AI

Eric Schmidt – All-in Summit, 2025

October 26, 2025 coffee
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AI, Education, Quantum and U, Speeches

Former Google CEO Eric Schmidt reveals the stark reality of US-China technological competition. While America pursues ambitious AGI projects, China focuses on practical AI applications and open-source dominance. Schmidt's firsthand experience with Ukraine demonstrates warfare's transformation through autonomous drones, fundamentally changing military economics. He emphasizes America must leverage its entrepreneurial culture, deep capital markets, and innovation ecosystem to maintain competitive advantage in this consequential global race spanning AI, space, and defense technologies.

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The FDE Playbook for AI Startups

October 21, 2025 coffee
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AI, Education, Quantum and U, Quantum Mindset Programme

Forward Deployed Engineers bridge the gap between product capabilities and customer needs by embedding technical engineers directly at client sites. Unlike traditional consulting, FDEs build rapid prototypes that inform permanent product improvements while delivering measurable business outcomes. This Palantir-originated model has become the dominant strategy for AI startups, with over 100 Y Combinator companies now hiring FDEs to navigate heterogeneous markets where no incumbent solutions exist.

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China’s $48B Xinjiang AI Data Center

September 17, 2025 coffee
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AI, AI Data Center, Education, Green Energy, NVIDIA

Xinjiang offers multiple strategic advantages for data centers including abundant renewable energy resources, natural cooling from low temperatures and dry climate, cheap land availability, and strategic geographic positioning along the Belt and Road Initiative. These combined factors enable China to build highly cost-effective AI infrastructure while spreading digital economy benefits beyond eastern cities, supporting ambitious national AI leadership goals effectively.

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Thinking Machines Lab 解决方案: 攻克LLM推理非确定性难题

September 13, 2025 coffee
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AI, Chinese/中文, Education, Quantum and U

## Thinking Machines Lab：Connectionism 核心摘要 Thinking Machines Lab由OpenAI前CTO米拉·穆拉蒂于2025年2月创立，完成20亿美元种子轮融资，估值120亿美元。团队汇集了OpenAI联合创始人约翰·舒尔曼、前VP巴雷特·佐夫等顶尖AI人才。公司推出"Connectionism"研究博客，首篇论文解决大模型推理非确定性问题。其使命是构建个性化AI系统、发展强大技术基础、培养开放科学文化。公司承诺定期分享研究成果，致力于让AI广泛有用和易于理解，代表了AI领域向开放透明科学研究的重要回归。

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SpecKit: Github’s NEW tool That FINALLY Fixes AI Coding

September 11, 2025 coffee
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AI, Education, Quantum and U

GitHub's SpecKit is an open-source toolkit that revolutionizes AI-assisted coding by transforming vague prompts into structured, executable specifications. Using a four-phase workflow (Specify, Plan, Tasks, Implement), it eliminates AI guesswork and ensures generated code aligns with project requirements. Compatible with GitHub Copilot, Claude Code, and Gemini CLI, SpecKit makes AI coding reliable and predictable.

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NVIDIA’s Isaac Sim & Isaac Lab – Complete Guide to Building & Training Robots

September 9, 2025 coffee
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AI, AI Robot, Education, NVIDIA, Quantum and U

NVIDIA's Isaac Sim and Isaac Lab offer a complete robotics simulation pipeline, enabling developers to train robots from CAD design to real-world deployment without physical hardware risks. This comprehensive 59-minute guide demonstrates installation, custom robot creation, machine learning integration, and successful simulation-to-reality transfer. While technically demanding, these free tools revolutionize robotics development through realistic physics simulation and policy training capabilities.

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Master Inverse Kinematics for Arduino Robots – Easy Math, Full Code, Real Results

September 8, 2025 coffee
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AI, AI Robot, Education, Quantum and U, Uncategorized

Master smooth robotic movement with this comprehensive inverse kinematics implementation guide for Arduino robots. Features complete object-oriented source code, step-by-step hardware setup, progressive test programs, and advanced features like Bluetooth control and obstacle avoidance. Transform complex mathematics into practical, working code for hexapod robots or robotic arms. Includes troubleshooting, calibration procedures, and multiple gait patterns for professional-grade robotic coordination.

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Stanford CS231N Deep Learning for Computer Vision, Lecture 1: Introduction

September 6, 2025 coffee
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AI, Education, Quantum and U, Quantum Mindset Programme, Speeches

Stanford CS231N's opening lecture traces computer vision from its biological origins 540 million years ago to today's AI revolution. Professor Fei-Fei Li chronicles the field's evolution from 1950s neuroscience discoveries through the AI winter to the transformative 2012 ImageNet breakthrough with AlexNet. The course explores deep learning fundamentals, visual understanding tasks, large-scale training, and generative models. Applications span medical diagnosis to creative AI, while emphasizing ethical considerations and interdisciplinary collaboration essential for responsible AI development in computer vision.

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NEW Sim AI compare to N8N

September 4, 2025 coffee
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AI, Education, Quantum and U, Uncategorized

SIM AI is an open-source, visual workflow builder specifically designed for AI agents, backed by Y Combinator and used by 20,000+ developers worldwide. It enables drag-and-drop creation of complex AI workflows with real-time team collaboration, local model support via Ollama, and production-ready deployment options. The platform offers AI-native design with structured outputs, extensive integrations, and eliminates coding requirements for sophisticated automation.

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Huawei has officially unveiled the world’s first ternary logic chip

September 2, 2025 coffee
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AI, AI Data Center, AI Robot, Education, Green Energy, NVIDIA, Quantum and U

**Huawei's Ternary Logic Chip: Revolutionary Computing Breakthrough** Huawei has unveiled the world's first ternary logic chip, utilizing three states (-1, 0, +1) instead of binary's two-state system. This breakthrough achieves 40% fewer transistors and 60% power reduction through innovative CNTFET technology and quantum state isolated gate architecture. Applications span AI data centers, autonomous vehicles, and machine learning, with dramatic cost savings—reducing autonomous driving computation costs by 67%. Successfully solving challenges that defeated Soviet scientists in 1958, this paradigm shift could revolutionize global computing architecture.

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