Hong Kong AI Podcast

Jenny Wong is a corporate marketer with a creative writing background and zero IT experience. Six months ago she set out to build an AI that could write tonally-correct Cantonese pop lyrics. Every major LLM failed at Cantonese tone-matching. So she taught herself through Dify, n8n, Manus, and Genspark, found the local HK AI community on Telegram and Instagram, met 黃志華 — the godfather of the 0243 tonal notation system — and shipped Cantolyrics.ai, which now generates Hong Kong-quality lyrics in around four minutes. Our second fully-Cantonese episode.

A self-taught shader artist from Diamond Hill who beat Google projects to reach the Webby Awards top 5 — Lok Lok Wong builds 3D worlds that run on an iPad using nothing but math, Three.js, and raw curiosity. From particle simulations and shader alchemy to building his own 'Next.js for 3D' framework, Lok Lok shows how creativity and experimentation can replace expensive tools. Plus: using vector embeddings to search the Bible for life wisdom, running local AI on a MacBook Air, and why the metaverse is really about social connection.

Ronald's tech career predates AI being a boardroom imperative by decades — IBM (on the same GM manufacturing team as pre-Craigslist Craig Newmark), Wang Labs, HP, FedEx Singapore (where the client-server system later used for Apple/Foxconn supply chain was first architected), then computer forensics, then law. He co-founded MakeBell with Kenneth and teaches AI Law at CityU and CUHK. We dig into the symbolic-to-generative-to-neurosymbolic arc, why vibe-coded agents will break at enterprise scale (and the coming "fixer economy" for cleanup specialists), and one oral-exam trick for assessing students in the GPT era.

Jeremy is a private M&A lawyer who runs a legal AI startup — and runs his own LLM inference hardware out of his living room because he's been building custom PCs since age 14 (for Call of Duty), then mined Dogecoin on graphics cards, and discovered all that knowledge transfers perfectly to training and serving models. We go deep on why lawyers can't use ChatGPT, Claude, or Gemini with client data, why the entire private equity domain is essentially absent from LLM training corpora, why Qwen punches way above its weight, and why the pre-training ceiling is real.

Michelangiolo quit quantitative finance during COVID to teach himself computer science from his home in Italy — now he builds some of the most interesting search infrastructure in Hong Kong. We dig into why vanilla RAG is broken, his "covariate search" approach that applies variable weights across multiple semantic dimensions at once, and an algorithmic tagging method he's publishing that aims to outperform zero-shot LLM labelling at scale. Then the fun part: Michelangiolo wrote and illustrated a 460-page Lovecraftian comic called "The Crimson Duke" using Midjourney — discovering a probabilistic consistency trick for character generation along the way.

Our first fully-Cantonese episode. Kenneth Yip is the founder and general counsel of MakeBell — an AI legal tech startup building domain-specific AI assistants for Hong Kong legal professionals, with a focus on human-in-the-loop design, accuracy, and attorney-client privilege protection. We dig into why lawyers can't just use ChatGPT, IP and patent law in the AI era, and what a dual-track engineer-to-lawyer career looks like in Hong Kong.

William has been doing AI since high school — 12 years before GPT made it mainstream. We talk about what's really inside these models, the difference between knowledge and intelligence, latent space research, and why the labeled data problem shaped everything.

Nils dives into multi-robot coordination and collaborative perception — how phones, glasses, and robots build a shared understanding of physical space. From Warhammer AR overlays during COVID to a patented phone-to-phone calibration technique and retail robots deploying this year. Plus why Hong Kong is the perfect testbed for spatial computing, and the "great reversal" of computers coming out to us.

AI and intellectual property — it's the question everyone runs into eventually. We dig into copyright vs. training data, trade secrets as a practical alternative to patents, music IP disputes, and what Hong Kong's regulatory landscape means for AI builders.

We dig into how AI is changing who gets to build software, how rabbit holes are a good thing, and what it's like to ship product in Hong Kong. Alexander shares how he went from oat milk to building conversational interfaces that replace forms for wholesale F&B accounts.

Aug steps in front of the camera for this one. We talk about his journey with the I-Ching, the challenges in teaching AI 'taste', and why transparent systems matter more than clever ones.