To Hell and Back…
DARPA, the Defense Advanced Research Projects Agency, a.k.a. the Agency that Builds 👽 Spacecraft (ABAS), really loves NLP. More specifically, they really like building multi-modal models for enhancing knowledge graphs. Apparently, they also have their own YouTube channel called DARPAtv.🤷♂️
Halfway during the video above, the fellow dives into a word sense disambiguation problem regarding the word “tank” in the sentence “There is a tank outside my house” 🤣🤣.
And I thought I had big problems with semantics, guess DARPA tops me.
So, how was your week?
This week we added 25 new datasets to the Big Bad NLP Database. We had several user contributors: Philip Vollet, Arthit Suriyawongkul, Talha Anwar, and Gabriel Altay. Thank you very much!
This Week:
– The Missing Semester
– StreamingLighting SpaCy
– Questioning Meaning
– Research From Scratch
– COTA: Customer Obsession Ticket Assistant
– Multi-Lingual Datasets Stand Among Giants
– Investing in AI for Investment
– Dataset of the Week: MultiLingual Question Answering (MLQA)
The Missing Semester
MIT has more secrets. Apparently, MIT has a hidden Konami cheat code for learning about computer science that few know about. While searching their website, I found this:
Classes teach you all about advanced topics within CS, from operating systems to machine learning, but there’s one critical subject that’s rarely covered…
Video:
StreamingLighting SpaCy
I thought SpaCy couldn’t get any more visually stunning. But apparently, it can. With the help of Streamlit, you can achieve all the NLP goodies that SpaCy has to offer. You can even recreate it with Prasanna’s code (Github) inspired by Ines Montani.
If you haven’t checked out Streamlit, here’s their site:
Streamlit is an open-source app framework for Machine Learning and Data Science teams…
🤖Hacked together this Interactive NLP Pattern Reverse engineering tool with @spacy_io 🔥, @streamlit ✨
— Sai Prasanna (@sai_prasanna) February 8, 2020
and https://t.co/ZeVz4kg0DU 🛸.
📜 Code: https://t.co/yMDaejUwtD
😎 Inspiration: https://t.co/NahXObHRoT pic.twitter.com/shhPNBtKkx