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From team workflows to national strategy, the real challenge with AI is how we structure thinking — not how fast we deploy tools. This morning, I found myself reading about the Asia Undercurrent Series session on Building & Securing Asia’s AI Future, moderated by Gregory C. Allen, with insights from Kay Firth-Butterfield, Dr. Ayesha Khanna, and Kyoko Yoshinaga — and it made me pause. We often look at AI through two very different lenses: At a global level - Nations are figuring out governance, security, and how to keep up with rapid development. At a team level (where I spend most of my time) - People are figuring out how to make Tuesday feel a little less chaotic. What struck me is how similar the underlying challenge is. Whether it’s a government or a 10-person team, the real bottleneck isn’t AI. It’s the system around it. How decisions are made. How workflows are structured. How people think about what “good work” even looks like. And that’s where the gap usually shows up. When I walk into an organisation to build AI systems, I’m not just dropping tools into their workflow. I’m helping them redesign the invisible architecture, the part that actually determines whether AI becomes an advantage or another shiny thing everyone ignores after three weeks. Today’s session reminded me that responsible AI doesn’t start at the policy level. It starts at the team level. With clarity. With structure. With people who know why they’re using AI, not just how. Asia’s AI future will depend on how intelligently we build systems at the macro level. But a company’s AI future? That starts with whether its people have room to think instead of firefight. If that’s the direction your team wants to grow into, I’m always open to a conversation. Sometimes the shift begins smaller than you’d expect. HMU for a coffee chat to discuss more for all the AI enthusiasts in the room!

Hey everyone, I just posted a detailed breakdown of A2UI, a new open-source project from Google that might solve the biggest bottleneck we have with AI Agents right now: Safety. It basically allows agents to "speak UI" and generate rich interfaces natively without the security risk of sending executable code to the client. I’ve covered how the architecture works and why the "Security First" approach is a big deal in my latest LinkedIn post. Check out the full breakdown here: https://www.linkedin.com/posts/karthikeyan-rajendran07_a2ui-generativeui-googleai-activity-7406502579196796929-u7mH?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAEbrn-ABgHp5yD8EZlAwTGEMwQD1vAsTKEw Let me know in the comments there if you think this is the future of Generative UI! 👇

📝 TL;DR Google is plugging its Gemini AI directly into Google Translate, so translations get more natural, context aware, and now even work live in your headphones. This turns Translate from a basic utility into a real time language assistant for conversations, content, and learning. 🧠 Overview Google has announced a major upgrade to Google Translate that uses Gemini, its latest AI model, to power better text translations and a new live speech to speech experience. The update promises more natural translations of idioms, slang, and nuanced phrases, plus real time audio translation you can listen to through any headphones. They are also expanding language learning tools inside the Translate app, so it becomes a place to both communicate and practice. 📜 The Announcement Google shared that Gemini is now powering state of the art text translation quality in Google Search and the Translate app. The rollout starts in the U.S. and India for English paired with nearly 20 languages, including Spanish, Hindi, Chinese, Japanese, and German. At the same time, Google is launching a beta for live speech to speech translation in the Android Translate app in the U.S., Mexico, and India, supporting more than 70 languages, with iOS and more countries planned next. ⚙️ How It Works • Gemini powered text translations - Translate now uses advanced Gemini capabilities to better understand context, so it can handle idioms, slang, and tricky phrases more naturally instead of doing word for word guesses. • Idioms and nuance aware - Examples like “stealing my thunder” are translated into phrases that match the meaning in the target language, not just the literal words, which makes outputs feel more human. • Live speech to speech in headphones - A new Live translate mode lets you hear real time translations directly in your headphones while you talk, listen to a lecture, or watch a show in another language.