Zhouzhou He

Alibaba Group dropped a Chinese New Year gift - Qwen 3.5 🚀 • Open-sourced Qwen3.5-397B-A17B (Qwen3.5-Plus), a natively multimodal foundation model (text, image, video). Strong on reasoning, coding, agents, and vision • 201 languages 🌍 - Up from 119 in Qwen3, including low-resource languages like Hawaiian, Fijian • Inference efficiency ⚡ - Linear attention + sparse MoE design cuts compute while matching the much larger Qwen3-Max (1T+ params). Lower deployment cost so teams can scale multimodal apps without blowing the budget. • Agentic use cases 📱 - Visual agent for phones and PCs; long-form video understanding (up to 2 hours); hand-drawn UI sketches → functional front-end code. Built for GUI interaction and multi-step workflows. • Where to get it 🔧 - Hugging Face, GitHub, ModelScope, and Qwen Chat. APIs on Alibaba Cloud Model Studio. TBD - More Qwen3.5 variants open-sourced in the coming weeks. Takeaway 💡 Open-source frontier models are moving to global audiences (200+ languages), optimized for production. What’s your take on the new Qwen model? Share in the comments. 👇 #AI #MachineLearning #Developer #SoftwareEngineering #Tech #OpenSource #Alibaba #Qwen

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The Open Claw Revolution: Why "Local AI Agents" are the New Digital Workforce 🚀 ​The viral "Moltbot" phenomenon (now officially Open Claw) has shifted the conversation from chatting with AI to deploying it. We aren't just looking at a trend; we are looking at the birth of the "Local Agentic Stack." ​If you’ve seen the "Moltbook" social network posts, you know the hype. But for those of us in the trenches of automation, the real question is: How do you host Open Claw securely on your own hardware to run 24/7? ​1. What is Open Claw (Formerly Moltbot)? ​Open Claw is an autonomous, local-first agent capable of executing complex tasks—coding, browser navigation, and file management—directly on your machine. ​Zero Latency: No API lag. ​Data Sovereignty: Your sensitive business data stays on your SSD. ​The "Moltbook" Network: Your agent can interact with other agents in a decentralized ecosystem. ​2. Step-by-Step: How to Setup Open Claw on Mac ​Environment Check: Ensure you have Node.js (v22+) and Homebrew installed. ​The Install Command: Run curl -fsSL https://lnkd.in/d5qm9fNN | bash in your Terminal. ​Local Brain Integration: Pair Open Claw with Ollama to run models like Llama 3 locally. ​Security: Ensure you are on version 1.4.2+ to stay protected against recent CVE protocols. ​3. The Performance Tier: Choosing Your "Agent Engine" ​You cannot run a high-level autonomous agent 24/7 on an underpowered machine. Here are the three optimal hardware paths I recommend for Open Claw: ​🟢 The "Always-On" Budget Server (Best for 24/7 Tasks) ​Perfect as a dedicated "AI Hub" for email sorting and simple research. 16GB RAM is the absolute minimum for local LLMs. 👉 Get the Mac Mini M1 (16GB RAM / 1TB SSD): https://amzn.to/4a6kstn ​🔵 The Mobile Powerhouse (Best for Solopreneurs) ​Built for Apple Intelligence, the M4 chip handles Open Claw’s browser-use features effortlessly while you're on the move. 👉 Get the 2025 MacBook Air 15-inch (M4 Chip): https://amzn.to/46gwFcP ​🔴 The Pro-Tier Agency Workhorse (Best for Agent Swarms) ​If you are running multiple Open Claw agents or processing heavy codebases, the 24GB of Unified Memory is a necessity. 👉 Get the 2024 MacBook Pro (M4 Pro / 24GB RAM): https://amzn.to/4qAeVAs ​4. Monetization: Turning "Claws" into Cash ​Setup-as-a-Service: Charge a premium to set up local "Agent Hubs" for non-technical founders. ​Automated Lead Gen: Set an Open Claw agent to identify high-intent leads on LinkedIn while you sleep. ​Local Code Audits: Use the agent to audit massive repos locally—saving thousands in cloud token costs. ​Are you ready to move your AI off the cloud and onto your desk? Let's discuss in the comments. 👇

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Recently got early access to ByteDance Seedance 2 Dreamina AI and the CapCut Creative Partner Program (CPP), so of course I had to run an experiment. If you don’t know me yet, I love pushing AI systems to their limits and seeing how far they can go. Here’s what I tested today: 1️⃣ Text-to-video generation (style exploration, character development, and consistency) 2️⃣ Uploading the generated video back as a reference and asking the system to recreate a new scene using the same characters and visual language Topaz Labs AI upscale So basically, I wanted to see if the model could stay consistent when referencing its own output. The result is actually really solid. The character retention and style continuity surprised me. You can judge it for yourself. Still early access. Still experimenting. And this is getting interesting.

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No peace for the market - AI hardware prices are taking off The hardware market is in trouble. A new report from the South Korean agency Newsis confirms what we are already seeing in stores, the days of cheap, high-power computers are over. * Experts say the RTX 5090 could reach 5000 USD. While people are still debating this, many stores have already raised prices to the 3 600 - 4 000 USD range. This is the new normal. * Video memory is now like "digital gold." Most of the supply is being bought by massive AI data centers. This has made memory so expensive that it now makes up most of the cost of a video card. * AMD and Nvidia are stopping fixed price lists. Starting in January and February, prices will likely change every month. A server you buy today will probably cost 10–15% more next month. So we are stopping the "wait and see" approach. Since hardware costs are rising so fast, we are moving to a "decide here and now" model. For current projects - we need to buy necessary parts immediately to avoid next month’s price increase. For new projects - we need to make our code as efficient as possible. If a project uses too much memory, we have to redesign it today. Stable prices are a thing of the past. Our goal is to protect our projects while costs keep growing. https://lnkd.in/dEjCKxHb https://lnkd.in/dxGHyEXF

