Falcon Language Translation
Principal ML Scientist building industrial-scale language translation serving 50+ nations and 50,000+ translators — the origin story for cybernetic systems.
Before transformers changed everything, I was a Principal ML Scientist building language translation systems that served 50+ nations and over 50,000 professional translators. The Falcon platform at Google/WeLocalize was industrial-scale machine learning in the pre-transformer era — statistical models, feature engineering, human-in-the-loop feedback cycles that made translation better through collaboration between humans and machines.
The defining moment came at NVIDIA GTC 2015. Andrew Ng stood on stage and showed neural machine translation outperforming the best statistical MT systems. I was in the audience, and it crystallized something I’d been feeling: the future wasn’t AI replacing human translators. It was AI amplifying them. Cybernetic systems — human expertise and machine capability fused into something neither could achieve alone.
That insight became the seed of everything that followed. The Lattice Protocol’s federation model, the aDNA knowledge architecture, the rare disease hackathon format where clinicians and AI work as teammates — all of it traces back to watching neural MT work and understanding that the real power was in the collaboration, not the automation. Falcon taught me scale. GTC taught me vision. The combination sent me to Stanford.