rbdn
The Terrifying Implications of Computers That Can Learn [video]
brew install emacs --HEAD --use-git-head --cocoa --with-gnutls --with-rsvg --with-imagemagickhttps://news.ycombinator.com/item?id=8700239
Edit: I've completely missed the videos. Amazing.
http://www.nature.com/nature/journal/v516/n7529/fig_tab/natu...
[0]: https://i.imgur.com/Bp3ra28.png
[1]: https://en.wikipedia.org/wiki/Fitts%27s_law
[2]: https://github.com/defunkt/dotjs
td { vertical-align: top }
td > img { background: repeating-linear-gradient(to right, rgba(0,0,0,0), rgba(0,0,0,0) 38px, rgba(0,0,0,0.3) 38px, rgba(0,0,0,0.3) 40px); margin-top: 4px; height: 12px!important }
div.votearrow { padding-bottom: 3px; background: url('https://i.imgur.com/UVPQXRX.png') !important; width: 20px!important;}Apple CoreGraphics framework logging input data to /tmp
Merkel speaks out against net neutrality
Terence Tao on Massively Collaborative Online Mathematics [video]
2015 Breakthrough Prize Symposia Videos (i.a. Terence Tao, Nima Arkani-Hamed)
If you are a recognized as human you could perhaps try it via Tor.
But how can you have something testable about something that does not exist yet? You would have to have evidence that an actual, intelligent program does something hostile, which is obviously impossible at the time since AGI has not been invented yet.
However, we do have evidence of naturally occuring hostile intelligence. If an AGI is vastly superior in some regards (for example through much tighter integration in knowledge and control systems), it could in fact pose a danger. The article even clearly states a hypothesis: "Humans, who are limited by slow biological evolution, couldn't compete and would be superseded."
We can’t really assign a probability of occurrence to scenarios like these, thus we have to include it in the list of events that could potentially wipe us out and which we may be able to prevent. Since people are actively working on AGI, it should probably be somewhere at the top where nuclear warfare, global warming and comet impacts are listed.
It’s not clear how sophisticated a neural network needs to be in order to yield AGI. It could be very simple (then you would be wrong with high probability), or it could extremely complex (then you would be right with high probability).
Looks like some sort of volumetric ray marching approach acceleratred by a signed distance field. Does anyone know what it is?