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**AI & Emerging Tech Highlights – 2026** - **Title:** *iQIYI LAND Yangzhou to Open on February 8, Marking New Chapter in China’s Immersive Entertainment Scene* **Summary:** iQIYI’s first global offline entertainment park, iQIYI LAND, will debut in Yangzhou, blending AI‑powered storytelling, real‑time motion capture, and interactive environments to bring Chinese IP to life in a fully immersive setting. **URL:** https://lnkd.in/gtht4RZn - **Title:** *Future Technology: ఏఐ.. క్వాంటమ్‌ టెక్నాలజీ.. హీరోలు* **Summary:** The article charts how AI and quantum computing are converging in 2026, with breakthroughs in drug discovery, logistics optimization, and secure communications underscoring the technology’s growing mainstream impact. **URL:** https://lnkd.in/ge2KR47s - **Title:** *Tech Giants Prepare Major AI and Hardware Launches for 2026* **Summary:** CES 2026 is set to showcase Intel’s Core Ultra processors, Samsung’s AI‑driven living solutions, Google’s Gemini‑powered smart glasses, and Apple’s 20‑product lineup, highlighting the industry’s pivot toward AI‑centric hardware. **URL:** https://lnkd.in/gpeW-Yde - **Title:** *Starlink India Release Date, Pricing, Internet Speed, Plans, Availability, And More, What To Expect In 2026* **Summary:** SpaceX’s Starlink satellite network will enter India in 2026, deploying AI‑optimized routing and adaptive beamforming to deliver high‑speed connectivity to rural and underserved areas. **URL:** https://lnkd.in/gDKY3Np8 - **Title:** *These HP LaserJet printers are optimal for quick printing at home and office* **Summary:** HP’s LaserJet lineup incorporates machine‑learning algorithms to predict ink usage, auto‑adjust print quality, and streamline maintenance, illustrating AI’s role in everyday office hardware. **URL:** https://lnkd.in/grx2CQqN - **Title:** *WNBA Fans Lose It After Caitlin Clark Teases Never‑Seen‑Before Nike Shoe Tech* **Summary:** Nike’s upcoming signature sneaker, teased by Caitlin Clark, will feature AI‑driven material science and predictive performance analytics, showcasing AI’s influence on next‑generation athletic footwear. **URL:** https://lnkd.in/gBri4E7V...

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🎙️ Kyrah AI is now live on YouTube — and this conversation matters. Dr. Nancy invited our leadership to the Product Insider Podcast to talk about Kyrah AI — the product we built during the AI PM Bootcamp to help detect emotional and psychological abuse early, before it escalates. This conversation between Diwakar Sharma and Dr. Nancy Li was deeply intentional. Because most harm doesn’t start loud. It starts quietly. 🎥 Watch the full conversation on YouTube https://lnkd.in/gH_4rTwn Some facts were discussed: • 80% of abuse begins with psychological control before becoming physical • Only 1% of victims seek professional help • Abuse does not discriminate by gender, career, or social status • Many people don’t realize abuse is happening — it often feels like “normal conflict” 💡 What Kyrah AI does differently • A private, AI-powered emotional safety tool • Identifies harmful patterns through journaling and conversation • Built with trauma-informed guardrails, privacy, and user agency at the core Kyrah AI is not about replacing professionals. It’s about giving people language, clarity, and awareness — especially in moments when speaking out feels impossible. Grateful to Dr. Nancy for creating space for this conversation and for supporting products that put emotional safety first. Ask Kyrah: 🔗 https://lnkd.in/gbxmuBA5 #KyrahAI #AIForGood #EmotionalSafety #TraumaInformedDesign #EthicalAI #ProductManagement #WomensSafety #MentalHealthAwareness Clement Lee

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𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗰𝗮𝗻 𝗻𝗼𝘄 𝘀𝘂𝗯𝗺𝗶𝘁 𝗮𝗽𝗽𝘀 𝘁𝗼 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗦𝗼 𝘁𝗵𝗲 𝗰𝗼𝗿𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗻𝗼𝘄 𝗶𝘀: 𝗕𝘂𝗶𝗹𝗱 𝗜𝗻-𝗵𝗼𝘂𝘀𝗲 𝗔𝗜 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗢𝗥. 𝗢𝗳𝗳𝗲𝗿 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗮𝗽𝗽𝘀 𝗮𝗻𝗱 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀? https://lnkd.in/gK3ZiHZB 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗶𝗻-𝗵𝗼𝘂𝘀𝗲   • Full control and deep product integration   • Clear ownership of quality, trust, and UX   • Higher cost, slower iteration, and   • 𝗥𝗶𝘀𝗸 𝗼𝗳 𝗿𝗲𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 something that gets outdated quickly 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗮𝗽𝗽𝘀 • Meet users where intent already lives. • Leverage ChatGPT’s context and tools integration • 𝗟𝗲𝘀𝘀 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗮𝗻𝗱 𝗺𝗮𝘀𝘀𝗶𝘃𝗲 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝘆 𝗠𝘆 𝘁𝗮𝗸𝗲 This isn’t an either-or decision. Obviously.   • Build in-house AI where you truly differentiate. Pick carefully.   • Use ChatGPT apps/MCP servers for intent capture, orchestration, and reach. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝘁𝗵𝗮𝘁 𝗽𝗹𝘂𝗴 𝗶𝗻𝘁𝗼 𝗟𝗟𝗠 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹𝗹𝘆 𝘄𝗶𝗹𝗹 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱 𝗳𝗮𝘀𝘁𝗲𝗿. How are you realigning your strategy?

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