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Alibaba Qwen Team Releases Qwen3.5-397B MoE Model with 17B Active Parameters and 1M Token Context for AI agents

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Alibaba Cloud just updated the open-source landscape. Today, the Qwen team released Qwen3.5 , the newest generation of their large language model (LLM) family. The most powerful version is Qwen3.5-397B-A17B . This model is a sparse Mixture-of-Experts (MoE) system. It combines massive reasoning power with high efficiency. Qwen3.5 is a native vision-language model. It is designed specifically for AI agents. It can see, code, and reason across 201 languages. https://ift.tt/yZtoL8k The Core Architecture: 397B Total, 17B Active The technical specifications of Qwen3.5-397B-A17B are impressive. The model contains 397B total parameters. However, it uses a sparse MoE design. This means it only activates 17B parameters during any single forward pass. This 17B activation count is the most important number for devs. It allows the model to provide the intelligence of a 400B model. But it runs with the speed of a much smaller model. The Qwen team reports a 8.6x to 19.0x increase in ...
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Google DeepMind Proposes New Framework for Intelligent AI Delegation to Secure the Emerging Agentic Web for Future Economies

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The AI industry is currently obsessed with ‘agents’—autonomous programs that do more than just chat. However, most current multi-agent systems rely on brittle, hard-coded heuristics that fail when the environment changes. Google DeepMind researchers have proposed a new solution. The research team argued that for the ‘agentic web’ to scale, agents must move beyond simple task-splitting and adopt human-like organizational principles such as authority, responsibility, and accountability. Defining ‘Intelligent’ Delegation In standard software, a subroutine is just ‘outsourced’. Intelligent delegation is different. It is a sequence of decisions where a delegator transfers authority and responsibility to a delegatee. This process involves risk assessment, capability matching, and establishing trust. The 5 Pillars of the Framework To build this, the research team identified 5 core requirements mapped to specific technical protocols: Framework Pillar Technical Implementation Core...
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A Coding Implementation to Design a Stateful Tutor Agent with Long-Term Memory, Semantic Recall, and Adaptive Practice Generation

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In this tutorial, we build a fully stateful personal tutor agent that moves beyond short-lived chat interactions and learns continuously over time. We design the system to persist user preferences, track weak learning areas, and selectively recall only relevant past context when responding. By combining durable storage, semantic retrieval, and adaptive prompting, we demonstrate how an agent can behave more like a long-term tutor than a stateless chatbot. Also, we focus on keeping the agent self-managed, context-aware, and able to improve its guidance without requiring the user to repeat information. Copy Code Copied Use a different Browser !pip -q install "langchain>=0.2.12" "langchain-openai>=0.1.20" "sentence-transformers>=3.0.1" "faiss-cpu>=1.8.0.post1" "pydantic>=2.7.0" import os, json, sqlite3, uuid from datetime import datetime, timezone from typing import List, Dict, Any import numpy as np import faiss...
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Moonshot AI Launches Kimi Claw: Native OpenClaw on Kimi.com with 5,000 Community Skills and 40GB Cloud Storage Now

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Moonshot AI has officially brought the power of OpenClaw framework directly to the browser. The newly rebranded Kimi Claw is now native to kimi.com , providing developers and data scientists with a persistent, 24/7 AI agent environment. This update moves the project from a local setup to a cloud-native powerhouse. This means the infrastructure for complex agents is now fully managed and ready to scale. ClawHub: A Global Skill Registry The core of Kimi Claw’s versatility is ClawHub . This library features over 5,000 community-contributed skills. Modular Architecture: Each ‘skill’ is a functional extension that allows the AI to interact with external tools. Instant Orchestration: Developers can discover, call, and chain these skills within the kimi.com interface. No-Code Integration: Instead of writing custom API wrappers, engineers can leverage existing skills to connect their agents to third-party services immediately. 40GB Cloud Storage for Data Workflows Data scient...
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Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support

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The landscape of generative audio is shifting toward efficiency. A new open-source contender, Kani-TTS-2 , has been released by the team at nineninesix .ai. This model marks a departure from heavy, compute-expensive TTS systems. Instead, it treats audio as a language, delivering high-fidelity speech synthesis with a remarkably small footprint. Kani-TTS-2 offers a lean, high-performance alternative to closed-source APIs. It is currently available on Hugging Face in both English ( EN ) and Portuguese ( PT ) versions. The Architecture: LFM2 and NanoCodec Kani-TTS-2 follows the ‘Audio-as-Language ‘ philosophy. The model does not use traditional mel-spectrogram pipelines. Instead, it converts raw audio into discrete tokens using a neural codec. The system relies on a two-stage process: The Language Backbone: The model is built on LiquidAI’s LFM2 (350M) architecture. This backbone generates ‘audio intent’ by predicting the next audio tokens. Because LFM (Liquid Foundation Models) a...
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Getting Started with OpenClaw and Connecting It with WhatsApp

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OpenClaw is a self-hosted personal AI assistant that runs on your own devices and communicates through the apps you already use—such as WhatsApp, Telegram, Slack, Discord, and more. It can answer questions, automate tasks, interact with your files and services, and even speak or listen on supported devices, all while keeping you in control of your data. Rather than being just another chatbot, OpenClaw acts as a true personal assistant that fits into your daily workflow. In just a few months, this open-source project has surged in popularity, crossing 150,000+ stars on GitHub. In this article, we’ll walk through how to get started with OpenClaw and connect it to WhatsApp. What can OpenClaw do? OpenClaw is built to fit seamlessly into your existing digital life. It connects with 50+ integrations , letting you chat with your assistant from apps like WhatsApp, Telegram, Slack, or Discord, while controlling and automating tasks from your desktop. You can use cloud or local AI models of y...
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Google AI Introduces the WebMCP to Enable Direct and Structured Website Interactions for New AI Agents

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Google is officially turning Chrome into a playground for AI agents. For years, AI ‘browsers’ have relied on a messy process: taking screenshots of websites, running them through vision models, and guessing where to click. This method is slow, breaks easily, and consumes massive amounts of compute. Google has introduced a better way: the Web Model Context Protocol (WebMCP) . Announced alongside the Early Preview Program (EPP) , this protocol allows websites to communicate directly to AI models. Instead of the AI ‘guessing’ how to use a site, the site tells the AI exactly what tools are available. The End of Screen Scraping Current AI agents treat the web like a picture. They ‘look’ at the UI and try to find the ‘Submit’ button. If the button moves 5 pixels, the agent might fail. WebMCP replaces this guesswork with structured data. It turns a website into a set of capabilities . For developers, this means you no longer have to worry about an AI breaking your frontend. You simply def...
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