Tina Park @devtinapark
AI Engineer & Developer Advocate | Building AI products in public | React, Next.js, GenAI spoken.kitchen San Francisco Bay Area Joined March 2024-
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One of the most beautiful things about a hackathon isn’t the technology—it’s the people. Different backgrounds. Different languages. One shared goal: build. That’s the magic of a #hackathon. Technology brings people together, but collaboration is what makes it unforgettable.
Wrapped up our first AI hackathon in Medellín! 🚀🇨🇴 50+ RSVPs. 5 teams. Countless ideas turned into AI solutions for real-world problems. Huge thanks to everyone who joined and creative cool AI solutions for real-life problems! #AI #Hackathon #BuildInPublic #Medellín
🇨🇴 After an amazing turnout at our last AI meetup, we’re hosting our first Medellín AI Builder Hackathon this Saturday! 🚀 👩💻 Build an AI project 🤝 Meet founders & builders 🎤 Demo what you ship 📅 Sat, July 25 @ 11 AM 📍 El Poblado, Medellín Register: luma.com/fz9gm8qx
In Medellín, Colombia this month 🇨🇴 — meeting local AI builders, hosting meetups, speaking at an upcoming AI Tinkerers event, and finishing my voice AI app, #SpokenKitchen. Why here? Family and language — the two things my app is built on. Building AI in Medellín? Come say hi.
Do you love dogs? Do you love building AI? 🐶💻 Most hackathons end with a slide deck. This one ends with lives saved. Join @aivalleyio, PetZen, & Copper’s Dream in SF to build tools for real rescue dogs. $10K+ in prizes. Build for a living being. 👇 RSVP below!
Biggest takeaway: While everyone hunts for bigger models, the real shift is running existing models efficiently. Note: Apple's MLX ecosystem makes local text/VLM models incredibly practical on M-series Macs. Next up, I'll share what I built! 👀 (3/3)
Other massive efficiency wins from the day: 🧠 KV Caching — avoids recomputing past work ⚙️ torch.compile — optimizes compute execution 📄 Paged Attention — efficient memory management 🤝 Speculative Decoding — small model drafts tokens, large model verifies (2/3)
Spent last weekend at Google I/O Extended Lab and one demo changed how I think about AI performance. 🧠 Gemma 4 with zero optimizations took ~147 seconds to respond. With GGUF 6-bit quantization? ~3 seconds. Same hardware. No bigger GPU. Smarter software. 👇 (1/3)
Helping out the @aivalleyio team part-time and love what they're building. If you're in SF on 6/25, don't miss this casual Boba-thon with @Workato. Come hack on AI workflows and meet other builders. 🧋🛠️ RSVP: luma.com/axp8kxos
Full Article: tinapark.dev/blog/2026-06-1… #BuildInPublic #AIEngineering
AI models love "fixing" how our families talk. I tested @claudeai , @GeminiApp, and @Alibaba_Qwen for Spoken.Kitchen. Most over-correct bilingual slang or crash JSON under stress. A "Noise Inversion Paradox"—some actually perform better when the text is messy. Link👇
Writeup: tinapark.dev/blog/2026-06-0… Repo + raw data: github.com/devtinapark/sp… Interactive results: devtinapark.github.io/spoken-kitchen…
Market research used to mean 40 tabs and pricing pages that never load. I did the whole thing in an afternoon — from my terminal, with @nimble_search. The unlock: every business question becomes a command you can run. 👇Writeup + scripts
Building Spoken Kitchen to save family recipes I tested @OpenAI GPT-4o vs @DeepgramAI Nova-3 for transcribing English-Korean in a noisy kitchen. GPT-4o was more accurate. Nova-3 was faster & cheaper. For Spoken Kitchen, accuracy won. spoken.kitchen #BuildInPublic
@kevton_ @OpenAI @DeepgramAI Didn’t know this one — thanks! Looks like it supports auto language detection, which is my main requirement, and it’s actually cheaper than what I tested. Have you tried it on noisy or non-English audio? Tempted to add it as round 2.
I benchmarked @OpenAI GPT-4o-transcribe vs @DeepgramAI Nova-3 on real Korean/English audio for spoken.kitchen. 🏆 GPT-4o-transcribe • Better accuracy (CER 0.053 vs 0.077) • More robust to noise ⚡ Nova-3 • ~2× faster • ~13% cheaper Results 👇
We've reset 5-hour and weekly rate limits for all users on Pro and Max plans. We fixed an issue that caused some Claude Code sessions to spawn excessive parallel subagents, burning through usage faster than expected.
📖 Full write-up: tinapark.dev/blog/2026-06-0… 💻 Code + dataset: github.com/devtinapark/ko…
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