Not being in the field, but having experience in making the judgement "Should I read this paper", here are a handful of observations:

For:

1. The paper has a handful of citations not entirely from the author (http://scholar.google.com/scholar?cites=8141802968877948536&as_sdt=2005&sciodt=0,5&hl=en) but by no means a huge number of citations.

2. The abstract is remarkably clear (it's clear that this is a slight extension of other author's work), and the jargon-y words are easily figured out based on gentle perusal of the paper.

3. It looks like this paper is actually also a chapter in a textbook (http://link.springer.com/chapter/10.1007/978-3-642-11876-0_8)

Against:

1. Nearly half of the paper's (very few) references in its reference section are self-citations.

I'd say it's worth reading if you're interested in it. Even the against-point above is more of a general heuristic and not necessarily a bad thing.

I have heard it claimed by people who know more about the history of philosophy than I do that it's less than perfectly reliable, and in particular that if Russell's account makes someone look silly then you should consider seriously the possibility that they were distinctly less silly than Russell makes them look.

(But I agree that it's a lovely book, and I wouldn't discourage anyone from reading it.)

Religion and Science by Bertrand Russell was interesting and informative. As a bonus, it's not that long.

A History of Western Philosophy by Bertrand Russell.

(To speed through books, I use VLC player, and then adjust the speed to 1.2X)

Academic conferences tends to be very technical, so don't expect to be able fully follow the talks. A review paper

When do you believe the first human-equivalent GAI will be created?

Are you a grad student? Because I don't know much about theoretical physics, but I find it very hard to believe much academic research could be automated.

I'm a post-doc doing research on computational linguistics. I can't imagine automating my work.

1 Hindsight bias? Quite a diagnosis there. I never specified the level of those algorithms.

I have, in my reply: probably AGI-level, i.e. too far into the haze of the future to be considered seriously.

2 Which part of theoretical physics is not math?

Probably the 1% that counts the most (I agree, 99% of theoretical physics is math, as I found out the hard way). It's finding the models that make the old experiments make sense and that make new interesting predictions that turn out to be right that is the mysterious part. How would you program a computer that can decide, on its own, that adding the gauge freedom to the Maxwell equations would actually make them simpler and lay foundations for nearly all of modern high-energy physics? That the Landau pole is not an insurmountable obstacle, despite all the infinities? That 2D models like graphene are worth studying? That can resolve the current mysteries, like the High Tc superconductivity, the still mysterious foundations of QM, the cosmological mysteries of dark matter and dark energy, the many problems in chemistry, biology, society etc.? Sure, it is all "symbol manipulation", but so is everything humans do, if you agree that we are (somewhat complicated) Turing machines and Markov chains. If you assert that it is possible to do all this with anything below an AGI-level complexity, I hope that you are right, but I am extremely skeptical.

Well, one thing that humans are superior at is modeling other humans, and their reactions to things. So to the extent that people do anything at all, they'll probably do that.

For example, music composition, writing fiction, and similar artistic endeavors require that the artist know what people enjoy. I think that that will be done by humans for the foreseeable future.

Also, things where you actually want the person doing it to be a person will continue. Counseling? I dunno.

My question is: What jobs will be the last ones to go, and why?

If your goal, in asking this question, is to plot a strategy that keeps you employed for as long as possible, then you probably ought to backtrack and look at the goals that's meant to serve. There are better ways to ensure long-term financial security, better ways to maintain a sense of purpose, and better ways to keep busy.

Organize all the known mathematics and physics of 1915 in a computer running the right algorithms, the ask it: 'what is gravity?' Would it output General theory of relativity? I think so.

You have fallen victim to the hindsight bias. The parameter space of the ways of reconciling Special Relativity with Newtonian gravity is quite large, even assuming that this goal would have occurred to anyone but Einstein at that time (well, Hilbert did the math independently, after communicating with Einstein for some time). Rejecting the implicit and unquestionable idea of a fixed background spacetime was an extreme leap of genius. The "right algorithms" would probably have to be the AGI-level ones.

I am a few steps away of earning a degree in theoretical physics specializing in quantum information theory. Theoretical quantum information theory is nothing but symbol manipulation in a framework on existing theorems of linear algebra.

"Theoretical quantum information theory" is math, not a natural science, and math is potentially easier to automate. Still, feel free to research the advances in automated theorem proving, and, more importantly, in automated theorem stating, a much harder task. How would a computer know what theorems are interesting?