623 karma · joined October 22, 2015
""Google silently did something revolutionary on Thursday. It open sourced a tool called word2vec, prepackaged deep-learning software designed to understand the relationships between words with no human guidance. Just input a textual data set and let underlying predictive models get to work learning."
“This is a really, really, really big deal,” said Jeremy Howard, president and chief scientist of data-science competition platform Kaggle. “… It’s going to enable whole new classes of products that have never existed before.” https://gigaom.com/2013/08/16/were-on-the-cusp-of-deep-learn...
Spotify seems to be using it now: http://www.slideshare.net/AndySloane/machine-learning-spotif... pg 34
But here's the interesting part:
Lawrence Berkeley National Lab was working on an approach more detailed than word2vec (in terms of how the vectors are structured) since 2005 after reading the bottom of their patent: http://www.google.com/patents/US7987191 The Berkeley Lab method also seems much more exhaustive by using a fibonacci based distance decay for proximity between words such that vectors contain up to thousands of scored and ranked feature attributes beyond the bag-of-words approach. They also use filters to control context of the output. It was also made part of search/knowledge discovery tech that won the 2008 R&D100 award http://newscenter.lbl.gov/news-releases/2008/07/09/berkeley-... & http://www2.lbl.gov/Science-Articles/Archive/sabl/2005/March...
A search company that competed with Google called "seeqpod" was spun out of Berkeley Lab using the tech but was then sued for billions by Steve Jobs https://medium.com/startup-study-group/steve-jobs-made-warne... and a few media companies http://goo.gl/dzwpFq
We might combine these approaches as there seems to be something fairly important happening here in this area. Recommendations and sentiment analysis seem to be driving the bottom lines of companies today including Amazon, Google, Nefflix, Apple et al."
The study of epigraphy is the microscope while the study of human aging, extending human lifespan is the telescope that lets us see the stars in the future. With Epigraphy you can change dates in human history which changes a lot of what we thought we knew about ourselves.
The best NLP is based on principles that underpin epigraphy combined with neuroscience and research in cognition. The interesting part is that unbeknownst to most, the study of the past (epigraphy/NLP) is being used to solve for the future (space biosciences - LET radition, DNA repair, extending human lifespan making real space travel possible for the purpose of inhabiting other planets). Sounds out there, but this is what we work on at LBNL/DOE/DARPA/NASA related to predicting new interactions between proteins, genes etc.
Fun fact: Epigraphy, ciphers/deciphering, info security, cryptography are all related [2]
[1] https://en.wikipedia.org/wiki/Epigraphy
[2] From the epigraphy mailing list:
"Georges Depeyrot <Georges.depeyrot@ehess.fr>
To: epigraphy@yahoogroups.com
Sep 20, 2003 at 10:28 PM
Dear List members, We are publishing books on numismatics and economy (see Moneta <http://www.cultura-net.com/moneta/content.htm>). I just want to inform you that one of the books in press is devoted to "coins, money and epigraphy, 1st - 3rd c." (author, Pr St. Mrozek, Uty of Gdansk, Poland). It will concern the Roman Empire."
If you're building a house you don't start by picking out hammers and saws.
This takes being passionate about your data and its pre and postprocessing as a data engineer.