From: Joshua Fox (email@example.com)
Date: Mon Oct 05 2009 - 02:11:35 MDT
Thank you for that link. There were some worthwhile constructive
criticisms about SIAI. And overall it was a good practical summary of the
state of the AGI field.
On Sat, Oct 3, 2009 at 10:18 AM, Aleksei Riikonen <firstname.lastname@example.org> wrote:
> Michael Wilson (aka "Starglider") has recently written a "Mini-FAQ on
> Artificial Intelligence" on a science/philosophy subforum of a certain
> somewhat random forum where he sometimes ends up discussing things:
> I mention this mostly because the mini-FAQ is written in a style that
> I found to be somewhat unusually honest in a refreshingly funny way,
> example below (also, there are very few things in the document that
> I'd disagree with):
> ***** start of quote *****
> 9. Can you tell me what it is like in the field? Having spend most of
> my time doing school work I'm not sure about the current developments
> and what doing work in the field involves and how I could fit in.
> If you mean the history, culture, personalities etc of the field,
> numerous books have been written on the subject* and they are still
> restricted to a brief overview of each subfield. As a graduate, your
> choice is between staying in academia, commercial narrow AI work (the
> biggest areas are robotics, games and search/data mining - though not
> that even in games very few people do purely AI), or joining a wildly
> ambitious general AI start-up (e.g. Adaptive AI Inc).
> * 'Mind Design II', compiled by John Haugeland, is a great example,
> because it's basically a big collection of papers from many different
> subfields where researchers trash rival approaches and claim only
> their own can work, as politely as possible. Probably inaccessible to
> laypeople, but it's really funny if you're in the field.
> Unsurprisingly most commercial work is kind of dull - you normally
> pick the off-the-shelf algorithm that has the lowest technical risk
> and development time, slot it in, and spend most of your time doing
> requirements capture, functional testing, interfaces and other non-AI
> stuff anyway. Finance has some interesting decision support problems
> and in the US particularly there have always been be a fair number of
> military and intelligence projects trying to push the narrow AI
> envelope (you'll need a security clearance for that).
> Academia usually means slaving away for low pay implementing the
> research director's ideas, when you're not grading essays or drafting
> papers (for your superiors to stamp their names on and take credit).
> Eventually you'll get tenure (if you're lucky) and be able to do
> pretty much what you like, as long as it results in lots of papers
> published and looks good at university open days. Startups focused on
> general AI are usually exciting, stimulating stuff, but the jobs are
> nearly impossible to get, probably involve moving across the country
> or to another country, and last for an average of oh 24 months or so
> before the company runs out of funding and implodes.
> ***** end of quote *****
> Aleksei Riikonen - http://www.iki.fi/aleksei
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