AI is everywhere. It’s telling you what to buy, who to connect with, what you’re looking for when you enter a search query, and what to watch on TV. Many of these AI models, like Netflix, compare the shows you watched and your user preferences to the shows other users with similar preferences have watched to guess what shows you’ll like.
If you’ve talked to me recently, I likely told you about our efforts to build the ultimate Freedom-To-Operate (FTO) search engine, Dorothy FREEDOMTM (pronounced Braveheart style, obviously).
Last week we discussed relevance and the advantages that NLP based search engines have compared to their keyword searching counterparts. Because NLP understands the elements of a search query in context, NLP based engines, like Dorothy, have a clear advantage over keyword based search engines. We used relatively simple examples to illustrate this point. But, there’s more.
It’s back to school time. The neighborhood kids are back to work learning the basics: reading, writing, arithmetic, and Java or C, maybe Python. Let’s hope they’re are also developing an appreciation for learning and a hunger for knowledge.
We invited 22 people to preview Dorothy, and I’ve had butterflies in my stomach for more than a week.
All things considered, the USPTO patent database is well curated. Millions of patent documents (issued patents and application publications) are available for search and download. The documents include the complete application (title, abstract, specification, and claims), along with various important dates (filing, publication, and issue dates) and lists of references submitted or cited during prosecution. Not bad.
A lot of you (hopefully) were looking forward to our initial release of our patent search platform, "Dorothy," in May. I was too. However, we decided to pump the breaks, slow our roll, and do more testing before letting customers or potential customers onto the platform.