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Description: DT is a biweekly newsletter covering productized AI, ML research, climate AI, and cool things.
About seven years ago, when I was a junior in high school, I built a “self-learning natural language search engine” called Wykki . It used “natural language” in that it was able to separate a user’s prompt like “How old is Barack Obama” into a question stub (“How old is blank ”) and a subject (“Barack Obama”) using some hard-coded tricks and simple heuristics. It then had a backend that connected those question stubs to properties in Freebase — think Wikipedia-as-a-database — so it could answer that questio
Once you knew about those tricks it wasn’t all that impressive — I wouldn’t use “natural language” or “self-learning” to describe Wykki today — but seeing it work for the first time was a pretty cool experience. Wykki was never more than a short-lived side project, but it got me really excited about the idea of accessing APIs (Freebase in this case) using natural language — and made me realize how difficult of a problem it is. Over the past few years I’ve had a lot of shower thoughts about how I’d approach
The Codex live demo
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