Enterprise-scale machine translation with Spence Green, CEO of Lilt
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Spence shares his experience creating a product around human-in-the-loop machine translation, and explains how machine translation has evolved over the years. --- Spence Green is co-founder and CEO of Lilt, an AI-powered language translation platform. Lilt combines human translators and machine translation in order to produce high-quality translations more efficiently. --- 🌟 Show notes: - http://wandb.me/gd-spence-green - Transcription of the episode - Links to papers, projects, and people ⏳ Timestamps: 0:00 Sneak peak, intro 0:45 The story behind Lilt 3:08 Statistical MT vs neural MT 6:30 Domain adaptation and personalized models 8:00 The emergence of neural MT and development of Lilt 13:09 What success looks like for Lilt 18:20 Models that self-correct for gender bias 19:39 How Lilt runs its models in production 26:33 How far can MT go? 29:55 Why Lilt cares about human-computer interaction 35:04 Bilingual grammatical error correction 37:18 Human parity in MT 39:41 The unexpected challenges of prototype to production --- Get our podcast on these platforms: 👉 Apple Podcasts: http://wandb.me/apple-podcasts​​ 👉 Spotify: http://wandb.me/spotify​ 👉 Google Podcasts: http://wandb.me/google-podcasts​​ 👉 YouTube: http://wandb.me/youtube​​ 👉 Soundcloud: http://wandb.me/soundcloud​ Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack​​ Check out Fully Connected, which features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, industry leaders sharing best practices, and more: https://wandb.ai/fully-connected
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