AI

LLM World Model – The Secret Mind Inside AI

LLM world models represent a paradigm shift including physical AI, bridging semantic understanding with robotic embodiment. While these models excel at creating internal representations through linguistic patterns, their transition to physical systems reveals critical gaps between textual knowledge and real-world interaction. Current vision-language-action models are revolutionizing robotic control today, yet significant challenges remain in safety, reliability, and true physical comprehension.

100%成功开源Coze本地部署教程

**开源Coze安装指南摘要** Coze Studio是字节跳动开源的AI智能体开发平台,采用Apache 2.0协议,支持免费商业使用。系统要求最低2核CPU、4GB内存,需预装Docker环境。安装过程包括:克隆GitHub仓库、配置AI模型(支持OpenAI/豆包等)、设置环境变量、启动Docker容器。通过`docker-compose up -d`命令即可一键部署,访问localhost:8888开始使用。整个安装过程约需10-15分钟,提供可视化界面创建智能体、工作流,无需编程基础即可快速构建AI应用。

NEW ADAPTIVE Multi-Agent AI System: AIME (ByteDance)

AIME (Autonomous Intelligent Multi-Agent Ecosystems) is ByteDance's revolutionary multi-agent AI framework that replaces rigid planning with dynamic, adaptive coordination. Its three core innovations—Dynamic Planner for real-time strategy refinement, Actor Factory for on-demand specialized agent creation, and centralized Progress Management—enable unprecedented flexibility and intelligence sharing, dramatically outperforming traditional static multi-agent systems across complex tasks.

Kimi K2驱动Claude Code无压力,完美支持MCP协议

月之暗面于2025年7月11日重磅发布并开源Kimi K2,这是国内首个万亿参数级MoE架构大模型,总参数1T,激活参数32B。该模型采用创新的MuonClip优化器,实现15.5T token稳定训练,在编程、Agent任务和数学推理方面表现卓越,多项基准测试刷新开源模型SOTA记录。支持128K长文本处理,兼容OpenAI/Anthropic API,为开发者提供强大且经济的AI解决方案。

LLM repairs Knowledge Graph (Apple MacBook)

**LLM Knowledge Graph Repair: Promise and Limitations** Current research reveals LLMs excel at structural pattern recognition (90%+ format adherence) but struggle with semantic accuracy, achieving only 20-40% correctness in critical domains like healthcare. While promising for detection and assistance, LLMs require hybrid neurosymbolic approaches with human oversight for reliable knowledge graph repair. Future solutions likely combine neural flexibility with symbolic reasoning validation.

Andrej Karpathy: Software 3.0

Software 3.0 represents a revolutionary programming paradigm where developers use natural language prompts instead of traditional code, as popularized by Andrej Karpathy in 2025. Southeast Asia is emerging as a major AI hub, with potential to add $1 trillion to regional GDP by 2030. The region attracts record investments exceeding $30 billion in AI infrastructure, while facing challenges including talent shortages and employment displacement concerns.

Google’s revolutionary AI video generation tool, VEO 3 (How will this impact to SEA?)

Google VEO 3 is Google's revolutionary AI video generator that creates 8-second videos with synchronized audio from text prompts. Now available in 71 countries including many SEA nations, it costs $19.99-$249.99/month. For Southeast Asia's mobile-first, culturally diverse region, VEO 3 democratizes video production, enabling small creators and cultural organizations to produce high-quality content at fraction of traditional costs. However, challenges include English-only audio output and risks of cultural misrepresentation, requiring careful adoption to preserve authentic regional storytelling traditions.

MiniMax + n8n : 搭建个性化播客AI生成工作流搭建个性化播客AI生成工作流

n8n与MiniMax集成指南摘要: 本指南详细介绍了如何安装配置n8n工作流自动化平台,并与MiniMax AI服务进行集成。涵盖三种安装方式:npm、Docker和VPS部署。重点讲解MiniMax API凭证配置、HTTP Request节点设置,以及构建个性化播客生成工作流。包含文本转语音、语音克隆、视频生成等功能实现。提供完整的生产环境配置方案,包括Nginx反向代理、SSL证书和PM2进程管理,确保系统稳定运行。

科学界AlphaGo时刻,DeepMind发布AlphaEvolve

DeepMind的AlphaEvolve标志着AI从工具向科学发现合作伙伴的历史性跃进。该系统将Gemini大语言模型与进化算法相结合,实现了56年来矩阵乘法算法的首次突破,将4×4矩阵运算从49次优化至48次。更令人瞩目的是,它优化了自身的训练基础设施,将Gemini训练效率提升23%,并为谷歌数据中心节省数亿美元成本。AlphaEvolve不仅解决传统数学难题,更在75%的测试案例中重现最优解,20%的案例中发现新突破,预示着人机协作科研的新纪元。

HOW TO Build Qwen3’s Dual Mode AI (0.6B to 235B)

Qwen3 introduces revolutionary dual-mode AI architecture enabling dynamic switching between "syncing" (thinking) and "non-syncing" modes within a single model. Syncing mode provides explicit step-by-step reasoning for complex problems, while non-syncing mode delivers rapid, immediate responses. This elegant solution uses simple template differences during training, effectively eliminating the need for separate specialized models while maintaining both reasoning depth and response efficiency.