Yes. Just three bases so far.
No. Not without breaching NDAs. But, let’s be clear, you don’t have to be good at search to be more efficient than Airtable’s current search feature. Here’s as concrete as I can get.
Imagine a record contains four fields with these exact terms:
- I-15 @ Sahara (option list)
- daily count (option list)
- northbound (option list)
- 2023-03-13 (date selector)
And my search query is:
Show me today’s volume for Interstate 15 north.
It will link me to that exact record. How does it do this? Simple - with word vectors. The record itself was automatically vectorized in the vector database when it was last changed. The query was vectorized when it was asked. The query’s vectors were compared with all the vectors in the vector database, and the top scores were presented to me much the way Google search does. The record I sought had the highest score, and the inference was 86% confidence.
This approach sidesteps full-text and wildcard searches by adding inferred similarities that are impossible with inverted index architectures. This is why Google’s search business is at risk and why embeddings will likely put a big dent in findability across many apps.