If we knew that AI will be created by Google, and that it will happen in next 5 years, what should we do?

I think that superAI via uploading in inherent safe solution. https://en.wikipedia.org/wiki/Inherent_safety It also could go wrong in many ways, but it is not its default mode.

Even if it kill all humans, it will be one human which will survive.

Even if his values will evolve it will be natural evolution of human values.

As most human beings don't like to be alone, he would create new friends that is human simulations. So even worst cases are not as bad as paper clip maximiser.

It is also feasible plan which consist of many clear steps, one of them is choosing and educating right person for uploading. He should be educated in ethics, math, rationality, brain biology etc. I think he is reading LW and this comment))

This idea could be upgraded to be even more safe. One way is to upload a group of several people which will be able to control each other and also produce mutual collective intelligence.

Another idea is broke Super AI into center and circumference. In the centre we put uploaded mind of very rational human, which make important decisions and keep values, and in periphery we put many Tool AIs, which do a lot of dirty work.

• acausal
• arational
• agnonstic
• Gnon
• gnonstic
• Moloch
• outreact
• postrational
• postrationalist
• underreact

Thank you kindly for your help so far. :)

I started entering the live city data, and everything was going fine. Had to tweak the weights a bit to avoid some initial problems... then I got to Washington DC, and nothing I try seems to get it to work again. http://pastebin.com/q1JhUpSp is what I've ended up with; if I comment out DC's lines, I get a plot, if I put it back in, python just errors out, no matter what I set the weight divisor to. Any thoughts?

Welp, it looks like it's been longer since I tried tweaking basic code than I thought. I'm having trouble just trying to adjust the box's range to be from -124 to -71 and 25 to 53 (ie, longitude and latitude) instead of 1-10/1-10. I'm going to keep puzzling away, but anyone reading this, feel free to offer advice. :)

(I have some TV to watch later with the fam, so I won't mind doing some drudge work during the shows of typing out the city-list into an array of X/Y coordinates and population/weight, to paste into the Python script in place of randomly-generated points. ... Once I figure out how to get the script to accept a fixed array instead of randomly-generated points.)

Seeking help with Voronoi map generation

I'm hoping somebody here can help me create a particular map. I'd like to build a weighted Voronoi map of North America, with the weights corresponding to each urban area's population. Or, put another way, I'd like to start with http://lpetrich.org/Science/GeometryDemo/GeometryDemo_GMap.html , input the urban areas listed at https://en.wikipedia.org/wiki/List_of_urban_areas_by_population , and then tweak how the map is produced so that if one metroplex has a population of 1,000,000 and another has 10,000,000, the border between them is about 90% of the way closer to the smaller city.

I'm trying to build a scifi setting to put a story in, and have certain suspicions about what such a map would look like, but would like to confirm my intuition. I'm running Fedora Linux, and don't mind compiling oddball software, I just don't know which packages I'd need to even try to generate this thing.

By any chance, anyone here already able to generate the final product with just a few mouse-clicks? :) If not, anyone have any advice on how to get started?

When one person doesn't understand economics, we call it ignorance. When millions don't, we call it a political movement.

Scott Adams

humanity not extinct or suffering ->FAI black box -> humanity still not extinct or suffering

My girlfriend's cat poops on the carpet. The cat does poop in the litter boxes some of the time, and always urinates in them, but she also poops on the carpet several times a day in different places. (She also never buries her poop when she does use the boxes.) Any advice?

ML is search. If you have more parameters, you can do more, but the search problem is harder. Deep NN is a way to parallelize the search problem with # of grad students (by tweaks, etc.), also a general template to guide local-search-via-gradient (e.g. make it look for "interesting" features in the data).

I don't mean to be disparaging, btw. I think it is an important innovation to use human AND computer time intelligently to solve bigger problems.

In some sense it is voodoo (not very interpretable) but so what? Lots of other solutions to problems are, too. Do you really understand how your computer hardware or your OS work? So what if you don't?