Single Pass

Microsoft has released VibeVoice-ASR as part of the VibeVoice family of open source frontier voice AI models. VibeVoice-ASR is described as a unified speech-to-text model that can handle 60-minute long-form audio in a single pass and output structured transcriptions that encode Who, When, and What, with support for Customized Hotwords. VibeVoice sits in a single

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Controlling AI agent sprawl: The CIO’s guide to governance

Corporate networks are filling up with AI agents, creating a governance blind spot for leaders managing multi-cloud infrastructures. As distinct business units race to adopt generative technologies, CIOs especially find their ecosystems populated by fragmented and unmonitored assets. This mirrors the shadow IT challenges of the cloud era, but involves autonomous actors capable of executing

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eBay bans illicit automated shopping amid rapid rise of AI agents

On Tuesday, eBay updated its User Agreement to explicitly ban third-party “buy for me” agents and AI chatbots from interacting with its platform without permission, first spotted by Value Added Resource. On its face, a one-line terms of service update doesn’t seem like major news, but what it implies is more significant: The change reflects

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FlashLabs Researchers Release Chroma 1.0: A 4B Real Time Speech Dialogue Model With Personalized Voice Cloning

Chroma 1.0 is a real time speech to speech dialogue model that takes audio as input and returns audio as output while preserving the speaker identity across multi turn conversations. It is presented as the first open source end to end spoken dialogue system that combines low latency interaction with high fidelity personalized voice cloning

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A Coding Guide to Anemoi-Style Semi-Centralized Agentic Systems Using Peer-to-Peer Critic Loops in LangGraph

In this tutorial, we demonstrate how a semi-centralized Anemoi-style multi-agent system works by letting two peer agents negotiate directly without a manager or supervisor. We show how a Drafter and a Critic iteratively refine an output through peer-to-peer feedback, reducing coordination overhead while preserving quality. We implement this pattern end-to-end in Colab using LangGraph, focusing

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Zhipu AI Releases GLM-4.7-Flash: A 30B-A3B MoE Model for Efficient Local Coding and Agents

GLM-4.7-Flash is a new member of the GLM 4.7 family and targets developers who want strong coding and reasoning performance in a model that is practical to run locally. Zhipu AI (Z.ai) describes GLM-4.7-Flash as a 30B-A3B MoE model and presents it as the strongest model in the 30B class, designed for lightweight deployment where

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How to Design a Fully Streaming Voice Agent with End-to-End Latency Budgets, Incremental ASR, LLM Streaming, and Real-Time TTS

In this tutorial, we build an end-to-end streaming voice agent that mirrors how modern low-latency conversational systems operate in real time. We simulate the complete pipeline, from chunked audio input and streaming speech recognition to incremental language model reasoning and streamed text-to-speech output, while explicitly tracking latency at every stage. By working with strict latency

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Nous Research Releases NousCoder-14B: A Competitive Olympiad Programming Model Post-Trained on Qwen3-14B via Reinforcement Learning

Nous Research has introduced NousCoder-14B, a competitive olympiad programming model that is post trained on Qwen3-14B using reinforcement learning (RL) with verifiable rewards. On the LiveCodeBench v6 benchmark, which covers problems from 08/01/2024 to 05/01/2025, the model reaches a Pass@1 accuracy of 67.87 percent. This is 7.08 percentage points higher than the Qwen3-14B baseline of

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