Keep it Movin’
How was your week? 😷
In light of recent events, we released a COVID tracker to stay-up-date on the latest COVID news from sources across the 50 US states. We have linked local and national news sources in addition to the Health Departments and other authorities from each state. We are using 3 different APIs: one from Datawrapper’s server that connects to John Hopkins COVID data, Feedly’s news API, and Twitter’s streaming API. 😋
Check it out:
Currently, the COVID-19 pandemic is spreading across the United States. Under these conditions, one must know how to react…
With regards to the Big Bad NLP Database, we also added research papers to ~90% of the database! Special thank you to our researcher Gabi Alexandru for doing an amazing job. 😎
Datasets for various tasks in Natural Language Processing – Quantum Stat
FYI, stay indoors!
This week, the newsletter will be shorter than usual given the slow news cycle, I’m assuming it’s related to the current pandemic 😌.
– TensorFlow Quantum
– Electra Feel
– Hugging Papers
– Dataset of the Week: Jeopardy Questions
Google introduced an open-source library for the rapid prototyping of quantum ML models!
In order to understand quantum models, you need to familiarize yourself with two concepts : quantum data and hybrid quantum-classical models (current approach).
Quantum Data: (which can be generated) can be used for the simulation of chemicals and quantum matter, quantum control, quantum communication networks, quantum metrology, and much more.
Hybrid quantum-classical models: OK spoiler alert, these quantum models are not YET using quantum powered hardware (still too noisy), so we are left with using GPUs. So that’s why they are “hybrid”.
The good thing about this library is: if we can get used to these models now, by the time the processors are ready for prime-time, we will be able to crunch HUMONGOUS amount of data using quantum principles. But first, we need to dip our feet with the quantum framework — this is what Google is doing for us with this library.