Melinda Gates and Fei Fei Li unite
in an attempt to “liberate AI from guys with hoodies”. The main concern: “If we don’t get women and people of colo[u]r at the table — real technologists doing the real work — we will bias systems”.
Inequality of computing resources strangles academic research. Libby Kinsey:
“ […] what avenues remain open for compute-limited academic contribution? […] (I also wondered whether this will soon be a moot question, when GAFA et al have finished recruiting all the academics!)”.
Per The Economist story above, data is the rocket fuel for artificial intelligence. While the GAFAs and others seek to build monopolies on key datasets, unlike oil where any given barrel of oil is a perfect substitute for any other given barrel, data is not as fungible. True, the GAFAs have very interesting datasets about personal preferences and behaviour (and the reach of humans to leverage them on) but there are many types of data they currently don’t yet have.
It is heartening to some of these being released for developers to experiment on. This exciting dataset of LiDAR data
from Washington DC is now available on AWS, as a public dataset. (h/t Rodolfo Rosini).
“Liar, liar, pants on fire!”
The largest publicly available dataset for fake news detection covers one decade, and 12.8K manually labelled short statements.